The Great Crypto-ESG Debate

The Great Crypto-ESG Debate

In my 13 years of finance, I’ve never quite encountered anything like this current trading environment. That’s taking into account a global financial crisis, a European debt crisis, a “flash crash”, and various other bits of absolute market turmoil and panic. Specialising in ESG investing has allowed me to strengthen my investment management craft in a way I have not been able to previously. It has been riveting to see the extent to which sustainability issues have affected the market’s views on different securities. As exciting as ESG considerations are, they seem relatively boring in comparison to cryptocurrency issues. As fate would have it, the two have recently become juxtaposed, and this provides an opportunity for some interesting views on where ESG and Cryptocurrency issues go from here.

So, what is cryptocurrency?

Cryptocurrency (as I understand it) is a decentralised vehicle for conducting various financial transactions, similar to the way money works, but in a much less conventional sense. What is untraditional about cryptocurrencies is that they operate through blockchain technology (BCT) rather than more orthodox mediums such as banks. This BCT is supposed to enable greater transparency and safety for the transacting parties. The creators of cryptocurrencies, also known as miners, use computational powers to solve complex algorithms and produce tokens. These tokens can then be bought, sold, and traded as needed.

ESG takes into account environmental, social and good governance factors in business decision making. At Leading Point, we have recently published our ESG Rationale and Action plan; read about them here.

The issue

One of the tenets of ESG is environmental sustainability. In recent years, there has been a monumental move in thinking towards climate change and the overall impact on human life. As a result, there has been a concurrent shift in businesses becoming more sustainable. This dynamic shift in thinking is unlikely to reverse.

One of the criticisms of the cryptocurrency mining process is that it tends to use a staggering amount of energy. For example, Cambridge University suggests that generating Bitcoin requires more power annually than powering Argentina. Higher electricity usage translates to higher CO2 production, which naturally is a big no-no in the ESG space. Of course, in a cruel twist of irony, there have been reports that the production of conventional forms of fiat currency (e.g. gold and copper) surpasses Bitcoin. Still, this has not slowed down the most recent criticism of cryptocurrencies. Many have argued that we cannot achieve greater efficiency in sustainability and increased cryptocurrency dominance at the same time.

The role that technology is playing in transforming the ESG market is well-documented. Meanwhile, BCT has seen higher usability across several sectors. So, the question is; where do we go from here in the great ESG vs Crypto debate?

There will be a sharper focus on the sustainability of cryptocurrency mining.

From its peak (at the time of writing), Bitcoin has fallen by more than 40% after Elon Musk (long time Bitcoin advocate and environmentalist) announced that Tesla would no longer be accepting Bitcoin as payment due to environmental concerns about its heavy energy use. Cardano, regarded as a much more sustainably mined cryptocurrency, has increased roughly 70% between May 2nd and May 16th as its executives have made moves to have Tesla replace Bitcoin with its offering. At Leading Point, we expect investors to continue to weigh sustainability and efficiency vs the popularity of various types of cryptocurrencies. As an asset class, cryptocurrencies will invariably come under greater regulatory scrutiny.

There will be increased volatility in the cryptocurrency market.

Investor discernment over sustainability will lead to higher volatility in cryptocurrency markets. This scrutiny adds to a trading dynamic that is already highly volatile.

ESG will continue to present moral and ethical dilemmas

If you’ve ever spoken to a very opinionated climate change activist, they may have been the type of person who wants to shut down fossil fuel production worldwide. While this would have immediate environmental benefits, there would be substantial human costs. No more fossil fuels would immediately put thousands out of work. At the same time, we’d also need massive infrastructural investment across the globe to ready ourselves thoroughly for new energy inputs. As one can imagine, there are numerous considerations.

As the world moves towards a more sustainable and responsible future, we view businesses as active participants rather than judging them as being “good or bad” in an ESG sense. At Leading Point, we have committed to using our expertise across many industries to help organisations address their stewardship needs. My most recent article talks on this in detail, exploring stewardship and ESG solutions, and why it will always matter, especially in 2021, read more here.

Summary

ESG vs Cryptocurrency is a debate that is growing in importance. We expect that this will reflect increased volatility and greater regulatory scrutiny.


How Startups Can Increase Employee Freedoms Without Losing Control

 

How Startups Can Increase Employee Freedoms Without Losing Control

 

Introduction from Leading Point:

We love collaboration here at Leading Point and we are lucky enough to have some great clients and partners that feel the same. We work with some similar like-minded start-ups that share some of the same challenges and adventures as us. Below is a brilliantly informative article by our friends at Spendesk, explaining how startups can successfully create a positive working environment for their employees through trust and freedom. At Leading Point, this is something we firmly embody. Forging strong, meaningful relations is how we deliver our services, and without a satisfied, confident team, this simply can't be done. If you're a startup, and increasing employee freedoms without losing control is something your company is in need of, don’t fret, this piece will provide great tips on how to apply some quick and easy changes to make team building better and brighter for everyone. Overall, we are delighted to be office neighbours with Spendesk, and are looking forward to some more collaborations in the future. Watch this space!

Words by Ellen Masterson:

Every employer wants their team to be happy, efficient, and effective. Most recognise that the vast majority make good decisions and don’t need to be micromanaged. 

And yet, because of concerns about risk and compliance, many companies create hurdles that slow down their teams and take power away from actors. 

As HBR explains, “executives have trouble resolving the tension between employee empowerment and operational discipline. This challenge is so difficult that it ties companies up in knots. Indeed, it has led to decades’ worth of management experiments, from matrix structures to self-managed teams.”

Today, we have bad solutions to legitimate concerns. The answer to a need for process security isn’t to restrict access - it’s to create more secure processes. And as we’ll see, that doesn’t have to be complex. 

In this article, we’ll explore the reasons why companies struggle allowing freedom, and how a few simple shifts can make all the difference. 

What prevents employee freedoms today?

Before getting to the positive actions all businesses can take, let’s start by identifying why employees may not have the freedom they need to excel.

Here, we’re talking about two kinds of freedom: 

  • Freedom to make decisions and shape their own work scope and projects;
  • Freedom from excessive administrative and managerial pressure.

Together, these lead to more productive employees, a happier work environment, and faster growth.

In particular, we can look at two crucial causes.

A systemic lack of trust

This is fundamental. Many businesses simply aren’t structured to let team members think for themselves. Every decision must be scrutinized, and every action needs sign-off. 

Of course, some micromanaging is always to be expected. And some actions really do need sign-off. But many don’t, and it’s vital to consider the cost of always putting the breaks on as team members push forward.

A few simple questions to ask: 

  • Are our employees free to do their best work?
  • Are the rules we have in place helping, or hurting?
  • Can we trust our teams to make the right decisions, without always second guessing?

As we’ll see, there are plenty of positive ways to remove hurdles without losing control over what really matters. 

Closed-off systems and gatekeepers

Aside from the broad principle that employees should be free to make choices, there are common corporate practices that limit freedom - and not always for good reasons. Whether there’s limited institutional knowledge or a lack of trust, we make certain people responsible for processes, and lock everyone else out. 

A few examples: 

  • Key business data is only accessible by executive leadership. New revenue, customer churn, and average deal size can all help employees make smarter decisions. But many simply don’t have access. 
  • Corporate credit cards belong to a few select managers. This makes it very hard for anyone else to spend company money, creates hurdles, and slows down business. 

Today, we have ways to give employees more hands-on access to these processes without creating new risks or losing control. Let’s take a look at these now. 

How to increase freedom while retaining control

We have what seem to be two conflicting objectives. But employee freedom and organisational freedom can certainly co-exist. Just follow these four principles. 

1. Recognise trust as a core company value

If you want employees to feel free to do their best work, you obviously need to trust them to do so. What’s more, they need to know that they’re trusted to make decisions. This is empowering. 

Which means that trust needs to be enshrined as a company value. Many startups are now taking the time to carefully craft their culture code - this is seen as vital to startup success. It’s also hugely important in the hiring process, and helps you keep employees around for longer. 

So one way or another, trust needs to be in there. At Spendesk, for example, one of our core values is ownership. Each employee owns their scope and is empowered to make decisions. Which is another way of saying that the company trusts us. 

2. Build systems that everyone can use

We mentioned above the trouble with having closed-off systems. This manifests itself in two main ways: 

  1. Systems are so complex that only those with specific skills can use them;
  2. Most employees literally cannot access them - they lack the permissions or the tools to do so.

And of course, there is occasionally good reason for this. Average employees shouldn’t have access to the company bank account, for example. Which leads many finance teams to believe they need control over all spending. Or that only managers should have the right to spend company money. Neither of which are true. 

Instead, you need systems that guide employees, set out limits and rules, and prevent them from making costly mistakes. Team members are free to make choices, just within certain parameters.

One example is replacing company credit cards and expense claims with more tailored spend management solutions. These let you set the rules per employee or team, create spending limits, and require managerial approval above certain thresholds. 

So there you have full control. But employees have their own access - they don’t need to come begging for the corporate card - and finance teams don’t have to hold people’s hands throughout. The software guides them through each payment.

That was one just one example. But similar systems exist for HR and payroll, invoice processing, accounting, and a wide array of other corporate procedures. 

3. Speak in plain language

Another simple error that many companies make is in communication. If you make policies harder to understand than they need to be, you actually reduce the likelihood that teams follow them. Which then leads to two outcomes: 

  1. Reduced control, since people aren’t following the rules you create;
  2. Slower outcomes, because a manager or finance team member has to explain every transaction to employees one-to-one.

So the simple and impactful choice here is to ensure that internal policies and processes can be followed with no intervention. In practice, this means: 

  • No lengthy policy documents. The more you trust your team, the shorter you can make your travel and expense policy, for example. 
  • Keep jargon to a minimum. Documents should be easy to understand.
  • Build policies into processes. Even better than cross-referencing policy documents is to have them actually built-into systems. Assume that people haven’t read the document, so have systems that guide them through the process and keep them within boundaries.
  • Communicate clearly and repeat yourself. At a higher level, company values and expectations should be expressed openly and reiterated often. 

Overall, don’t confuse freedom with a lack of rules. Employees need the freedom to make choices within clearly set boundaries. Knowing what’s expected and allowed is freeing.

4. Remove obvious administrative hurdles

One clear impediment to freedom is creating hurdles and hoops to jump through. If employees can’t work smoothly and independently - and are always catching up on paperwork - it’s hard to say that they’re operating freely

But we can’t remove all admin for good. Instead, here are principles to make processes as painless as possible, while still maintaining compliance and control.

  • Go paperless. The very act of filing a form by hand, only to digitize it later adds time and effort. Replace all paper-based systems with digital-first alternatives, and things will move faster and freer.
  • Make processes and data easy to find. Employees should be able to answer their own questions and find solutions quickly. Otherwise, you’re forcing them to rely on others - usually HR and finance teams - which can quickly lead to interpersonal issues.
  • Make approvals fast and efficient. Purchases will usually need a manager’s approval. As will other areas of compliance. Make this smoother with automated approval workflows, and with systems that track approvals asynchronously. In other words, it shouldn’t require an email chain to find out who approved a particular transaction. Build this into your systems. 

We often think of admin as a necessary evil if we want to keep control and compliance. But you can have free-flowing, fast processes without creating unnecessary roadblocks along the way. 

Conclusion

As mentioned above, it’s natural to micromanage and to seek control over company decisions. But it’s not good. You’ve hired team members for their skills and ingenuity, so why would you restrict their use of them?

Brian Carney and Isaac Getz offer this example of a liberated company’s manager: “When her team shares a problem or an opportunity with her, she will not offer a solution. Instead, she asks them to find their own—after ensuring that there isn’t something she’s doing that would get in the way.”

For some businesses, achieving liberated company status would be a tectonic shift. It’s a worthwhile project, but one that will take years and plenty of soul searching.

But we’ve seen examples above of precise, easy-to-implement changes that have profound effects. Start with a few of these, and gradually work towards becoming a company that puts employee trust on a par with corporate control. 

After all, the two can naturally co-exist with no issue.

 

Author:

Ellen Masterson: Ellen Masterson is a UK and Ireland market expert at Spendesk, where she helps startups and scaleups establish simple yet robust spend management processes.


Stewardship Always Matters: 3 reasons why ESG is here to stay

It’s difficult to imagine a world without ESG. It certainly feels like it’s all anyone talks about now. It seems like everyone is covering it. Here’s Matthew, who has just become an ESG Consultant. There’s Annie, who completed her CFA Level 4 ESG-Investing certificate. And Jason, who has a daily blog post covering the top 10 largest US companies’ efforts concerning ESG.

It’s understandable that some of us are experiencing a level of “ESG-fatigue” as we continue to be washed in news, updates, regulations and content. But none of this is without good reason. All this is to preserve our quality of life as a species, and it will take herculean efforts spanning all across the globe in EVERY industry.

ESG is a relatively new term (reportedly coined in the early to mid-2000s after the now famous ‘Who Cares Wins’ conference). However, “stewardship” is not. The word ‘steward’ is derived from an old English saying describing an estate’s guardian; charged with ensuring the safety of the estate’s asset.

ESG factors can be traced as far back as the 17th and 18th century; when Methodists and Quakers set out guidelines for their followers about which companies they should invest in (this is the first recording “exclusionary screen”). Via advancements such as the Sullivan Principles in the 1970s (two guidelines that sought to bring economic pressure on ending apartheid in South Africa) and the growth of impact/social investing through the 1980s and 2000s, we find ourselves at a tipping point of what can overall be categorised as a stewardship revolution. But what makes this more than just another passing cloud?

1. Greater political and regulatory commitment

In April of this year, the US President, Joe Biden, hosted a virtual two-day summit where both the US and the EU pledged to cut carbon emissions by 50% by 2030. In the UK, the Task Force for Climate-Related Financial Disclosures (TCFD), has engaged in consultation to bring all large UK firms into regulation. This is regarding their governance, strategy, risk management and metrics and targets, as they relate to carbon emission reductions. It comes into effect by 2022. Japan has been steadily trying to incorporate higher diversity, inclusion and ESG into corporate governance codes. Similar efforts are being made in China and Korea.

It’s clear that there is already a buy-in from “the top”. We predict stricter ESG regulatory frameworks going forward, affecting both smaller and larger companies alike. We believe businesses should prepare for this eventuality sooner rather than later.

2. Greater efforts to standardise disclosures

One of the pain points in the ESG market is that data is often incomparable. The levels of disclosure differ by company, industry and geography. Additionally, among ESG research companies, there are differing views of levels of materiality (a crucial aspect of ESG incorporation) which has led to differing opinions on firms’ ESG readiness. It is widely accepted that industry ESG scores correlate somewhere between 0.3 and 0.5. Recently, The International Integrated Reporting Council (IIRC) and the Sustainability Accounting Standards Board (SASB) announced a 2021 merge into a unified organisation, The Value Reporting Foundation. This is intended to simplify sustainability reporting disclosures for companies and investors alike.

We think this represents a turning point in how companies and investors will be able to assess risk and opportunities; opening the doors for greater global collaboration on solving complex yet common ESG issues.

3. Technology opening new doors

Blockchain technology has a range of applications in the ESG market, e.g. enabling companies to more quickly identify instances of money laundering and bribery (higher governance); to playing a major part in data security and privacy. There has been a higher use of AI and other forms of technology to aid the ESG-data integration process. While there is some discrepancy as to the view of how intense technology exacerbates the climate change issue, there is a range of applications that technology can play in improving our current, and future quality of life.

We expect to see soaring use of tech in the ESG landscape going forward, as companies explore ways of becoming more efficient in executing their stewardship frameworks and action plans.

Summary

There always was and continues to be room for stewardship in every business model. In that vein,


Leading Point Listed as one of the Most Influential Fintech Companies of 2021

 

 

We are delighted to share we have been chosen as one of the Most Influential Financial Technology Companies of 2021 by Harrington Starr and the panel of equally influential judges.  

 

The past year could not have been further from the norm, and we can see this being reflected in the companies we work for or with. With all the changes and adjustments that came with this frenzied year, to be chosen as one of the Most Influential, is an achievement we are over the moon with. Leading Point has been recognised by Harrington Starr’s magazine, The Financial Technologist, as one of the most exceptional companies set to dominate the headlines in the year ahead. We’re thrilled to be featured amongst the brightest and most dynamic companies in the industry.

 

The Harrington Starr Group explains:

 

“This listing is particularly poignant as we see and hear from companies that have not only survived the pandemic, but come through stronger, bigger and even better than they were before.”

 

Being recognised in this way is a huge testament to the ever-growing Leading Point family and our determination to help businesses work better. Our growth journey will never stop - as those in the Fintech sector will appreciate, learning and growing will, and can never cease, as it is the key to solutions and success. Our founding Partner & COO Dishang Patel gushes over our triumph, saying:

 

“I’m delighted to be recognised and it is humbling to be amongst such incredible names within the fintech ecosystem. This award is special to us as it’s allowed the Leading Point culture and successes to be recognised and discussed.

 

After claiming a spot on this highly coveted list, Dishang then spoke on Harrington Starr’s podcast, Fintech Focus TV, discussing a range of intriguing topics, such as the values and practices that have really made Leading Point an exceptional place to work. He explores how we are continually attracting the best in the industry and how we have created a successful working environment that ensures we are building and retaining our relations and the best talent in the sector.  

 

Check out Dishang on Fintech Focus TV: https://www.youtube.com/watch?v=mn12YAbTf6A 

Click below to enjoy issue 1, free of charge, featuring Leading Point:

 

#mostinfluentialfinancialtechnologists2021

 

Who we are:

 

Leading Point is a digital transformation company, dedicated to helping business work better. We’re transformation specialists fluent in people, data and innovation. Our software products and bespoke consultancy services give you greater control and more peace of mind at every stage of your development. Helping you seamlessly progress from where you are today to where you need to be tomorrow.

 


GDFM & Leading Point Partnering for Smarter Regulatory Health Management

GDFM and Leading Point collaborate to deliver innovative and efficient regulatory risk management to our clients and through the SMART_Dash product; enabling consistent, centralised, accessible regulatory health data to assist responsible and accountable individuals with ensuring adequate transparency, for risk mitigation decision making and action taking.  This is complemented by a SMART_Board suite for Board level leadership and a more detailed SMART_Support suite for regulatory reporting teams.

We are delighted that SMART_Dash has been shortlisted in 3 categories in this year's prestigious RegTech Insight Awards in Europe, which recognises both established solution providers and innovative newcomers, seeking to herald and highlight innovative RegTech solutions across the global financial services industry.

GD Financial Markets Head of Regulatory Compliance Practice and SMART_Dash Co-creator Sarah Peaston "Centralised, consolidated, consistent regulatory health transparency and tracking is key to identifying and managing regulatory and operating risk.  I am delighted that SMART_Dash has been recognised as a new breed of solution that practically assists Managers, Senior Managers and Leadership with managing their regulatory health through the provision of the right information, at the right level to the right seniority”.

Leading Point CEO Rajen Madan "Our vision with SMART_Dash is to accelerate better regulatory risk management approaches and vastly more efficient RegOps. As financial services practitioners we are acutely aware of the time managers spend trying to make sense of their regulatory and operating risk areas from a multitude of inconsistent reports. SMART_Dash enables the shift to an enhanced way of risk management, which creates standardisation and makes reg data work for your business. We are very grateful to the COO, CRO and CFOs whom have contributed to its development and help the industry move forward”.

GDFM and Leading Point are rolling out the SMART_Dash suite to the first set of industry consortium partners progressively in H1 2021, and thereafter open to a wider set of institutions.


The Composable Enterprise: Improving the Front-Office User Experience

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By Dishang Patel, Fintech & Growth Delivery Partner, Leading Point Financial Markets.

The past six months have by no means been a time of status quo. During this period of uncertainty, standards have been questioned and new ‘norms’ have been formed.

A standout development has been the intensified focus on cloud-based services. Levels of adoption have varied, from those moving to cloud for the first time, to others making cloud their only form of storage and access, and with numerous ‘others’ in between.

One area affected adversely (for those who weren’t ready) but positively (for those who were) is software. ‘Old-school’ software vendors – whose multi-million-pound solutions were traditionally implemented on premise at financial institutions, whether as part of a pure ‘buy’ or broader ‘build’ approach – have worked hard to offer cloud-based services.

The broad shift to working from home (WFH) as a result of the Covid-19 pandemic has tested the end-user experience all the way from front to back offices in financial institutions. Security, ease of access and speed are all high on the agenda in the new world in which we find ourselves.

The digitisation journey

With workforces operating globally, it is difficult to guarantee uniform user experiences and be able to cater for a multitude of needs. To achieve success in this area and to ensure a seamless WFH experience, financial institutions have moved things up a level and worked as hard as software providers to offer cloud-based solutions.

All manner of financial institutions (trading firms, brokerages, asset managers, challenger banks) have been on a digitisation journey to make the online user experience more consistent and reliable.

Composable Enterprise is an approach that those who have worked in a front office environment within financial services may have come across and for many could be the way forward.

 

Composable Enterprise: the way forward

Digitisation can come in many forms: from robotic process automation (RPA), operational excellence, implementation of application-based solution, interoperability and electronification. Interoperability and electronification are two key components of this Composable Enterprise approach.

Interoperability – whether in terms of web services, applications, or both –  is an approach that can create efficiencies on the desktop and deliver improved user experience. It has the potential to deliver business performance benefits, in terms of faster and better decision making with the ultimate potential to uncover previously untapped alpha. It also has two important environmental benefits:

1) Reducing energy spend;

2) Less need for old hardware to be disposed of, delivering the reduced environmental footprint that organisations desire.

Electronification, for most industry players, may represent the final step on the full digitisation journey. According to the Oxford English Dictionary, electronification is the “conversion to or adoption of an electronic mode of operation,” which translates to the front office having all the tools they need to do their jobs to the best of their ability.

The beauty of both interoperability and electronification is that they work just as well in a remote set up as they do in an office environment. This is because a good implementation of both results in maximising an organisation’s ability to use all the tools (trading platforms, market data feeds, CRMs, and so on) at their disposal without needing masses of physical infrastructure.

Because of the lower barriers (such as time and cost) of interoperability, financial institutions should start their digitisation journeys from this component and then embark on a larger and more complicated move to electronification.

Composable Enterprise is about firms being able to choose the best component needed for their business, allowing them to be more flexible and more open in order to adapt to new potential revenue opportunities. In these challenging times, it is no surprise that more and more financial institutions are adding Composable Enterprise as a key item on their spending agenda.

 

 

 

 

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"The broad shift to working from home as a result of the Covid-19 pandemic has tested the end-user experience all the way from front to back offices in financial institutions."

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"It has the potential to deliver business performance benefits, in terms of faster and better decision making with the ultimate potential to uncover previously untapped alpha."

[/et_pb_text][et_pb_text disabled_on="on|on|off" _builder_version="4.4.8" min_height="15px" custom_margin="427px|||||" custom_padding="1px|||||"]

"The beauty of both interoperability and electronification is that they work just as well in a remote set up as they do in an office environment."

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Responsible for delivering digital FS businesses.

Transforming delivery models for the scale up market.

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Contact Us

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Information Security in a New Digital Era

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Shifting priorities

 

The 2020’s pandemic, subsequent economic turmoil and related social phenomena has paved the way for much-needed global digital transformation and the prioritisation of digital strategies. The rise in digitisation across all businesses, however, has accelerated cyber risk exponentially. With cloud-based attacks rising by 630% between January and April 2020(1), organisations are now turning their focus on how to benefit from digitisation whilst maintaining sufficiently secure digital environments for their services and clients.

 

A global challenge

 

A new digital setup could easily jeopardise organisations’ cyber safety. With data becoming companies’ most valuable asset, hackers are getting creative with increasingly-sophisticated threats and phishing attacks. According to the 2019 Data Breach Investigation Report(2) by Verizon, 32% of all verified data breaches appeared to be phishing.
As data leaks are increasing (3,800 alone in 2019), so is the cyber skill shortage. According to the MIT Technology Review report(3), there will be 3.5 million unfulfilled cybersecurity jobs in 2021; a rise of 350%. As a result of Covid-19 and digitised home working, cybersecurity professionals are high in demand to fill the gaps organisations’
currently face.

 

The way forward

Although tackling InfoSec breaches in the rapidly-evolving digital innovation landscape is not easy, it is essential to keep it as an absolute priority. In our work with regulated sector firms in financial services, pharma and energy as well as with fintechs, we see consistent steps that underpin successful information security risk management. We have created a leaderboard of 10 discussion points for COOs, CIOs and CISOs to keep up with their information security needs:

  • Information Security Standards
    Understand information security standards like NIST, ISO 27001/2 and BIP 0116/7 and put in place processes and controls accordingly. These are good practices to keep a secure digital environment and are vital to include in your risk mitigation strategy. Preventing cyber attacks and data breaches is less costly and less resource-exhaustive than dealing with the damage caused by these attacks. There are serious repercussions of security breaches in terms of cost and reputational damage, yet organisations still only look at the issue after the event. Data shows that firms prefer to take a passive approach to tackle these issues instead of taking steps to prevent them in the first place.
  • Managing security in cloud delivery models
    2020 has seen a rise in the use of SaaS applications to support employee engagement, workflow management and communication. While cloud is still an area in its preliminary stages, cloud adoption is rapidly accelerating. But many firms have initiated cloud migration projects without a firm understanding and design for the future business, customer or end user flows. This is critical to ensuring a good security infrastructure in a multi-cloud operating environment. How does your firm keep up with the latest developments in Cloud Management?
  • Operational resilience
    70% of Operational Risk professionals say that their priorities and focus have changed as a result of Covid-19(4). With less than half of businesses testing their continuity and business-preparedness initiatives(5), Coronavirus served as an eye-opener in terms of revisiting these questions. Did your business continuity plan prove successful? If so, what was the key to its success? How do you define and measure operational resilience in your business? Cross-functional data sets are increasingly vital for informed risk management.
  • Culture
    Cyber risk is not just a technology problem; it is a people
    problem. You cannot mitigate cyber risks with just technology;
    embedding the right culture within your team is vital. How do you make sure a cyber-secure company culture is kept up in remote working environments? Does your company already have an information security training plan in place?

 

  • Knowing what data is important
    Data is expanding exponentially – you have to know what you need to protect. Only by defining important data, reducing the signal-to-data noise and aggregating multiple data points can organisations look to protect them. As a firm, what percentage of your data elements are defined with an owner and user access workflow?
  • Speed of innovation means risk
    The speed of innovation is often faster than the speed of safety. As technology and data adoption is rapidly changing, data protection has to keep up as well – there is little point in investing in technology until you really understand your risks and your exposure to those risks. This is increasingly true of new business-tech frameworks, including DLT, AI and Open Banking. When looking at DLT and AI based processes - how do you define the security and thresholds?
  • Master the basics
    80% of UK companies and startups are not Cyber Essentials ready, which shows that the fundamentals of data security are not being dealt with. Larger companies are rigid and not sufficiently agile – more demands are being placed on teams but without sufficient resources and skills development. Large companies cannot innovate if they are not given the freedom to actually adapt. What is the blocker in your firm?
  • Collaborate with startups
    Thousands of innovative startups tackling cyber security currently exist and many more will begin their growth journey over the next few years. Larger businesses need to be more open to collaborating with them to help speed up advancements in the cyber risk space.
  • The right technology can play a key role in efficiency and speed
    We see the emerging operating models for firms are open API based, and organisations need to stitch together many point solutions. Technology can help here if deployed correctly. For
    instance, to join up multiple data, to provide transparency of
    messages crossing in and out of systems, to execute and detect
    information security processes and controls with 100x efficiency and speed. This will make a material difference in the new world of
    financial services.
  • Transparency of your supply chain
    Supply chains are becoming more data-driven than ever with increased number of core operations and IT services being outsourced. Attackers are using weak supplier controls to compromise client networks and dispersed dependencies create increased reliance and risk exposure from entities outside of your direct control. How do you manage the current pressure points of your supplier relationships?

 Next steps

 

Cyber risk (especially regarding data protection) is simultaneously a compliance problem (regulatory risk, legal risk etc.), an architecture problem (infrastructure, business continuity, etc.), and a business problem (reputational risk, loss of trust, ‘data poisoning’, competitor intelligence etc.). There are existing risk assessment frameworks for managing operational risk (example: ORMF) – why not plug in?
Getting the basics right, using industry standards, multi-cloud environments and transparency of supply chain are good places to start. These are all to do with holistic data risk management (HRM).
While all these individual issues pose problems on their own, they can be viewed through inter-relationships applying a holistic approach where a coordinated solution can be found to efficiently manage these issues as a whole. The solution lies in taking a more deliberate approach to cyber security and following this 4-step process:

 IDENTIFY
 ORGANISE
 ASSIGN
 RESOLVE

 

 

Find out more on Operational Resilience from Leading Point:
https://leadingpointfm.com/operational-resilience-data-infrastructure-and-aconsolidated-risk-view-is-pivotal-to-the-new-rules-on-operational-risk/#_edn2

Find out more on Data Kitchen, a Leading Point initiative:
https://leadingpointfm.com/the-data-kitchen-does-data-need-science/

 

 

(1) https://www.fintechnews.org/the-2020-cybersecurity-stats-you-need-to-know/

(2) https://www.techfunnel.com/information-technology/cyber-security-trends/

(3) https://www.technologyreview.com/2018/10/18/139708/a-cyber-skills-shortage-means-students-are-being-recruited-to-fight-off-hackers/

(4) https://leadingpointfm.com/operational-resilience-data-infrastructure-and-a-consolidated-risk-view-is-pivotal-to-the-new-rules-on-operational-risk/#_edn2

(5) https://securityintelligence.com/articles/these-cybersecurity-trends-could-get-a-boost-in-2020/

 

 

 

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"With data becoming companies’ most valuable asset, hackers are getting creative with increasingly-sophisticated threats and phishing attacks."

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"Preventing cyber attacks and data breaches is less costly and less resource-exhaustive than dealing with the damage caused by these attacks."

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"70% of Operational Risk professionals say that their priorities and focus have changed as a result of Covid-19."

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Rajen Madan

Founder & CEO

rajen@leadingpoint.io

Delivering Digital FS businesses. Change leader with over 20 years’ experience in helping firms with efficiency, revenue and risk management challenges

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Aliz Gyenes

Leading Point

aliz@leadingpoint.io

Data Innovation, InfoSec, Investment behaviour research Helping businesses understand and improve their data strategy via the Leading Point Data Innovation Index

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How Leading Point can help

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3 Reasons Why All Startups Should Embrace ESG

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Environmental, Social & Governance (ESG) issues are firmly on the board agendas of large, publicly-listed companies. 2021 marks the year in which VC-backed startups need to follow suit. What is the best way to achieve this change? 

Some smaller companies have already made the move. A recent survey (1) of pre-seed and series A startups found that almost two thirds already have some ESG policies in place. Of those who didn’t, over half were now seriously considering them.  

Startups can benefit from an ESG focus for three key reasons: a higher chance of investment, attracting better talent and risk mitigation.

 

Increased investment

Over the last five years there has been an explosion in VC funds focusing on startups in the ESG space. One such fund is DBL Partners. They are currently looking to raise $450m for their fourth fundt. Their mission involves investing in companies which provide capital returns while also enabling environmental and social benefits. 

More recently, an increasing number of non-ESG focused VC firms are embedding ESG values into the companies they invest in. For example, Christine Tsai, CEO of 500 Startups, one of the most active global early stage venture capital firms whose “unicorn investments” include Credit Karma, Canva, Grab and Talkdesk, said that startups should implement ESG early on (2)

If startups want to stand out, they should embed ESG policies into their business model, principles and culture at the beginning rather than trying to “retro-fit” policies later under the pressure of investors or others. 

 

Top talent attraction and retention

Startups with ESG values embedded in the business are more attractive to the best talent. This gives them a tangible competitive advantage.

Millennials currently make up 50% of the global workforce (3). A recent study (4) found that more than 40% said they had joined a firm because they performed better on sustainability. The same study showed that they are 70% more likely to stay longer if they feel the company has a strong sustainability plan. 

However, relying on ESG policies and reporting (internally and externally) alone is not enough to benefit. Startups need to embrace a culture of openness at the core of their business. They must be honest to their stakeholders about their ESG weaknesses as well as their strengths. Only then will their ESG communications be authentic and have real impact on talent attraction and more importantly retention. 

 

Risk mitigation 

ESG policies can de-risk young companies as policy adoption becomes more difficult as they grow. A recent white paper (5) argued that startups are even more vulnerable to negative reputational impacts compared to more established firms, given their relatively small size and high growth characteristics.

For example, German fintech success story Wirecard shook the financial world earlier this year as it became clear that over $2bn was missing from their balance sheet (6). Also, in late 2019, it was reported that the CEO and founder of luggage startup AWAY, which had raised over $31 million, openly bullied and belittled her employees (7). This led to a media backlash against the company which greatly impacted their growth and market position.

With stronger governance policies and procedures, these scandals may have been avoidable. Startups which embed strong governance policies early on are much less likely to run into such issues.

How to integrate ESG into a VC-backed startup

It can be difficult for founders to decide which ESG policies to apply, which areas to focus on and how to communicate their outcomes authentically to stakeholders. Yet this is something which investors and top talent are increasingly looking for.  

ESG action plans should follow a staged approach, with a roadmap assessed and realigned at each funding round:  

  • Map your current ESG strengths
     Work out what you are already doing right, supported by resources such as the Sustainable Accounting Standards Board Materiality Map to work out which ESG policies and metrics are relevant for your industry. Also, map out the ecosystem of the different stakeholders your company interacts with, including customers, suppliers, regulators and employees. 
  • Develop your goals and measure your progress
     Collect the relevant data to work out your current baseline and decide goals for the short, medium and long term, building a dashboard incorporating relevant Key Performance Indicators (KPIs) to track progress. ESG standards are complex and can need a multitude of different data points depending on the type of industry.  
  • Communicate your position
    Regularly collect and communicate your ESG data to relevant stakeholders including investors, employees, regulators, consumers and the media. Publish your ESG successes and milestones on your social media channels and your recruitment page. You might also want to consider inviting in third party auditors to validate your ESG data and methods of collecting it, and look into external certification e.g B-corp status. 

This brief overview may not answer all your questions. 

If you would like to hear more about how we can help VCs and startups manage, improve and communicate their ESG impact please get in touch. 

1. 500 Startups (2020) Survey results: The Impact of Covid-19 on the Early-Stage Investment Climate,  https://survey.500.co/investor-survey-report-download/
2.
Venture Capital Journal (Jun 2020) 500 Startups makes ESG top of mind going forward,https://www.venturecapitaljournal.com/500-startups-makes-esg-top-of-mind-going-forward/
3.
KMPG (2017) Meet the millennials https://home.kpmg/content/dam/kpmg/uk/pdf/2017/04/Meet-the-Millennials-Secured.pdf
4. Fast Company (Feb 2019) Most millennials would take a pay cut to work at a environmentally responsible company,https://www.fastcompany.com/90306556/most-millennials-would-take-a-pay-cut-to-work-at-a-sustainable-company
5. CDC investment works & FMO Entrepreneurial Investment Bank (Jan 2020) Responsible venture capital Integrating environmental and social approaches in early-stage investing,  https://assets.cdcgroup.com/wp-content/uploads/2020/01/16092500/Responsible-Venture-Capital.pdf
6. Markets Insider (Jun 2020) How $2 billion vanished from the balance sheet of Wirecard, according to a forensic financial expert,
https://markets.businessinsider.com/news/stocks/wirecard-scandal-numbers-financial-forensic-expert-breakdown-2020-6-1029332810
7.
The Verge (Dec 2019) Away’s founders sold a vision of travel and inclusion, but former employees say it masked a toxic work environment, https://www.theverge.com/2019/12/5/20995453/away-luggage-ceo-steph-korey-toxic-work-environment-travel-inclusion

 

 

 

 

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"Startups can benefit from an ESG focus for three key reasons: a higher chance of investment, attracting better talent and risk mitigation."

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"If startups want to stand out, they should embed ESG policies into their business model, principles and culture at the beginning rather than trying to “retro-fit” policies later under the pressure of investors or others."

[/et_pb_text][et_pb_text disabled_on="on|on|off" _builder_version="4.4.8" min_height="15px" custom_margin="427px|||||" custom_padding="1px|||||"]

"ESG policies can de-risk young companies as policy adoption becomes more difficult as they grow."

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Environmental Social & Governance (ESG) and Sustainable Investment

Client propositions and products in data-driven transformation in ESG and Sustainable Investing.

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Responsible for delivering digital FS businesses.

Transforming delivery models for the scale up market.

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Upcoming blogs:

 

This is the fourth in a series of blogs that will explore the ESG world: its growth, its potential opportunities and the constraints that are holding it back. We will explore the increasing importance of ESG and how it affects business leaders, investors, asset managers, regulatory actors and more.

 

Artificial Intelligence: the Solution to the ESG Data Gap? In the second part of our Environmental, Social and Governance (ESG) blog series, Anya explores the potential opportunities surrounding Artificial Intelligence and responsible investing.

 

Riding the ESG Regulatory Wave: In the third part of our Environmental, Social and Governance (ESG) blog series, Alejandra explores the implementation challenges of ESG regulations hitting EU Asset Managers and Financial Institutions.

 

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How Leading Point can help

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By using our cloud-based data visualisation platform to bring together relevant metrics, we help organisations gain a standardised view and improve your ESG reporting and portfolio performance.  Our live ESG dashboard can be used to scenario plan, map out ESG strategy and tell the ESG story to stakeholders.

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AI helps with the process of ingesting, analysing and distributing data as well as offering predictive abilities and assessing trends in the ESG space.  Leading Point is helping our AI startup partnerships adapt their technology to pursue this new opportunity, implementing these solutions into investment firms and supporting them with the use of the technology and data management.

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Implementing ESG regulations and providing operational support to improve ESG metrics for banks and other financial institutions. Ensuring compliance by benchmarking and disclosing ESG information, in-depth data collection to satisfy corporate reporting requirements, conducting appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.

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Riding the ESG Regulatory Wave

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Riding the ESG Regulatory Wave 

In the third part of our Environmental, Social and Governance (ESG) blog series, Alejandra explores the implementation challenges of ESG regulations hitting EU Asset Managers and Financial Institutions.

A new brand of Regulation

Whilst the world is still recovering from the effects of COVID-19, and adapting to the issues uncovered as a result of the Black Lives Matter movement, adopting sustainable practices and timely adherence to ESG regulations is pivotal in safeguarding a company’s long-term success.

Widely recognised as being more than a fad or a feel-good exercise, it is clear that creating stronger ESG alignment correlates with higher equity returns.* Compliance with ESG regulations will create monumental changes to the financial services industry and it will take well-rounded experience in regulatory transition to ensure seamless adherence and minimal disruption to operations.

Similar to the Know Your Client (KYC) and Anti Financial Crime (AFC) regulation landscape of five years ago, ESG regulation implementation will require heavy lifting from the advisory and consulting sectors. Compounded with this, firms need a commitment to transition and adjust investment principles and processes in order to achieve these ambitious goals.

This influx of new rules reflects the regulators attempts to catch up with longstanding investor demand.** As a result of these optional and mandatory principles, businesses are understanding the importance of having well-governed and socially-responsible practices in place, making it the optimal time for financial institutions to start planning for ESG rules implementation.

 

Upcoming EU ESG Regulation Examples

  1. MiFID II Amendments (in force Q1 2020) Advisers will need to be more proactive with customers in relation to ESG considerations by asking them about their preferences
  2. The Taxonomy Regulation (in force July 2020) Sets out a common classification system to determine which  economic activities and investments can be treated as “environmentally sustainable”
  3. Benchmarks Regulation Has been amended to include two new benchmarks to help increase transparency and avoid greenwashing 
    4. Stress Testing Rules for Banks Tools and mechanisms to integrate ESG factors into the EU prudential framework, banks’ business strategies, investment policies and risk management processes 

    In the last three years, ESG regulations grew by 158% in the UK, and by 145% in the US and Canada.***

The most regulated topics are business ethics and climate change in financial services, energy use and consumer rights in the US utilities, and product and service safety in healthcare and pharmaceuticals.


These regulations will affect many areas significant to asset managers, from corporate governance to process and product considerations. Implementing these changes effectively in order to gain a competitive advantage over their peers and avoiding the burden of non-compliance will mean drawing up consistent definitions, identifying the data points needed to set comparable targets, monitoring investments and reporting to regulators. Additionally, they will have to consider their role in the design, delivery and sale of financial services and products. 


Data, Benchmarking and Disclosure

When it comes to benchmarking and disclosing data it is important to highlight the difference between ‘sustainability’ and ‘ESG’. Specifically with ESG information, the devil is in the detail. Asset managers must perform this in-depth data collection to satisfy their own corporate reporting requirements, to conduct appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.

Because asset managers produce, distribute and ingest financial and non-financial ESG data, these regulations can bring competitive advantage and clarity to those who implement them effectively.

A typical asset manager will have to ingest endless subsets of relevant ESG considerations from various asset classes, industries and geographies all of which depend on differing underlying data in order to reach informed and accurate decisions. The major challenge is being able to determine the data points required to set comparable targets, monitor investments, and measure and compare performance across sectors, industries, and national or regional borders.

Implementation Insights

A proactive approach is essential as it enables firms to gain an early understanding of the changes needed to their operations and position them as credible, trusted partners with regulators.

Once an organisation has established its guiding vision and strategy for implementing investment principles, the real work begins. Updates to compliance, risk management, product development, data management, sales and reporting processes all need to take place and have to be coordinated across business units and functions to ensure consistency and traceability. 

Analysis and assembly of regulations, standards and good practices, clear and up-to -date management views and evaluation of peer approaches all have to be part of a holistic regulatory implementation approach.

Whilst trying to predict the future and see the outcomes of implementing these future-facing requirements, it is important to remember the importance of flexibility and adaptability. The transition has to be well-managed and sustainable to be maintained. It is also important to incorporate lessons learnt from previous regulatory implementations. The organisations who will come out the strongest will be those who take the time to invest and begin with a good understanding of the changes in the operational environment and internal capabilities required.

https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/five-ways-that-esg-creates-value

** https://www.unpri.org/signatories/signatory-resources/signatory-directory

*** https://www.datamaran.com/global-insights-report

 

 

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"Compliance with ESG regulations will create monumental changes to the financial services industry and it will take well-rounded experience in regulatory transition to ensure seamless adherence and minimal disruption to operations."

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"Because asset managers produce, distribute and ingest financial and non-financial ESG data, these regulations can bring competitive advantage and clarity to those who implement them effectively."

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"Similar to the Know Your Client and Anti Financial Crime regulation landscape of five years ago, ESG regulation implementation will require heavy lifting from the advisory and consulting sectors."

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Environmental Social & Governance (ESG) and Sustainable Investment

Client propositions and products in data-driven transformation in ESG and Sustainable Investing.

[/et_pb_team_member][/et_pb_column][et_pb_column type="1_4" _builder_version="4.4.8"][et_pb_team_member name="Rajen Madan" position="Founder and CEO" image_url="https://leadingpointfm.com/wp-content/uploads/2020/09/rajen.png" _builder_version="4.4.8" link_option_url="mailto:thush@leadingpoint.io"]

Responsible for delivering digital FS businesses.
Change leader with over 20 years’ experience in helping financial markets with their toughest business challenges.

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Upcoming blogs:

This is the third in a series of blogs that will explore the ESG world: its growth, its potential opportunities and the constraints that are holding it back. We will explore the increasing importance of ESG and how it affects business leaders, investors, asset managers, regulatory actors and more.

Artificial Intelligence: the Solution to the ESG Data Gap? In the second part of our Environmental, Social and Governance (ESG) blog series, Anya explores the potential opportunities surrounding Artificial Intelligence and responsible investing.

Is it time for VCs to take ESG seriously? In the fourth part of our  Environmental, Social and Governance (ESG) blog series, Ben explores the current research on why startups should start implementing and communicating ESG policies into their business.

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How Leading Point can help

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By using our cloud-based data visualisation platform to bring together relevant metrics, we help organisations gain a standardised view and improve your ESG reporting and portfolio performance.  Our live ESG dashboard can be used to scenario plan, map out ESG strategy and tell the ESG story to stakeholders.

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AI helps with the process of ingesting, analysing and distributing data as well as offering predictive abilities and assessing trends in the ESG space.  Leading Point is helping our AI startup partnerships adapt their technology to pursue this new opportunity, implementing these solutions into investment firms and supporting them with the use of the technology and data management.

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Implementing ESG regulations and providing operational support to improve ESG metrics for banks and other financial institutions. Ensuring compliance by benchmarking and disclosing ESG information, in-depth data collection to satisfy corporate reporting requirements, conducting appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.

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  • Connect

 

 

 

 

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GLUE42 and Leading Point Collaborate on Front Office Modernisation

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Glue42, the company that delivers integrated desktop experiences to financial institutions globally, and Leading Point Financial Markets, a financial services advisory and delivery partner, today announced a partnership to help clients provide a next-generation trading desktop experience.  

Sales and trading activities are inherently complex and require equally complex software applications to manage data and workflows. Due to single monolithic applications and bloated technology stacks, financial organizations today find it hard to adapt to changing user, customer and regulatory needs. Those organizations that can design and build so called ‘composable enterprises’, i.e. modular portfolios of business capabilities, are able to lead front office innovation and achieve higher productivity.

As part of the partnership, Leading Point Financial Markets will help organizations define the best vendor strategy and ecosystem architecture to enable the core of the composable enterprise and optimize the desktop for the best-in-class experience. Glue42 will provide the underlying integration platform to delivers seamless user journeys and configurable workflows.

“Together, we will provide a unique mix of world-class implementation services and software,” said Dishang Patel, Partner, Leading Point Financial Markets. “In the short term, traders will gain unparalleled speed of visibility across applications so they can focus on generating alpha. In the longer run, firms will need to purchase and maintain less hardware, which will vastly improve the environmental impact and making it easier to meet their ESG policy.” 

As a result of the collaboration, IT teams will be able to selectively replace or augment legacy systems, simplifying and automating complex processes, making for a leaner, system-agnostic and agile desktop. Front office teams will be able to interact with multiple systems and data sources directly from their financial desktops using only the best functionality of each application. This intelligent, user-driven desktop reduces noise and risk. With as much as 90 percent fewer clicks for basic tasks; traders can execute faster and generate 20 percent more alpha on average for their clients.

“The perfect storm of the post-Covid world and the evolving ‘interop’ innovation has created a period of reflection for many firms. For many organizations, the digital transformation was prematurely accelerated and the need for greater efficiency and process optimization is now stronger than ever,” said James Wooster, COO, Glue42. 

“As organizations innovate and adapt to changing business needs, and vendors continue to deliver more modular capabilities, they will need to rethink how they source and deliver business solutions. This partnership will help firms gain higher front-office productivity much faster,” he continued.

For more information, read Glue42’s latest paper: Modernizing Legacy Systems: Why Loving Legacy Apps is Key to Capital Markets’ Digital Transformation​. You can also watch a recording of the latest webinar: A Practitioner's View of Legacy Migration.

Read the press release here.

 

 

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Leading Point has been shortlisted in the Data Management Insight Awards 2020

We are so thrilled to have been shortlisted for the 2020 Data Management awards, vote for us in the ‘Most Innovative Data Provider’ category

From designing a solution SMART_Dash that specifies, quantifies and visualises risks arising from firms’ non-financial risk to a legal reference data-based digital repapering process for LIBOR, to target state data-driven op model implementations in anti-financial crime and treasury to ESG data readiness, Leading Point is always striving for a best-in-class solution for their clients.

Leading Point’s proprietary platform modellr allows change leaders to capture and visualise process, systems, controls, organisation and data flows in real-time. Our reimagined box-in-box view allows change and technology teams with accelerated design and delivery phases driving project initiation to completion time down by 70% and allows for continuous performance measurement of businesses’ op models.

Being recognised in this way is a huge testament to the Leading Point family and the hard work everyone has put into our data offerings this year. We have reached many milestones in our growth journey this year and are very much looking forward to the months ahead and to our next Data Kitchen event!

These prestigious awards are designed to recognise leading providers of data management solutions, services, and consultancy to capital markets.


If you believe in the power of human-centric data-driven op models in our industry please show your support for us by completing this short survey. You have until Monday 21 September to cast your vote.


Founder and CEO Rajen Madan comments on our inclusion:

“We are delighted to be shortlisted for the 2020 Data Management Awards. This is a testament to our expert practitioner-led delivery successes and our solutions focus on the business user, as a newer breed of service providers to the industry. We have grown immensely with some great partners, clients and our industry advisors. We are truly thankful to have them in our journey”

Angela Wilbraham, CEO of A-Team Group, which hosts the Data Management Insight Awards, added that being shortlisted was “in itself a fantastic achievement amongst such strong competition.”

Voting closes Midnight (GMT) Monday 21st September 2020.

The winners will be announced on Thursday 3rd December 2020.


Who we are:

Leading Point helps financial services businesses thrive in new realities by combining financial experience with data and innovation. We provide data-led solutions and seamless integrations in Regulatory Compliance, Risk Assurance, KYC/AML, Corporate Treasury, Information Security and Trading. We specialise in helping our clients implement digital user journeys and data-driven operating models. We work with some of the world’s largest global financial institutions, challenger fintech and tech innovators with a combination of AI/ML/ RPA and DLT.


Artificial Intelligence: The Solution to the ESG Data Gap?

The Power of ESG Data

It was Warren Buffett who said, “It takes twenty years to build a reputation and five minutes to ruin it” and that is the reality that all companies face on a daily basis. An effective set of ESG (Environment, Social & Governance) policies has never been more crucial. However, it is being hindered by difficulties surrounding the effective collection and communication of ESG data points, as well a lack of standardisation when it comes to reporting such data. As a result, the ESG space is being revolutionised by Artificial Intelligence, which can find, analyse and summarise this information.
 

There is increasing public and regulatory pressure on firms to ensure their policies are sustainable and on investors to take such policies into account when making investment decisions. The issue for investors is how to know which firms are good ESG performers and which are not. The majority of information dominating research and ESG indices comes from company-reported data. However, with little regulation surrounding this, responsible investors are plagued by unhelpful data gaps and “Greenwashing”. This is when a firm uses favourable data points and convoluted wording to appear more sustainable than they are in reality. They may even leave out data points that reflect badly on them. For example, firms such as Shell are accused of using the word ‘sustainable’ in their mission statement whilst providing little evidence to support their claims (1)

Could AI be the complete solution?

AI could be the key to help investors analyse the mountain of ESG data that is yet to be explored, both structured and unstructured. Historically, AI has been proven to successfully extract relevant information from data sources including news articles but it also offers new and exciting opportunities. Consider the transcripts of board meetings from a Korean firm: AI could be used to translate and examine such data using techniques such as Sentiment Analysis. Does the CEO seem passionate about ESG issues within the company? Are they worried about an investigation into Human Rights being undertaken against them? This is a task that would be labour-intensive, to say the least, for analysts to complete manually.  

 

In addition, AI offers an opportunity for investors to not only act responsibly, but also align their ESG goals to a profitable agenda. For example, algorithms are being developed that can connect specific ESG indicators to financial performance and can therefore be used by firms to identify the risk and reward of certain investments. 

 

Whilst AI offers numerous opportunities with regards to ESG investing, it is not without fault. Firstly, AI takes enormous amounts of computing power and, hence, energy. For example, in 2018, OpenAI found the level of computational power used to train the largest AI models has been doubling every 3.4 months since 2012 (2). With the majority of the world’s energy coming from non-renewable sources, it is not difficult to spot the contradiction in motives here. We must also consider whether AI is being used to its full potential; when simply used to scan company published data, AI could actually reinforce issues such as “Greenwashing”. Further, the issue of fake news and unreliable sources of information still plagues such methods and a lot of work has to go into ensuring these sources do not feature in algorithms used. 

 

When speaking with Dr Thomas Kuh, Head of Index at leading ESG data and AI firm Truvalue Labs™, he outlined the difficulties surrounding AI but noted that since it enables human beings to make more intelligent decisions, it is surely worth having in the investment process. In fact, he described the application of AI to ESG research as ‘inevitable’ as long as it is used effectively to overcome the shortcomings of current research methods. For instance, he emphasised that AI offers real time information that traditional sources simply cannot compete with. 

 A Future for AI?

According to a 2018 survey from Greenwich Associates (3), only 17% of investment professionals currently use AI as part of their process; however, 40% of respondents stated they would increase budgets for AI in the future. As an area where investors are seemingly unsatisfied with traditional data sources, ESG is likely to see more than its fair share of this increase. Firms such as BNP Paribas (4) and Ecofi Investissements (5) are already exploring AI opportunities and many firms are following suit. We at Leading Point see AI inevitably becoming integral to an effective responsible investment process and intend to be at the heart of this revolution. 

 

AI is by no means the judge, jury and executioner when it comes to ESG investing and depends on those behind it, constantly working to improve the algorithms, as well as the analysts using it to make more informed decisions. AI does, however, have the potential to revolutionise what a responsible investment means and help reallocate resources towards firms that will create a better future.

[1] The problem with corporate greenwashing

[2] AI and Compute

[3] Could AI Displace Investment Bank Research?

[4] How AI could shape the future of investment banking

[5] How AI Can Help Find ESG Opportunities

 

"It takes twenty years to build a reputation and five minutes to ruin it"

 

AI offers an opportunity for investors to not only act responsibly, but also align their ESG goals to a profitable agenda

Environmental Social Governance (ESG) & Sustainable Investment

Client propositions and products in data driven transformation in ESG and Sustainable Investing. Previous roles include J.P. Morgan, Morgan Stanley, and EY.

 

Upcoming blogs:

This is the second in a series of blogs that will explore the ESG world: its growth, its potential opportunities and the constraints that are holding it back. We will explore the increasing importance of ESG and how it affects business leaders, investors, asset managers, regulatory actors and more.

 

 

Riding the ESG Regulatory Wave: In the third part of our Environmental, Social and Governance (ESG) blog series, Alejandra explores the implementation challenges of ESG regulations hitting EU Asset Managers and Financial Institutions.

Is it time for VCs to take ESG seriously? In the fourth part of our Environmental, Social and Governance (ESG) blog series, Ben explores the current research on why startups should start implementing and communicating ESG policies at the core of their business.

Now more than ever, businesses are understanding the importance of having well-governed and socially-responsible practices in place. A clear understanding of your ESG metrics is pivotal in order to communicate your ESG strengths to investors, clients and potential employees.

By using our cloud-based data visualisation platform to bring together relevant metrics, we help organisations gain a standardised view and improve your ESG reporting and portfolio performance.  Our live ESG dashboard can be used to scenario plan, map out ESG strategy and tell the ESG story to stakeholders.

AI helps with the process of ingesting, analysing and distributing data as well as offering predictive abilities and assessing trends in the ESG space.  Leading Point is helping our AI startup partnerships adapt their technology to pursue this new opportunity, implementing these solutions into investment firms and supporting them with the use of the technology and data management.

We offer a specialised and personalised service based on firms’ ESG priorities.  We harness the power of technology and AI to bridge the ESG data gap, avoiding ‘greenwashing’ data trends and providing a complete solution for organisations.

Leading Point's AI-implemented solutions decrease the time and effort needed to monitor current/past scandals of potential investments. Clients can see the benefits of increased output, improved KPIs and production of enhanced data outputs.

Implementing ESG regulations and providing operational support to improve ESG metrics for banks and other financial institutions. Ensuring compliance by benchmarking and disclosing ESG information, in-depth data collection to satisfy corporate reporting requirements, conducting appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.

 


Trading Platform Interoperability

"Glue42 is proud to partner with Leading Point bringing a joint value proposition to accelerate first-class implementation, delivery, and support service for trading systems in the investment community. Their domain knowledge and subject matter expertise coupled with highly recognised and experienced industry practitioners have already revealed new ways to deliver benefits to the Financial Services market"

COO @ Glue42


ESG: The Future Pillars of Investing

The ESG Explosion

With the ESG (Environmental, Social and Governance) market being estimated to reach $50 trillion over the next two decades [i], it is safe to say ESG is here to stay. This explosion is being driven by an increasingly conscientious world, with voices such as Greta Thunberg ensuring we no longer stay passive in our impact. Investors are increasingly realising the gains to be had from aligning themselves with firms that perform well in ESG criteria, such as risk management and possible financial gains. 

This movement from investors as well as the general public has motivated firms to look in the mirror with regards to ESG performance and how they can improve. With new regulation on the horizon, forward thinking companies are wanting to report their ESG data more frequently and comprehensively. 

ESG is Good for Business

ESG investing is becoming increasingly driven by millennials, who are taking an active role in aligning their personal values and their investing strategies. This investment pattern facilitates the belief that change - now more than ever - is a goal we can reach. If consumer behaviour is more directed towards ‘creating an impact’, what is the logical next step for businesses to thrive? 

Organisations need to become more conscious of their mission and how they communicate it to the public, especially since good ESG metrics and reporting could seriously affect their staff and customer base[ii]

. Today’s start-up culture and the focus on the entrepreneurial mindset further demands this issue to be taken seriously. As well as helping to land conscientious clients and retain millennial job talent, a strong ESG proposition directly correlates to value creation within a business. More than a fad or a feel good exercise,[iii] a stronger esg proposition correlates with higher equity returns. 

Why ESG is Important for Investors

During Q2 2019, ETFs with a sustainability criteria attracted EUR5 billion in net flows; this is more than throughout the whole of 2018[iv]. As demand skyrockets for responsible funds, there is increasing client pressure on investors and asset managers to take ESG factors into consideration. However, there are many other reasons why ESG data provides a competitive edge to investors. 

Firstly, a good ESG performance is a strong indicator that a business is well-managed and, hence, considering ESG data acts as an effective way to manage risk. For example, a recent report from McKinsey states good ESG performance is associated with lower loan and credit default swap spreads and higher credit ratings.[v]

As well as a desire to profit from ESG data, there is ever-tightening regulation meaning investors need to care about it. For example, the EU taxonomy regulation is redefining what it means for an investment to be ‘environmentally sustainable’. Investors are keen to stay ahead of such regulation by having effective methods to monitor the key ESG data points of their portfolio companies. 

Constraints on ESG

Whilst the ESG market is growing incredibly fast, there are a number of constraints on this growth. Financial data has clear, widely-agreed metrics whose implications are straightforward; however, the same cannot be said for ESG data. This can result in an “ESG Data Gap” between businesses and their investors as ESG information is failed to be communicated effectively between the two parties. 

This “Data Gap” is especially obvious in the startup world where sustainable VCs are failing to communicate the ESG landscape of their portfolio companies effectively to their LPs. Finally, there is also ever-tightening regulation surrounding ESG disclosure for Asset Managers and FIs generally. It is difficult to integrate these effectively into procedures leading to inefficiencies. 

Our series of blogs will delve deeper into the ESG world and these problems which plague it. 

 

[i] Complete guide to sustainable investing

[ii] Five ways that ESG creates value

[iii] ESG framework

[iv] https://www.wealthadviser.co/2020/01/06/281642/how-artificial-intelligence-transforming-esg-data-and-indices

[iv] https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/five-ways-that-esg-creates-value

 

As demand skyrockets for responsible funds, there is increasing client pressure on investors and asset managers to take ESG factors into consideration.

 

a good ESG performance is a strong indicator that a business is well-managed and, hence, considering ESG data acts as an effective way to manage risk.

 

Data Innovation, Investment behaviour research

Helping businesses understand and improve their data strategy via the Leading Point Data Innovation Index.

Environmental Social Governance (ESG) & Sustainable Investment

Client propositions and products in data driven transformation in ESG and Sustainable Investing. Previous roles include J.P. Morgan, Morgan Stanley, and EY.

 

Upcoming blogs:

This is the first in a series of blogs that will explore the ESG world: its growth, its potential opportunities and the constraints that are holding it back. We will explore the increasing importance of ESG and how it affects business leaders, investors, asset managers, regulatory actors and more.

Artificial Intelligence: the Solution to the ESG Data Gap? In the second part of our Environmental, Social and Governance (ESG) blog series, Anya explores the potential opportunities surrounding Artificial Intelligence and responsible investing.

Riding the ESG Regulatory Wave: In the third part of our Environmental, Social and Governance (ESG) blog series, Alejandra explores the implementation challenges of ESG regulations hitting EU Asset Managers and Financial Institutions.

Is it time for VCs to take ESG seriously? In the fourth part of our  Environmental, Social and Governance (ESG) blog series, Ben explores the current research on why startups should start implementing and communicating ESG policies into their business.

 

Now more than ever, businesses are understanding the importance of having well-governed and socially-responsible practices in place. A clear understanding of your ESG metrics is pivotal in order to communicate your ESG strengths to investors, clients and potential employees.

By using our cloud-based data visualisation platform to bring together relevant metrics, we help organisations gain a standardised view and improve your ESG reporting and portfolio performance.  Our live ESG dashboard can be used to scenario plan, map out ESG strategy and tell the ESG story to stakeholders.

AI helps with the process of ingesting, analysing and distributing data as well as offering predictive abilities and assessing trends in the ESG space.  Leading Point is helping our AI startup partnerships adapt their technology to pursue this new opportunity, implementing these solutions into investment firms and supporting them with the use of the technology and data management.

We offer a specialised and personalised service based on firms’ ESG priorities.  We harness the power of technology and AI to bridge the ESG data gap, avoiding ‘greenwashing’ data trends and providing a complete solution for organisations.

Leading Point's AI-implemented solutions decrease the time and effort needed to monitor current/past scandals of potential investments. Clients can see the benefits of increased output, improved KPIs and production of enhanced data outputs.

Implementing ESG regulations and providing operational support to improve ESG metrics for banks and other financial institutions. Ensuring compliance by benchmarking and disclosing ESG information, in-depth data collection to satisfy corporate reporting requirements, conducting appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.


Regulatory Risk: Getting away from Whack-a-Mole

Senior Management is under more pressure than ever to demonstrate compliance and risk-sensitive decision making - but the process by which they do it is straining under the sheer number and weight of obligations to manage.

36% of fines handed out by the FCA over the last 3 years - over a third - have been for failings related to management and control (PRIN 3)*. With an average penalty of £24 million firms cannot afford to be lax in this.  Transparency of their firm’s systems and controls continues to be vital for leaders at Board level and within Senior Management Functions to ensure that their business is compliant and within risk tolerances. 

Increasingly, during the ongoing pandemic, regulators expect comprehensive, responsible, and tangible governance and control to be operated by regulated firms. Creating transparency of firms’ regulatory activity across the business paramount. Not just for leaders at Board and Senior Management Functions levels (SMFs) but also in the supporting infrastructure within Compliance, Operations, Technology, Finance, Legal, and HR.

In their recent Joint Statement for Firms, the UK regulators outlined that firms must:

“Develop and implement mitigating actions and processes to ensure that they continue to operate an effective control environment: in particular, addressing any key reporting and other controls on which they have placed reliance historically, but which may not prove effective in the current environment. .. Consider how they will secure reliable and relevant information, on a continuing basis, in order to manage their future operations.”**

Joint statement by the Financial Conduct Authority (FCA), Financial Reporting Council (FRC) and Prudential Regulation Authority (PRA), 26th March 2020

‘Securing reliable and relevant information’ is harder than it sounds. The information required for this is frequently cobbled together in PowerPoint, Excel or other tools from a wide variety of disparate sources. This is inefficient and time intensive, and is subject to inconsistencies. Information may be out of date by the time it is produced, and often does not meet the level of detail required by the various audiences. 

More than that, Senior Managers lack a consolidated view of their regulatory risk across their business. This is difficult to achieve given the number of areas they need to monitor, ongoing regulatory change, and the pace of digital transformation. Managers are often spending more time piecing together a picture of their overall regulatory ‘health’ and fighting fires than they are developing the business.

Compliance issues become like Whack-A-Mole, as soon as one gets whacked, another one pops up, and then another. Senior Management are effectively blindfolded holding the ‘mole hammer’ and have to ask a business analyst or a compliance officer “are there any moles today?” and “what do I hit?”. 

These regulatory moles are not common or garden business problem moles. There may be hundreds of moles to whack at any given time. As a result, managers need the ability to triage the reports of mole sightings to decide which is most pressing. Which is most likely to ruin his or her lawn? Is it the Sanctions Breach mole, the Data Protection mole or Transaction Reporting mole? 

Not only are there many of them - you need to keep records of which ones you’ve whacked and why. At some point you’ll need to evidence why you didn’t whack the Sanctions Breach mole immediately and provide the context for that decision. If you fail to whack enough of them, or the right ones, your business could be fined, or worse, you personally could end up in court.

This is a much more pressing issue due to the level of personal accountability, and broadened personal liability,  introduced by the Senior Managers and Certification Regime (SM&CR). The SM&CR, which came into force on 9th December 2019, overhauled the Approved Persons Regime for individuals working in UK financial services firms. Placing more stringent requirements on senior managers to take responsibility for their firms’ activities through a ‘Duty of Responsibility’ to take ‘reasonable steps’ to prevent or stop regulatory breaches. 

As the FCA Handbook states in their “Specific guidance on individual conduct rules” (COCON 4.2) addressed to Senior Managers: “SC2: You must take reasonable steps to ensure that the business of the firm for which you are responsible complies with the relevant requirements and standards of the regulatory system.”***

We believe that one of these ‘Reasonable Steps’ is having appropriate reporting to achieve a clear view of the ‘Regulatory Health’ of their business and their risk points. Firms and Senior Managers need the ability to:

  1. Capture key regulatory risk metrics
  2. Link them to the appropriate compliance monitoring data
  3. Put those risk metrics into context across the business
  4. Generate a consolidated view of the business’ regulatory health and risk points
  5. Make it accessible & easily understandable to the relevant managers
  6. Make it ‘persistent’ over time to and allow ‘point in time’ views of risk levels

A solution that could a) take existing and live compliance data b) isolate the risk metrics that really ‘matter’, and c) present them in context across regulations and business areas is really needed for Senior Managers to have a picture of their overall risk. 

Senior Management should know where the regulatory moles are - without having to ask. Rather than having to review reams of documentation, it could allow managers a more holistic and focused view of regulatory risk across their business, as well as save time and resource spent creating, managing, and reviewing PowerPoints. Knowing what to look for is half the battle after all.  

Don’t let the moles ruin your lawn.

 

References

1. Leading Point analysis of FCA fines related to PRIN 3 Management and control: A firm must take reasonable care to organise and control its affairs responsibly and effectively, with adequate risk management systems.” FCA Principles for Business https://www.handbook.fca.org.uk/handbook/PRIN/2/?view=chapter

 

2. https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/2020/joint-statement-on-covid-19.pdf?la=en&hash=28F9AC9E45681F3DC65B90B36B5C92075048955F

 

3. “Specific guidance on individual conduct rules” (COCON 4.2) addressed to Senior Managers: https://www.handbook.fca.org.uk/handbook/COCON/4/2.html

On July 14th, experts from banks, hedge funds and market infrastructure providers will discuss how financial institutions can create transparency and insights from their regulatory risk data, and Leading Point will introduce their new industry-leading regulatory risk data system SMART_Dash.

Panellists will discuss:

- The challenges of internal regulatory oversight that all financial services firms are facing

- How businesses can create a consolidated view of their regulatory risk

- The ways that regulatory monitoring data can be more accessible

- An introduction to SMART_Dash; a revolutionary tool providing regulatory risk reassurance

*Regulatory Risk, not moles

Join our webinar to learn more about how to create transparency and insights from regulatory risk data

 

 

 

Senior Management are effectively blindfolded holding the ‘mole hammer’ and have to ask a business analyst or a compliance officer “are there any moles today?” and “what do I hit?”.

 

36% of fines handed out by the FCA over the last 3 years - over a third - have been for failings related to management and control (PRIN 3).

 

"[Firms must] Consider how they will secure reliable and relevant information, on a continuing basis, in order to manage their future operations."

 

"firms need to ensure that their cloud-based operating models are not only safe and secure, but address the capabilities required for operational resilience testing. Investment in frameworks and data analytics that can support these capabilities are essential"

 

Thushan Kumaraswamy
Head of Solutions

Architecture lead with over 20 years’ experience helping the world’s biggest financial services providers in capital markets, banking and buy-side to deliver practical business transformations in client data, treasury, sales, operations, finance and risk functions, and major firm-wide efficiency initiatives. Mastery in business and technical architecture, with significant experience in end-to-end design, development and maintenance of mission critical systems in his early career. Specialities – business and technical architecture leadership, data warehousing, capital markets, wealth management, private banking.

 

 

Rajen Madan
Founder & CEO

Change leader with over 20 years’ experience in helping financial markets with their toughest business challenges in data, operating model transformation in sales, CRM, Ops, Data, Finance & MI functions, and delivery of complex compliance, front-to-back technology implementations. Significant line experience. Former partner in management consulting leading client solution development, delivery and P&L incl. Accenture. Specialities – Operating Models, Data Assets, Compliance, Technology Partnerships & Solutions in Capital Markets, Market Infrastructure, Buy-Side, Banking & Insurance.

 

 


WEBINAR | Regulatory Risk: Making it SMART

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Getting a consolidated view of regulatory risk data is a headache for many financial institutions. Creating senior manager and governance forum packs that bring together the latest regulatory data in an understandable way can take up days of valuable time and can overwhelm managers with their level-of-detail.

Experts from banks, hedge funds and market infrastructure providers will discuss how financial institutions can create transparency and insights from their regulatory risk data, and Leading Point will introduce their new industry-leading regulatory risk data system SMART_Dash.

Panellists will discuss:

  • The challenges of internal regulatory oversight that all financial services firms are facing
  • How businesses can create a consolidated view of their regulatory risk
  • The ways that regulatory monitoring data can be more accessible
  • An introduction to SMART_Dash; a revolutionary tool providing regulatory risk reassurance

About the panellists:

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Michelle is an experienced Compliance Professional with twenty years experience in Asset Management, specialising in alternative funds. She is a Partner (SMF27), Chief Compliance Officer (SMF16) and Money Laundering Reporting Officer (SMF17).


[/et_pb_team_member][/et_pb_column][et_pb_column type="1_4" _builder_version="4.3.4"][et_pb_team_member name="Sarah Peaston " position="Director at Regulatory Governance Consulting Limited" image_url="https://leadingpointfm.com/wp-content/uploads/2020/06/Untitled-e1593013287613.png" _builder_version="4.3.4" body_font_size="14px" custom_margin="0px|-10px|0px|-10px|false|false" custom_padding="0px|0px|0px|0px|false|false" border_color_all_image="rgba(0,0,0,0)"]

Sarah is an industry and regulatory expert who has enjoyed a Financial Services career spanning over two decades in US, UK and European investment banking and Financial Services organisations.


[/et_pb_team_member][/et_pb_column][et_pb_column type="1_4" _builder_version="4.3.4"][et_pb_team_member name="Rajen Madan" position="CEO at Leading Point" image_url="https://leadingpointfm.com/wp-content/uploads/2020/06/Rajen-photo.jpg" _builder_version="4.3.4" body_font_size="14px" custom_margin="0px|-10px|0px|-10px|false|false" custom_padding="0px|0px|0px|0px|false|false" border_color_all_image="rgba(0,0,0,0)"]

Change leader with over 20 years’ experience in helping financial markets with their toughest business challenges in data, op models, regulatory compliance, and digital platforms.
[/et_pb_team_member][/et_pb_column][et_pb_column type="1_4" _builder_version="4.3.4"][et_pb_team_member name="Thushan Kumaraswamy " position="Head of Solutions at Leading Point" image_url="https://leadingpointfm.com/wp-content/uploads/2020/06/Thush-photo.jpg" _builder_version="4.3.4" body_font_size="14px" custom_margin="0px|-10px|0px|-10px|false|false" custom_padding="0px|0px|0px|0px|false|false" border_color_all_image="rgba(0,0,0,0)"]

Thush is an expert architecture lead with over 20 years’ experience helping the world’s biggest financial services providers in capital markets, banking and buy-side to deliver practical transformations in client data, anti-financial crime, treasury, risk, ops and finance functions, and major firm-wide efficiency initiatives.
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What if business operations could be more like Lego?

Financial services (FS) professionals from 30+ organisations tuned in to our inaugural webinar last week “What if business operations could be more like Lego?” to hear the challenges that COO and Heads of Change face in changing their business operating models and how we might break through the barriers. A summary of key takeaways from the discussion are presented below. See the webinar recording here

 

The importance of ‘Know Your Operating Model’

FS firms are under renewed pressure to rethink their operating models; competitive pressure, raised consumer expectations, and continuous regulatory requirements mean constant operating model re-think and change. Yet most firms are stuck with theoretical target operating models that lack a plan, a way to measure performance and progress, or a business case. As a result, only 25% of investors are confident strategic digital transformation will be effective.**

Innovation is hindered as firms struggle to overcome significant technical debt to implement new technology (e.g. automation, AI, cloud etc.) while effectively using budget tied up in high operating costs. Indeed, 80% of technology spend in organisations is focused on legacy systems and processes, while only 20% of analytics insights deliver business outcomes and 80% of AI projects “remain alchemy, run by wizards”***

Insufficient business understanding means lost opportunities, wasteful spends & risk – if you don’t understand your business well enough, you will be exposing yourself to risks and lost opportunities.

 

The barriers to business understanding

Firms current approaches to business operations and change are not fit for purpose.

Insight Gap in the Boardroom: Experts with specialist toolkits are needed to structure and interpret most business information. Management’s understanding of the business is often directly related to the ability of their analytical teams to explain it to them. Most firms are still stuck with an overload of information without insights, without the right questions being asked.

Cultural Challenge: Many execs still think in terms of headcount and empire building rather than outcomes, capabilities, and clients.

Misaligned metrics: Metrics are too focused on P&L, costs and bonuses! Less on holistic organisation metrics, proof points and stories.

Complexity makes it difficult to act… Most enterprises suffer from excessively complicated operating models where the complexity of systems, policies, processes, controls, data and their accompanying activities make it difficult to act.

…and difficult to explain: Substantiating decisions to stakeholders, regulators or investors is an ongoing struggle, for both new and historic decisions.

If you can't measure it, you can't manage it: Inconsistent change initiatives without performance metrics compound errors of the past and mean opportunities for efficiency gains go unseen.
How can we break through these barriers?

Business insight comes from context, data and measurement: How the building blocks of the business fit together and interact is essential to the ‘what’ and ‘how’ of change, and measurement is key to drive transparency and improved behaviours.

Operating model dashboards are essential: Effective executives either have extremely strong dashboards underpinning their decisions or have long standing experience at the firm across multiple functions and get to “know” their operating mode innately. This is a key gap in most firms. 50% of attendees chose improved metrics & accessibility of operating model perspectives as priority areas to invest in.

Less is more: Senior managers should not be looking at more than 200 data points to run and change their business. Focusing on the core and essential metrics is necessary to cut through the noise.

The operating model data exists, it should now be harvested: The data you need probably already exists in PowerPoint presentations, Excel spreadsheets and workflow tools. Firms have struggled to harvest this data historically and automate the gathering process. We demonstrated how operating model data can be collected and used to create insights for improved decision-making using the modellr platform.

Culture change is central: Culture was voted by attendees as the #1 area to invest in, in order to improve business decision-making. Organisational culture is a key barrier to operating model change. A culture that incentivises crossing business silos and transparency will create benefits across the enterprise.

Client-driven: Clients are driving firms to more real-time processing along with the capability to understand much more information. Approaches that combine human intelligence with machine intelligence are already feasible and moving into the mainstream.

Get comfortable with making decisions with near perfect information: Increasingly executives and firms need to get comfortable with “near perfect” information to make decisions, act and deliver rapid business benefits.

 

Future Topics of Interest

Regulatory Reassurance: Regulators continue to expect comprehensive, responsible and tangible governance and control from Senior Managers. How can firms keep up with their regulatory obligations in a clear and simple way?

Environmental, Social & Governance (ESG): An increasingly-popular subject, ESG considers  the impact of businesses on the environment and society. ESG metrics are becoming more important for investors & regulators and firms are looking for consistent ways to measure performance and progress in ESG metrics.

Operating Model-as-a-Service: As well as managing business operations themselves, firms need to monitor the models that describe those operations; their current state, their target state and the roadmap between the two. Currently, this is often done with expensive PowerPoint presentations that are usually left in cupboards and ignored because they are not “live” documents. Metrics around the operating model can be captured and tracked in a dashboard.

Anti-Financial Crime (AFC): Money laundering, terrorist financing, fraud, sanctions, bribery & corruption; the list of ways to commit financial crime through FS firms grows by the day. How can firms track their AFC risk levels and control effectiveness to see where they need to strengthen?

Information Security: With the huge volume of data that firms now collect, process & store, there are more and more risks to keep that data secure and private. Regulations like GDPR can impose very large fines on firms that break those regulations. Industry standards, such ISO 27001, help improve standards around information security.

*,**  Oliver Wyman, 2020, The State Of The Financial Services Industry

*** Gartner, 2019, Our Top Data and Analytics Predicts for 2019

 


WEBINAR: What if business operations could be more like lego?

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What if business transformation could be more like Lego?

Brightly coloured, tactile, and with standardised connectors, Lego bricks can be easily assembled, moved, or replaced. Making changes is easy because the structure is easy to understand, and the components and their purpose visible.

Unfortunately, business operations are nothing like Lego. The complexity in relationships between business services and the dimensions of the stack of associated systems, policies, processes, controls, data and their accompanying activities makes understanding operating models the realm of specialists and specialist tool sets.

As a result, many leaders struggle to track their operating models or digitally transform their business due to a lack of clear information and knowledge, leading to inhibited decision-making, poor communication, wasted change budgets, and unforeseen consequences.

But what if you could lower the barrier for true business understanding?

Join us on 2nd June to understand:

  • How firms can visualise and organise their business data to find the relationships within their business that matter
  • How to easily track business performance and model ‘what if’ scenarios
  • How visualisation of critical domains and data metrics can accelerate project roadmaps and execution
  • How you can better communicate your business environment to your stakeholders

Leading Point is proud to launch modellr; a data-driven storytelling tool for change leaders. modellr's interactive interface provides an intuitive visualisation of business operations, processes and managed risk.

https://leadingpointfm.com/services/modellr/

 

 
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Operational Resilience: data infrastructure and a consolidated risk view is pivotal to the new rules on operational risk

What have we learnt about Operational Resilience in the last three months?  

The last three months has taken the world – and Financial Services completely by surprise and further highlighted some major weaknesses in firms’ approaches to operational risk.

In January 2020, infectious diseases or Pandemic Risk, was not in the top 20 operational risks in Financial Services – at the time dominated by Cybercrime, data breaches and financial crime.[1] While many firms’ will have run pandemic scenarios at some point as part of their operational risk scenario analysis programme (probably based on SARs, or Ebola) – it’s becoming increasingly clear that many firms’ business continuity plans were being updated ‘on the fly’ as they moved to crisis management as the pandemic situation evolved. 70% of Operational Risk professionals say that their priorities and focus have changed as a result of Covid 19.[2]

This is understandable. No-one anticipated a situation of near total remote working that the pandemic has called for – even in extreme scenarios.

Many banks and insurance companies now have up to 90% of their staff working from home and are attempting to manage the plethora of associated impacts and increased risks resulting from this new environment.

Risks such as internal fraud or engaging in unauthorised activities are increasing as a direct consequence of the reduced monitoring capabilities caused by distance working as well as simple operational errors, mistakes, and omissions. While many other indirect risks are increasing, such as cyber criminals taking advantage of new vulnerabilities revealed by remote working.

 

Regulators are re-writing the rulebook on how to manage operational risk

The ability of Financial Services to cope in situations such as this has been an area of regulatory focus for some years now, in great part driven by the parliamentary response to high profile IT failures such as with TSB or RBS[3]. Named ‘Operational Resilience’, regulators are looking at the “ability of firms and the financial sector as a whole to prevent, adapt, respond to, recover, and learn from operational disruptions.”

The Bank of England & FCA released a discussion paper in 2018 on this topic, stating:

“The financial sector needs an approach to operational risk management that includes preventative measures and the capabilities – in terms of people, processes and organisational culture – to adapt and recover when things go wrong.”[4]

Covid 19 is a prime example of things ‘going wrong’.

As a result, regulators are closely monitoring this situation as Covid 19 replaces Brexit as the test case for UK financial services’ ‘Operational Resilience’ rules. How firms manage Covid 19 now, will shape the final form of the imminent legislation as firms’ successes and failures are factored into the final rules due in 2021.

A joint PRA/FCA consultation paper ‘CP29/19 Operational resilience: Impact tolerances for important business services’ released in December 2019[5] breaks down their proposed policy and regulatory requirements to reform operational risk management. Namely:

  1. Identification of Important Business services – A firm or Financial Market Infrastructure (FMI) must identify and document the necessary people, processes, technology, facilities, and information (referred to as resources) required to deliver each of its important business services.
  2. Set impact tolerances for those business services – firms should articulate specific maximum levels of disruption, including time limits within which they will be able to resume the delivery of important business services following severe but plausible disruptions
  3. Remain within those impact tolerances – Scenario testing: is the testing of a firm or FMI’s ability to remain within its impact tolerance for each of its important business services in the event of a severe (or in the case of FMIs, extreme) but plausible disruption of its operations.

The shift in focus means moving away from tracking individual risks to individual systems and resources towards considering the chain of activities which make up a business service and its delivery. This includes outsourcing and third party risk management, as made clear in a separate consultation paper. [6] As a result, operational risk management will become significantly more data intensive.

To understand business services’ impact tolerances in ongoing testing requires a significant level of infrastructure and data sophistication. Identifying and assessing the criticality of the ‘chain’ of activities involved is a project in itself, but defining, collecting, and reporting on the right metrics on an ongoing basis would require purpose built infrastructure.

As they stand, the rules under consultation require firms to produce a detailed end-to-end mapping of processes, applications, and people, new and updated policies, standards and procedures. Testing of operational resilience programs will require significant effort from firms depending on the scale and complexity of operations, testing frequency, or level of integration required.

Alongside these operational changes, the regulators expect Boards and senior management to consider operational resilience when making strategic decisions. As a result, robust information tools are needed that incorporate metrics such as KRIs, KCIs or KPIs into informed strategic decision making.[7]

 

How firms currently manage their operational risks is undergoing a paradigm shift

Firms’ existing operational risk management is primarily informed by the Basel II’s capital requirements legislation[8]. Firms are required to hold Operational Risk Capital (ORC) against aggregate operational risks calculated largely against quantifiable, historical ‘loss events’ (i.e. how much money was lost, and for what reason) and the RCSA[9] scores based on the adequacy of the controls designed to prevent those losses.

Basel II’s more sophisticated, model-based, advanced measurement approach (AMA) has been widely criticised as being difficult to implement and ineffective – leading many firms to default to the simpler Basic Indicator Approach (BIA) rather than invest in the infrastructure to support the AMA and eat the increased capital charges the BIA entails.

As a result, most operational risk scenarios have been largely event-driven e.g. what happens if the trade reconciliation system goes down. Firms largely don’t attempt to track what would happen if that system deteriorated by 20% for example.

This is the key difference in approach between the proposed operational resilience rules and existing frameworks. Where traditional operational risk management is much more siloed and vertical, operational resilience requires a much more holistic, and horizontal, approach internally.

Taking an end-to-end view of the ‘chain’ of activities that make up a service and its associated controls, means tracking the entirety of the inputs and outputs from front to back across business lines, middle and back offices, and 3rd party suppliers and outsourcing (e.g. from sales to execution to settlement).

As a result, analysing the impact of a deterioration in control effectiveness requires data infrastructure and risk management software designed for the purpose that can incorporate the relevant metrics (e.g. volume, uptime, etc.) and track the impact of changes across downstream processes.

Given many firms have challenges managing end-to-end business flows on a BAU basis without significant manual manipulation of data as they are so complex and fractured, there will likely be significant challenges around defining and delivering resilience thresholds which meet the regulatory requirements as the data sets underpinning such thresholds will also be complex and fractured.

Basel II’s system is now being overhauled with the new Standardized Measurement Approach (SMA) under Basel III regulations, now[10] due 2023. As a result, banks will need to ensure their internal loss data is as accurate and robust as possible to substantiate their calculated ORC.

How this system meshes with the operational resilience rules is an open question for the industry. Can they be aligned? or will firms be doomed to operate multiple and potentially conflicting risk frameworks?

 

Movement to the cloud needs purposeful development of operational resilience capabilities

The regulators are clear about how they see the future of Financial Institutions – they should be deeply interconnected with the regulators and be able to provide the data they need ‘on tap’. The move towards more granular, end-to-end views of operational resilience needs to be seen as a continuation of this objective.

According to ORX, the international operational risk management association:

“Risks are becoming more interconnected and traditional operational risk management is not suited to manage them … we have tools, we have tactics, we have value, but that we lack a strategy. We need a strategy to deal with the changing risk horizon, new business models, changing technology and, most of all, new expectations from senior management.”[11]

These are issues the UK regulators understand deeply, however, the Operational Resilience proposals need to be seen in the broader regulatory context. In the UK, the industry spends £4.5 billion in regulatory reporting, but the BoE wants to move towards a more integrated system.

“supervisors now receive more than 1 billion rows of data each month… the amount of data available in regulatory and management reports now exceeds our ability to analyse it using traditional methods.”[12]

As a result, the BoE has tabled proposals to pull data directly from firms’ systems or use APIs to ‘skip the middleman’ and go directly to source[13].

The drive towards innovation and digital transformation means the industry is aggressively moving towards wholescale cloud adoption. As firms such as a Blackrock, Lloyds, sign strategic partnership deals with Google, Microsoft or other cloud providers, in 2020, cloud technology is seen as a real, scalable and safe option for Financial Services.

While cloud security is a well-known concern, firms need to ensure that their cloud-based operating models are not only safe and secure, but address the capabilities required for operational resilience testing. Investment in frameworks and data analytics that can support these capabilities are essential – but should not be limited to purely operational resilience objectives.

Cloud adoption is a huge opportunity for firms to build ‘green field’ infrastructure that can not only support digitisation and business transformation objectives but also support ever increasing data requirements – regulatory or otherwise. The ability to handle and trace iterative regulatory requirements for new data sets need to be built into the fabric of firms’ operating models not just for compliance purposes but to track the impact of that compliance.

Conclusion

How many firms have today a consolidated view of their anti-financial crime, information security, or other non-financial or compliance risks, the resources devoted to their management, or the management information on tap to support decision making? It is clear firms need the right infrastructure and tools to support the granularity, and traceability of these data sets.

Real investment in operational risk data capabilities can yield significant business benefits – not just in the reduction of material risk and future spend on compliance, but as an invaluable source of internal intelligence for resource and business optimisation.

Top-of-the-line risk data positions Financial Institutions to further build out capabilities such as big data analytics, correlation and root cause analysis, and predictive risk intelligence.

However, in the face of the current pandemic, competing challenger institutions, market disruption, and the uncertainties of the future – the ability for firms to provide evidence they are robust and resilient organisations will give them a real competitive advantage as clients seek resiliency as core requirement in their banking/FMI partners.

Ultimately, the most important benefit a robust operational resilience framework can give firms is trust – from both customers and regulators.

 

[1] Risk.Net, March 2020, ‘Top 10 operational risks for 2020’ https://www.risk.net/risk-management/7450731/top-10-operational-risks-for-2020

[2] Elena Pykhova, 2020, ‘Operational Risk Management during Covid-19: Have priorities changed?’ https://www.linkedin.com/pulse/operational-risk-management-during-covid-19-have-changed-pykhova/

[3] House of Commons & Treasury Committee, October 2019, ‘IT failures in the Financial Services Sector’ https://publications.parliament.uk/pa/cm201919/cmselect/cmtreasy/224/224.pdf

[4] Bank of England & FCA, 2018, ‘Building the UK financial sector’s operational resilience’ https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/discussion-paper/2018/dp118.pdf?la=en&hash=4238F3B14D839EBE6BEFBD6B5E5634FB95197D8A

[5] Bank of England/PRA, December 2019, ‘CP29/19 Operational resilience: Impact tolerances for important business services’ https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/consultation-paper/2019/cp2919.pdf

[6] Bank of England/PRA, December 2019, ‘CP30/19 Outsourcing and third party risk management’ https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/consultation-paper/2019/cp3019.pdf?la=en&hash=4766BFA4EA8C278BFBE77CADB37C8F34308C97D5

[7] Key Risk Indicators, Key Control Indicators, and Key Performance Indicators respectively.

[8] There are a whole host of regulations that impact operational risk management in a variety of ways such as CPMI-IOSCO Principles for Financial Market Infrastructures, the G7 Fundamental Elements of Cybersecurity for the Financial Sector, the NIST Cybersecurity Framework, ISO 22301, the Business Continuity Institute (BCI) Good Practices Guidelines 2018.

[9] (Risk Control Self Assessment)

[10] Delayed by a year as a result of Covid 19

[11] ORX, September 2019, The ORX Annual Report, https://managingrisktogether.orx.org/sites/default/files/public/downloads/2019/09/theorxannualreportleadingtheway_0.pdf

[12] Bank of England, June 2019, ‘New Economy, New Finance, New Bank: The Bank of England’s response to the van Steenis review on the Future of Finance’ https://www.bankofengland.co.uk/-/media/boe/files/report/2019/response-to-the-future-of-finance-report.pdf?la=en&hash=C4FA7E3D277DC82934050840DBCFBFC7C67509A4#page=11

[13]  Ibid

 

“Risks are becoming more interconnected and traditional operational risk management is not suited to manage them” –

ORX, The operational risk management association

 

 

Taking an end-to-end view of the ‘chain’ of activities that make up a service and its associated controls, means tracking the entirety of the inputs and outputs from front to back across business lines, middle and back offices, and 3rd party suppliers and outsourcing (e.g. from sales to execution to settlement).

 

Given many firms have challenges managing end-to-end business flows on a BAU basis without significant manual manipulation of data as they are so complex and fractured, there will likely be significant challenges around defining and delivering resilience thresholds which meet the regulatory requirements as the data sets underpinning such thresholds will also be complex and fractured.

 

“firms need to ensure that their cloud-based operating models are not only safe and secure, but address the capabilities required for operational resilience testing. Investment in frameworks and data analytics that can support these capabilities are essential”

 

No-one anticipated a situation of near total remote working that the pandemic has called for – even in extreme scenarios.

 

Real investment in operational risk data capabilities can yield significant business benefits – not just in the reduction of material risk and future spend on compliance, but as an invaluable source of internal intelligence for resource and business optimisation.

 

Nick Fry
Reg Change, Data SME, RegTech Propositions

Experienced financial services professional and consultant with 25 years’ experience in the industry. Extensive and varied business knowledge both as a senior manager in BAU and change roles within investment banking operations and as a project delivery lead, client account manager, practice lead and business developer for consulting firms

 

 

Alaric Gibson
Reg Change, Data SME, RegTech Propositions

Analyst with expertise in regulatory analysis and implementation, customer reference data management, and data driven transformation & delivery. Has worked for a number of RegTech start-ups within Capital Markets.

 

 


Scaling a cyber-security FinTech with our interim COO leadership

"Leading Point have been instrumental in helping us cover our COO needs at a critical stage for the business from a product readiness and a go-to-market perspective. They have developed our client implementation capability with fit-for-purpose processes, systems and methodologies, significantly improving our engagement with our target customers and our time to market. We look forward to our continued alliance with Leading Point as our implementation partner to help us grow in the right way."

CEO @ Information & Cyber Risk Startup


Time to Reset?

We see the varnish from the old oil painting of government, enterprise, business and leadership fade a bit every day. 2020 has already shown us how interconnected our world has become - a true Butterfly Effect. Interconnectivity is not a bad thing. It is the fragility, the brittleness of modern economies that is cause for concern. I believe this is a result of critical imbalances we have allowed to build up, without questioning. Now as the varnish from the old oil painting comes off, we have a once in a decade opportunity to reset and tackle these imbalances. To make bold brush strokes.

Where can we start?

Big Government or Small?

Do we need a Big Government or Small? The term ‘Big Government’ here is not intended to be derogatory. We see national priorities and decisions that don’t match that of the city, the village, or the council. Great plans and budgets that don’t translate into change on the ground. Equally, in the face of this crisis, we see barriers breaking down. A C-19 COVID Symptom tracker app, which each of us can use, allows a judicious allocation of scarce testing and treatment resources at a national and grassroot level. The opportunity is to examine the flow from the national to the level of council. Provide transparency and allow engagement. If it doesn't exist it should be created. Direct channels for us citizens to highlight problems, propose solutions, be data-driven and monitor implementation. It is not a question of a big government versus small. It is one that works transparently that matters.

Public or Private Sector Enterprise?

A key debate going into 2020 was about which sector provides a better service, is more efficient with resources - private or public sector enterprise? Think about the NHS, Transport, Energy, Manufacturing, Financial Services, Agriculture, Technology and Utilities. Healthy arguments and examples are cited to show the merits of both public and private sector. I believe the public-private argument completely misses the point. Whether an enterprise provides a good service or poor, spends judiciously or not is not down to public or private sector. It is down to some key principles - how it is governed, how accountable is its team and partners, does it know what good service looks like and is it equipped to provide these services. Enterprises can be funded by either public or private sector resources. The opportunity ahead is in data and tech enabled service delivery models, going digital. And public-private collaboration funding models can ignite innovation and value added services. The key to provide good service is not public or private sector, it is to provide a good service!

 

Role of Business

Businesses are standing out in two ways in these times. Those that care about their employees and partners and are doing their bit to help their communities and those that pretend to. People will remember businesses that care. Those that don't, will fall out of favour. That most of our essential "front line" staff in the face of a pandemic are paid low/ minimum wages is cowardly. It shows the scale of imbalances we have allowed to build up and seem to be comfortable with. Colleagues in maintenance, cleaning, nursing, restaurant, retail, agriculture, driving, security, manufacturing and teaching professions amongst others need to be compensated fairly. The opportunity here is to go after skewed compensation models, unviable business models and poor productivity with vigour. The tax structures reportedly exploited by big tech and conglomerates are ripe for reform and become principle driven. Likewise business owners having billions and calling for government bailouts or larger profitable companies using furlough schemes to offload their responsibilities to the public should face the consequence. This is a failure of law and the will of successive governments. Let us get it right this time. Bashing businesses and entrepreneurs is not the answer. They are born from the risk-reward equation and are the lifeblood of any economy.

Lessons in Leadership

As much as it is tempting to draw leadership lessons from the current pandemic, they are unique to the situation and not a one size fits all. But I find the war analogy somewhat flawed. The chancellor of the exchequer, Rishi Sunak said “we will be judged by our capacity for compassion and individual acts of kindness” – does that sound like a war? If anything, the lesson for future leaders is to be that much more focused on ensuring their team’s wellbeing, ensuring they are equipped with relevant resources. Good leaders will understand the importance of the informal and the invisible stuff – collaboration, unconventional thinking, meaningful conversations and problem solving over formal organisation structures. The world we have to navigate in is increasingly unpredictable and non-linear, command and control team structures and top-down change will not work.

Everyday we are seeing concrete examples of what is working in business, government and leadership and what is not. We can allow 2020 to be one mired in tragedy, lost lives, lost livelihoods and failed businesses or we can seize the once in a decade opportunity to reset and create the government, the enterprise, the business and leaders that we want and have lacked for some time. This is within reach.

What steps do you think will help create better business, government and leaders?

Please feel free to comment and share. Keep well!

Change leader with over 20 years’ experience in helping financial markets with their toughest business challenges in data, operating model transformation in sales, CRM, Ops, Data, Finance & MI functions, and delivery of complex compliance, front-to-back technology implementations. Significant line experience. Former partner in management consulting leading client solution development, delivery and P&L incl. Accenture. Specialities – Operating Models, Data Assets, Compliance, Technology Partnerships & Solutions in Capital Markets, Market Infrastructure, Buy-Side, Banking & Insurance.

"2020 has already shown us how interconnected our world has become - a true Butterfly Effect."

"It is not a question of a big government versus small. It is one that works transparently that matters."

"Businesses are standing out in two ways in these times. Those that care about their employees and partners and are doing their bit to help their communities and those that pretend to."

 

"We can allow 2020 to be one mired in tragedy, lost lives, lost livelihoods and failed businesses or we can seize the once in a decade opportunity to reset and create the government, the enterprise, the business and leaders that we want and have lacked for some time"

 


Reimagining trading platform support: Who's supporting you through turbulent times?

Trading platform support is, and has been, going through some heavy changes. It’s a changing world we live in and even putting the current situation to one side (we know it’s difficult but let’s try) it’s worth noting how cost reduction, market consolidations, and changes in approach, etc. have changed the landscape for how trading platforms are supported.

Good front line support for trading platform functionality is now more difficult to access and slower to respond resulting in fewer issues actually being resolved.

Changes in focus from vendors has meant the trading industry has had to come up with, let’s face it, a compromise, to ensure their businesses can continue to operate ‘as normal’. There are many new normals across all industries and sectors at present, but the trading world is highly arcane in nature and therefore any change is difficult for traders and salespeople alike. This has translated into moves towards other models like ‘Live Chat’ style support, which some find impersonal, with fewer experienced people showing up regularly at client sites.

At the sharp end this can mean less voice support and a reduction in face to face support resulting in declining reassurance for users from regular contact with the ‘floorwalkers’. Some trading platform users have found that trading support has been neglected and their experience has suffered as a consequence.

For instance, a Waters Technology article, published last year, reported one Fidessa user citing difficulties with issue resolution:

“It seems like they’ve lost the ability to distinguish between a general issue and an urgent issue that needs to be resolved because it’s putting our clients at risk. We’ve had some issues that have been sitting with them for months.”

Obviously this is a sub-optimal ongoing predicament to be in. Whether due to cost savings, staff attrition rates or other reasons – the provision of first line support has deteriorated.

Even so, the cost of support to a trading firm remains constant in real terms. But in terms of what they get in return, it effectively becomes an added overhead translating to something with a diminishing return.

Added to these ongoing, and somewhat reluctantly accepted concerns, new uncertainties are pushing themselves to the forefront of users minds. The big one currently of course are the changes companies and staff are having to make now to their working arrangements in relation to the current climate and the need to maintain a distributed workforce.

Uncertainties around this mean that some in this space now acknowledge a real need for flexibility and better business continuity planning and scalability options (there have been significant spikes in volumes and volatility) in the approach to providing support for users. One just needs to look at the increasing number of LinkedIn or Facebook posts of people attempting to replicate their office desk at home to see the level of impact.

All of the above factors appear to be leading to a dawning realisation for many trading platform users for two necessary changes:

  • A higher degree of self-sufficiency for navigating a platform and making full use of its features.
  • Fast and reliable turnaround for resolving complex issues and being trained in new functionality without the necessity to call upon a fixed cost resource pool.

So what is the obstacle here?

Think about applications like Word or Excel. How many people who regularly use applications such as these are proficient in just enough to enable them to carry out their daily job? Many of these people are probably utilising less than ten percent of what the application offers and therefore unable to identify avoidable bottlenecks and efficiency gains no matter how simple to implement – 90% of the potential benefits remain unused, an ‘unknown unknown’.

With such a wealth of functionality offered, knowing what *really* matters requires an understanding of both the application and your specific needs.

The same can be said for trading functionality; untapped opportunities for improved workflows are lying undiscovered and unutilised before users’ eyes. Comprehensive support and training in existing and new functionality can pave the way for users to discover that potential including, dare we say, the opportunity of alpha generation due to the possibility of speed of use through innate familiarity.

Communication and tailored collaboration with knowledgeable and experienced support teams is essential. Targeted, independent and focused front line support available from experienced outsourced providers presents a viable support proposition for platform users, wherever you sit in the organisation.

At Leading Point we are not only able to react to issues quickly but also know the information you are looking for (often before you need it) that will make a real difference to your daily trading platform experiences. With an innate ability to speak your ‘language’ we can provide seamless communication. All of this underpinned by an always available service when you and your users need it most.

  • Imagine an innovative trading support experience comprising an equally innovative commercial model enhancing an entire trading platform experience.
  • Imagine the knowledge your users can benefit from through such a collaboration and the degree to which that benefit is passed on to clients
  • Imagine, through the unlocking of that untapped potential, your regular users becoming super users

The time for change is NOW. If you’d like to get in touch, we would be delighted to tell you more about the potential benefits to you and your firm.

 

Untapped opportunities for improved workflows are lying undiscovered and unutilised before users’ eyes.

 

Good front line support for trading platform functionality is now more difficult to access and slower to respond resulting in fewer issues actually being resolved.

 

“It seems like they’ve lost the ability to distinguish between a general issue and an urgent issue that needs to be resolved because it’s putting our clients at risk.”


Legal Risk: Too big to manage?

Arguably, the model by which we manage legal risk in Financial Institutions is no longer fit for purpose.

The current model assumes that regulatory change can be accommodated “off the side of the desk” of the legal department using outsourced project teams to do the bulk of the work.  This model may not only be inappropriate in the current deluge of regulation and business generated data, it may actually introduce further risk.

As firms grow and change, they amass an enormous quantity and variety of contracts.  These contracts, coupled with regulations, form an array of legal obligations, which the firm attempts to track. The numbers surrounding regulation and legal data are astronomic:

  • Spending on regulatory compliance is now around 200 to 300 billion US dollars[i]
  • Hundreds of acts are promulgated in the EU alone every year[ii]
  • There are an estimated 50 million words in the UK statute book, with 100,000 words added or changed every month[iii]
  • 250  number of regulatory alerts issued daily  by over 900 regulators globally

And, when firms get into litigation, the figures boggle the mind:

“We’re now working on a case more than twice that size, with 65m [documents], and there’s one on the way with over 100m. It’s impossible to investigate cases like ours without technology.”[iv]

It is not all about the numbers either.  Each piece of new legislation, i.e. new law, is linked somehow with a number of existing laws so it is not just a matter of treating each one in isolation.[v]

In addition, there are self-made “laws” in the shape of legal agreements (contracts) which set out the respective obligations agreed between the parties entering into the agreement.  Both types of law need to be mapped and tracked throughout the contract lifecycle.  Data on this flow management is difficult to come by as many firms do not (or are not able to) collect management information about legal activity.

 

MANAGING LEGAL RISK IS A HUGE UNDERTAKING

Lawyers are working ever harder both in-house and in law firms than ever before.[vi]

It is difficult to generalise about the way in-house legal departments[vii] within financial services firms are run but two general themes are discernible.  General Counsel (GCs) are expected to run their departments aligned to business strategies with budgets provided by the Business[viii]; and, they are expected to manage regulatory and legal risk.

Managing Legal Risk for a large Financial Institution is huge undertaking. Ensuring that a firm tracks emerging regulation, operationalises compliance with new law, educates the workforce (and its clients) on compliance, agrees with its clients in writing how their relationship needs to change in response to new law, ensures that daily business activities are structured to be compliant and are recorded accurately in writing – all this is the management of regulatory and legal risk[ix].

There is no standard definition of legal risk, but can be defined as ‘the risk of loss to an institution that is primarily caused by’:[x]

  1. a defective transaction;
  2. a claim (including a defence to a claim or counterclaim) being made or some other event occurring that results in a liability for the institution or other loss (for example as a result of the termination of the contract);
  3. failing to take appropriate measures to protect assets (for example intellectual property) owned by the institution;
  4. a change in law.

The repercussions for failure to manage legal risk are many and varied.  One of the tools used by the regulators is to “name and shame” non-compliant firms.  Not only does a firm receive a fine but it is also publicly named in the Final Report[xi] and in the press as having failed to comply with the relevant regulation.

This has a direct impact on a firm’s reputation (hence the term “reputational risk”) - current and prospective clients will ask awkward questions or even leave the firm; the firm may lose credibility in the marketplace; the balance sheet and profitability will be impacted.  It also has an adverse impact on a firm’s ability to attract and retain staff.  Employees may ask awkward questions (in some cases whistle blow), leave the firm, or occasionally be able to claim compensation.

All this is in addition to whatever fine is levied which will have balance sheet and prudential management implications.  The firm may need to hold additional capital against the risk of future failure.  And the regulators, globally, will now be acutely aware of a firm’s failings and will be more watchful.

All four of these pillars of legal risk could potentially be in play in each regulatory change project, i.e. when a new law is introduced or an existing law has changed, because with every regulatory change there is always a document change. This means that as regulation evolves, and contracts continue to be developed, there are a myriad of obligations to manage and analyse.

Each regulatory change project, which is conducted in addition to a lawyer’s usual (BAU) duties, produces a plethora of new documents. Lawyers need to analyse each one to figure out how the introduction of new obligations impacts the old ones.  In addition, every new piece of legislation means more reading, more rethinking of business strategy, resulting in more paperwork.

 

IN-HOUSE LEGAL IS UNDER PRESSURE

Despite the scale and complexity of this task, as well as the negative consequences of getting it wrong, the legal department is generally regarded as a cost centre and may be underfunded.

The current model has the legal department in a more or less successful partnership with the Business providing advice on existing and new activities and projects, advising on existing law and new regulations, documenting the intent between the business and their counterparties, i.e. creating/updating legal agreements, negotiating those contracts, advising on strategy and execution when things go wrong.

The legal department is “paid” for its time by way of a budget provided by the business which covers the salaries of lawyers and support staff.  For more difficult matters, the advice of external counsel is sought – again paid for by the Business.

With budget constraints and cost cutting in firms, legal departments don’t have the staff numbers they used to. Like all other functions in-house legal departments are under pressure to cut costs and improve efficiency, transparency, user experience and access to data. Sometimes, more junior lawyers have been retained while seniors have been let go on the basis that external counsel can fill the gap.

If the Business increases its activity level or if there are a number of non-BAU projects then, clearly, these fewer resources are less likely to cope.  This results in slower service to the Business and, sometimes, increased costs as work needs to be outsourced.

The decrease in budget and lawyer numbers are likely to result in increased legal risk because:

  • Delays impact new business as Business may go ahead without legal documentation because they cannot afford to wait. When the deal is finally documented, the documentation may not accurately reflect what was agreed between the parties
  • Tired lawyers make poorer decisions
  • Institutional memory loss as staff leave and legal knowledge pertaining to the Business is lost
  • Increased opportunity costs as prioritisation means that urgent issues may be addressed while the important are left unaddressed[xii]
  • Legal tools which might alleviate some of the above are unavailable or poorly understood or unable to be used.

The result is an environment where legal functions spend the highest proportion of time (and budget) reacting to compliance breaches, misconduct, litigation and arbitration, rather than anticipating risk and prevention – leaving the legal department is unable to adequately support the business’ needs.

So, either the legal department needs more lawyers to keep up with demand or it needs to figure out how to use the lawyers it has more effectively so that they are not spending their time on low level, repetitive tasks which might more efficiently be done by a legal tool.

The model needs to change.

 

[i] KPMG RegTech – There’s a revolution coming puts the figure at $270bn - https://home.kpmg/content/dam/kpmg/uk/pdf/2018/09/regtech-revolution-coming.pdf

[ii] https://eur-lex.europa.eu/statistics/legislative-acts-statistics.html

[iii] https://gtr.ukri.org/projects?ref=AH%2FL010232%2F1

[iv] Ben Denison, Serious Fraud Office chief technology officer, https://www.ft.com/content/7a990f1a-d067-11e8-9a3c-5d5eac8f1ab4

[v] See, for example, John Sheridan’s visualisation of the interconnectedness of one piece of UK legislation (the Companies, Audit, Investigations and Community Enterprise Act 2004)

[vi] https://www.legalcheek.com/2018/11/revealed-law-firms-average-arrive-and-leave-the-office-times-2018-19/

[viii] Legal is perceived as a cost centre not a revenue generator.  The Business is a catch all term which refers to the revenue generating portions of a financial institution

[ix] Legal risk is a subset of operational risk under Basel II

[x] Cited in Legal risks and risks for lawyers, Herbert Smith Freehills and London School of Economics Regulatory Reform Forum, June 2013

[xi] The paper produced by the FCA setting out the details of the firm’s failings and the fine

[xii] President Eisenhower quoting a college president to the Second Assembly of the World Council of Churches: “This President said, "I have two kinds of problems, the urgent and the important. The urgent are not important, and the important are never urgent."”  https://www.presidency.ucsb.edu/documents/address-the-second-assembly-the-world-council-churches-evanston-illinois

 

legal functions spend the highest proportion of time (and budget) reacting... rather than anticipating risk and prevention

 

“We’re now working on a case ... with 65m [documents], and there’s one on the way with over 100m. It’s impossible to investigate cases like ours without technology.”

 

Despite the scale and complexity of this task, as well as the negative consequences of getting it wrong, the legal department is generally regarded as a cost centre and may be underfunded.

 

either the legal department needs more lawyers to keep up with demand or it needs to figure out how to use the lawyers it has more effectively  

 

in-house legal departments are under pressure to cut costs and improve efficiency, transparency, user experience and access to data.

 


Legal Technology in FS – The need for a new legal services operating model

Law, data, machines – these are not words that historically have had much to do with one another.

However, as the number of laws increases, communications traffic increases, and, as the fabric of the law can be read by machines, the interaction between these words will become ever more important.

90% of data in the world has been created in the last two years – and it’s not slowing down. [1]  As regulation increases, the ability of financial institutions to manage the legal risk flowing from that regulation becomes ever more challenged.  The resources being devoted to this increase every year and lawyers are starting to turn to technology to assist.

Recent research[2] found 82% of General Counsel have introduced various forms of technology into their department but 60% of lawyers don’t understand how that technology could help them.  This, at a time where the pressure on resources (both human and financial) means that there is a real need for technological assistance.

The regulatory environment has imposed an unprecedented burden on firms.  Legal risk has become increasingly complex and difficult to manage but is under-examined and often poorly understood.  Due to the massive technological, political, regulatory and cultural shift over the past 30 years, the model by which we manage legal risk is outdated. This has led to increased fines, customer loss and higher operational costs at the least.

Poor management of data results in missed opportunities and increased costs as businesses rerun regulatory change and other projects.  Effective management and exploitation of legal data could provide new business opportunities in addition to saving costs for business as usual (BAU).  There needs to be a more formalised data flow between Business and Legal, leading to an effective and efficient end-to-end framework.

The in-house legal model needs to change.  Technology can help.

But while the market is saturated with ‘RegTech’ and other legal solutions, these are disparate point solutions that do not address the underlying issues.  Lawyers are reluctant to spend time training machines unless results are proven.  This reluctance has resulted in suboptimal take up of the various solutions.

Machines are best at repetitious, low level tasks.  Much of the law is to do with context, relationships between ideas and situations and nuance at which humans are better.  While the race is on for machines to solve the problem of unstructured data, a tool pointed currently at the unstructured data lake that is ‘legal data’ results in unhelpful returns.

A new legal services operating model is needed to diminish the disjointed nature of legal and business issues.  This new operating model needs to take into account not only new technology, but also the underlying data efficiencies to appropriately assemble and deploy solutions seamlessly across legal and business units.

Firms can gain most value by structuring data to best deploy legal technology.  If firms do not make decisions about these issues now they will find themselves trapped in a never-ending loop of manually adjusting data to achieve the required results.

The hardest part of adoption of an “in the round” solution is implementing a framework within the firm which allows the various legal software tools to work optimally. A clear pathway needs to be created to reduce silos, create standards, appoint golden sources and create an enterprise architecture.

Law, data and machines can all work together successfully but it will take vision and hard work.

 

[This is part 1 of a 10 part series where we will consider the role of Legal Technology within Financial Services, how it can and should be applied, and what a ‘utopian’ target operating model for in-house legal departments looks like in FS]

 

[1] Presentation by Dr Joanna Batstone, VP IBM Watson & Cloud Platform, Legal and Technology Procurement 2018 – Thomson Reuters conference 8 November 2018

[2] Legal Technology: Looking past the hype, LexisNexis UK, Autumn 2018

 

There needs to be a more formalised data flow between Business and Legal, leading to an effective and efficient end-to-end framework.

 

A new legal services operating model is needed that takes into account not only new technology, but also the underlying data efficiencies to appropriately assemble and deploy solutions seamlessly across legal and business units.

 

the market is saturated with ‘RegTech’ and other legal solutions, these are disparate point solutions that do not address the underlying issues.

 


Excel Ninjas & Digital Alchemists – Delivering success in Data Science in FS

In February 150+ data practitioners from financial institutions, FinTech, academia, and professional services joined the Leading Point Data Kitchen community and were keen to discuss the meaning and evolving role of Data Science within Financial Services. Many braved the cold wet weather and made it across for a highly productive session interspersed with good pizza and drinks.

Our expert panellists discussed the “wild” data environment in Financial Services inhabited by “Excel Ninjas”, “Data Wranglers” and “Digital Alchemists”. But agreed that despite the current state of the art being hindered by legacy infrastructure and data siloes there are a number of ways to find success.

Here is the Data Kitchen’s ‘Recipe’ for delivering success in Data Science in Financial Services:

1. Delivery is key – There is a balance to strike between experimentation and delivery. In commercial environments, especially within financial services there is a cost of failure. ROI will always be in the minds of senior management, and practitioners need to understand that is the case. This means that data science initiatives will always be under pressure to perform, and there will be limits on the freedom to just experiment with the data.

2. Understand how to integrate with the business – Understanding what ‘good’ delivery looks like for data science initiatives requires an appreciation of how the business operates and what business problem needs to be solved. Alongside elements of business analysis, a core skill for practitioners is knowing how to ‘blend in’ with the rest the business – this is essential to communicate how they can help the business and set expectations. “Data translators” are emerging in businesses in response.

3. Soft skills are important – Without clear articulation of strategy and approach, in language they can understand, executives will often either expect ‘magic’ or will be too nervous to fully invest. Without a conduit between management and practitioners many initiatives will be under-resourced or, possibly worse, significantly over-resourced. Core competencies around stakeholder and expectation management, and project management is needed from data practitioners and to be made available to them.

4. Take a product mindset – Successful data science projects should be treated in a similar way to developing an App. Creating it and putting it on the ‘shelf’ is only the beginning of the journey. Next comes marketing, promotion, maintenance, and updates. Many firms will have rigorous approaches to applying data quality, governance etc. on client products, but won’t apply them internally. Many of the same metrics used for external products are also applicable internally e.g. # active users, adoption rates etc. Data science projects are only truly successful when everyone is using it the way it was intended.

5. Start small and with the end in mind – Some practitioners find success with ‘mini-contracts’ with the business to define scope and, later, prove that value was delivered on a project. This builds a delivery mindset and creates value exchange.

6. Conduct feasibility assessments (and learn from them) – Feasibility criteria need to be defined that take into account the realities of the business environment, such as:

  • Does the data needed exist?
  • Is the data available and accessible?
  • Is management actively engaged?
  • Are the technology teams available in the correct time windows?

If you run through these steps, even if you don’t follow through with a project, you have learned something – that learning needs to be recorded and communicated for future usage. Lessons from nearly 100+ use cases of data science in financial services and enterprises, suggest that implementing toll-gates for entry and exit criteria is becoming a more mature practice in organisations.

7. Avoid perfection - Sometimes ‘good’ is ‘good enough’. You can ‘haircut’ a lot of data and still achieve good outcomes. A lot of business data, while definitely not perfect, is being actively used by the business – glaring errors will have been fixed already or been through 2-3 existing filters. You don’t always need to recheck the data.

8. Doesn’t always need to be ‘wrangled’ – Data Scientists spend up to 80% of time on "data cleaning" in preparation for data analysis but there are many data cleansing tools now in the market that really work and can save a lot of time (e.g. Trifacta). Enterprises will often have legacy environments and be challenged to connect the dots. They need to look at the data basics – an end to end data management process, the right tools for ingestion, normalisation, analysis, distribution and embedding outputs as part of improving a business process or delivering insights.

Our chefs believed Data Science will evolve positively as a discipline in the next three years with more clarity on data roles, a better qualification process for data science projects, application of knowledge graphs, better education and cross pollination of business and data science practitioners and the need for more measurable outcomes. The lessons from failures are key to make the leap to data-savvy businesses.

Just a quick note to say thank you for your interest in The Data Kitchen!

We had an excellent turn out of practitioners from organisations including: Deutsche Bank, JPMorgan, HSBC, Schroders, Allianz Global Investors, American Express, Capgemini, University of East London, Inmarsat, One corp, Transbank, BMO, IHS Markit, GFT, Octopus Investments, Queen Mary University, and more.

And another Thank You to our wonderful panellists!

  • Peter Krishnan, JP Morgan
  • Ben Ludford, Efficio
  • Louise Maynard-Atem, Experian
  • Jacobus Geluk, Agnos.ai

…And Maître De – Rajen Madan, Leading Point FM
We would like to thank our chef’s again and to all participants for sharing plenty of ideas on future topics, games and live solutions.


LIBOR Signals Need for New Approaches to Legal Data

The Scope of LIBOR Remediation is the Problem

Time is now of essence – with the end of 2021 deadline looming, financial institutions need to reduce their ‘stock’ of legacy LIBOR contracts to a minimum as a matter of priority, writes Rajen Madan, CEO, Leading Point.

The challenge is of course colossal. Firms need to find every reference to IBORs embedded in every contract they hold; update each contract with fallback provisions / reflect the terms of the alternative reference rate they are migrating to; and communicate the results with clients.

LIBOR’s retirement potentially impacts over $350 trillion of contracts and requires all LIBOR transactions (estimated at over 100 million documents) to be examined and most likely repapered. LIBOR is embedded in every asset class – mortgages and retail loans, to commodities, derivatives, bonds and securities.

It’s estimated that large banks may be exposed to more than 250,000 contracts directly referencing LIBOR maturing after 2021, and indirectly exposed to many thousands more embedded in servicing activities, supplier agreements and such.

Only 15 percent of Financial Institutions are ready to deal with this volume of contract remediation, deal restructuring, and repapering activities required for the scale of their legacy contract back-book; 14 of the world’s top banks expect to spend more than $1.2 billion on the LIBOR transition.

 

Firms that have comprehensive visibility of their legal contract information via retained structured data, can avoid 80 percent of the typical repapering process, and focus their efforts on the remaining, critical, 20 percent.

 

LIBOR Repapering Not a ‘Find and Replace’ 

The repapering of contracts isn’t as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR.

Risks are many including conduct, legal, prudential and regulatory. Consider ‘conduct’ risk. In the UK, the Treating Customers Fairly (TCF) regime is particularly concerned with how customers are affected by firms’ LIBOR transition plans. Before contracts can be updated, firms will need to ensure that LIBOR linked products and services have ‘fair’ replacement rates that operate effectively.

Similarly, there’s prudential risk. When the underlying contracts change, firms may find that the instruments they rely on for capital adequacy purposes may no longer be eligible, potentially even resulting in a sudden drop in a bank’s capital position. Similarly, there are several Counterparty Credit, Market, Liquidity, and Interest Rate Risks that will need to be reflected in firms’ approaches.

 

LIBOR is proving to be a real impetus for financial institutions to use technology that, to be honest, has been available in the marketplace for a long time now.

 

Mindset Change is Needed to Manage Legal Data

Most historic repapering exercises have involved hastily identifying the documents impacted, outsourcing the difficult issues to law firms (at huge cost) and throwing manpower (again at substantial cost) at the problem to handle the contract updates and communications with counterparties. The exact same process has been repeated for every repapering project. Despite the substantial costs, many financial institutions still don’t meet the deadline. MiFID II is an example.

With ample evidence of regulators continually tightening their grip on financial institutions through reform – alongside an increasingly dynamic global business environment (e.g. LIBOR, Brexit) – it is time organisations acknowledged and accepted repapering as a ‘business as usual’ activity.

A change in mindset and a smarter approach is needed to manage legal data. Financial institutions need to ensure that LIBOR or indeed any future business repapering exercise does not compromise client well-being or negatively impact client experience. For instance, to accurately model the financial risk firms’ portfolios are exposed to via LIBOR when transitioning to a new rate, they need a way to directly link, say, multiple cash and derivative contracts to a single client. Furthermore, in an environment where most firms are product driven, the scenario of multiple repetitive communications, requests for information and re-papering contract terms looms on the horizon for firms’ customers.

It is heartening to see that LIBOR is beginning to pique the interest of financial institutions to develop a long-term vision to create smarter capabilities that will deliver business advantages in the future.

Stephanie Vaughan, Global Legal AI Practice Director at iManage RAVN and ex-Allen & Overy, recently observed, “LIBOR is proving to be a real impetus for financial institutions to use technology that, to be honest, has been available in the marketplace for a long time now. While they may have dabbled with it in the past, due to the scale of the LIBOR remediation and the constantly changing regulatory challenges, it has finally hit home that such projects are a drain on resources and are delivering no business value.”

 

Financial institutions have started every repapering project (e.g. MiFID II, Dodd Frank, Margin Rules) from scratch including going through the entire process of determining the clients, what the terms of engagement are, when the contracts expire and so on.

 

Technology Can Make Repapering ‘Business as Usual’

A strategic approach to managing legal data requires all stakeholders in a financial institution to come on board – from business units and the compliance department through to legal operations and the General Counsel. This is instrumental to ensuring genuine cross-functional recognition and support for strategic directional change.

Financial institutions need to build a strong, technology-supported foundation for remediation projects. Thus far, financial institutions have started every repapering project (e.g. MiFID II, Dodd Frank, Margin Rules) from scratch including going through the entire process of determining the clients, what the terms of engagement are, when the contracts expire and so on.

Hereafter, with LIBOR and Brexit, extracting, classifying, storing and maintaining all these data points as structured, base level information on customers on a single technology platform, will provide institutions with capabilities to quickly understand their exposure, assign priorities and flexibly make contractual changes in tune with evolving requirements.

This approach is proven. Firms that have comprehensive visibility of their legal contract information via retained structured data, can avoid 80 percent of the typical repapering process, and focus their efforts on the remaining, critical, 20 percent. Financial institutions will then also be well poised to take advantage of new bolt on capabilities  that leverage artificial intelligence for application to specific use-cases – which in turn can deliver business value from contract search, contract classification, clause management, to real time analytics, contract generation and integration with operational, risk and compliance systems.

The opportunity with more effective legal data management is huge and realisable. Building and incrementally strengthening capability through the strategic and proactive use of technology is potentially the only way for financial institutions to adapt to their new regulatory and business environment.

 

The repapering of contracts isn’t as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR.

 

 


LIBOR: Manual Approaches are no Longer Enough to Manage FS Legal Data

The transition away from LIBOR is the biggest contract remediation exercise in Financial Services history – and firms are under prepared.

As the Bank of England and FCA lays out in bold font, in their January 2020 letter to CEOs, “LIBOR will cease to exist after the end of 2021. No firm should plan otherwise.”[1] As a result, Financial Institutions have very little time to reduce their “stock of legacy LIBOR contracts to an absolute minimum before end-2021”.

The challenge is this:

1. Firms have to find every reference to IBORs embedded in every contract they hold.

2. Update each contract with fallback provisions or to reflect the terms of the alternative reference rate they are migrating to.

3. Communicate the results with clients

 

This is much easier said than done due to the sheer scale of the task.

LIBOR’s retirement has the potential to impact over US$ 350 trillion of contracts and will require all LIBOR transactions (estimated at over 100 million documents) to be examined and most likely repapered. LIBOR is embedded in far more than just derivative contracts. Every asset class is affected; from mortgages and retail loans, to commodities, bonds or securities. The resolution of Lehman Brothers after 2008 gives some idea of the scale of the repapering effort for each firm – Lehman was party to more than 900,000 derivatives contracts alone.

The scope of the problem is part of the problem. Hard numbers are difficult to come by as no-one really knows exactly what their exposure is, or how many contracts they need to change.

Current estimates say large banks’ may be exposed to more than 250,000 contracts directly referencing LIBOR maturing after 2021, and indirectly exposed to many thousands more embedded in servicing activities, supplier agreements or more.

Only 15% of Financial Institutions are ready to deal with this volume of contract remediation, deal restructuring, and repapering activities required for the scale of their legacy contract back-book.[2] Fourteen of the world’s top banks expect to spend more than $1.2 billion on the LIBOR transition[3].

 

To approach the LIBOR transition manually will likely require years of man-hours and cost millions of dollars, with significant potential for human error

 

There are a wide variety of risks to consider.

But it’s not as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR. Firms face huge operational, conduct, legal and regulatory risk arising from both the difficulties in managing the vast volumes of complex client contractual documentation but also the downstream impacts of that documentation having been changed.

Conduct Risk: In the UK, the Treating Customers Fairly (TCF) regime is particularly concerned with how customers are affected by firms’ LIBOR transition plans. Before contracts can be updated, firms will need to ensure that LIBOR linked products and services have ‘fair’ replacement rates that operate effectively.[1] Firms will also need to ensure that any changes made are applied across the entire customer ‘class’ to comply with TCF rules and avoid preferential treatment issues.

Legal Risk: There is a huge amount of legal risk arising from disputes in what interest rates should be paid out in amended agreements referencing alternative reference rates.[2] The ISDA protocol expected to be published in Q2 2020 should help with, but not solve, these problems.[3]

This is not to mention the legacy contracts that cannot legally be converted or amended with fallbacks – named by Andrew Bailey at the FCA as the ‘tough legacy’.[4] The UK Working Group on Sterling Risk Free Reference Rates (RFRWG) is due to publish a paper on ‘tough’ legacy contracts in the second half of Q1 2020.[5]

The realism of firms’ assessments of the number of contracts requiring renegotiation should be considered a legal risk in itself – a realised 10% increase in this number would likely incur serious, additional legal fees.

Prudential Risk: When the underlying contracts change, firms may find themselves in a position where suddenly the instruments they rely on for capital adequacy purposes may no longer be eligible - “This could result in a sudden drop in a bank’s capital position.” [6] For similar reasons, there are a number of Counterparty Credit, Market, Liquidity, and Interest Rate Risks that will need to be reflected in firms’ approaches.

Regulatory Risk: Regulators are closely monitoring firms’ transition progress – and they are not happy with what they are seeing. Financial Policy Committee (FPC) stated in January, 2020, has made clear that they are ‘considering’ the supervisory tools that authorities could use to “encourage the reduction in the stock of legacy LIBOR contracts to an absolute minimum before end-2021.”[7] This is regulatory code for ‘we will either fine or increase the capital requirements for firms we judge to be dropping the ball’. The PRA and FCA laid out their expectations for the transition in June 2019 – this is required reading for any LIBOR transition project manager.[8]

 

It’s not as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR

 

What this means for firms is that they need:

1. The capability to quantify their LIBOR exposure – Firms need a good understanding of their LIBOR contractual exposure that can quantify a) firms’ contractual population (i.e. which documents are affected) b) the legal, conduct and financial risk posed by the amendment of those documents

2. The ability to dynamically manage and track this exposure over time – As strategies evolve, the regulatory environment changes, and new scenarios develop, so will firms’ exposure to LIBOR change. Without good quality analytics that can track this effectively, in the context of this massive change project, firms will be strategically and tactically ‘flying blind’ in the face of the massive market shifts LIBOR will bring about.

3. The capability to manage documentation - Jurisdictional, product, or institutional differences will necessitate large client outreach efforts to renegotiate large populations of contracts, manage approvals & conflict resolution, while tracking interim fall-back provisions and front office novation of new products to new benchmarks.

Accomplishing the above will require enterprise-wide contract discovery, digitisation, term extraction, repapering, client outreach and communication capabilities – and the ability to tie them all together in a joined-up way.

To approach the LIBOR transition manually will likely require years of person-hours and cost millions of dollars, with significant potential for human error.

 

Accomplishing the above will require enterprise-wide contract discovery, digitisation, term extraction, repapering, client outreach and communication capabilities – and the ability to tie them all together in a joined-up way

 

LIBOR cannot be treated as ‘just one more’ repapering exercise.

Firms are continually hit with new requirements which require the update, negotiation and amendment of client contracts.

The reaction is always the same: Scramble to identify the documents impacted, outsource the thornier problems to external legal, and hire huge teams of consultants, remediation armies and legal operations to handle the contract updates and communications with counterparties.

Once complete - often months past the deadline - everyone stands down and goes home. Only to do the same thing again next year in response to the next crisis. While this gets the job done, there are number of problems with this project by project approach:

1. It’s inefficient: Vast amounts of time (and money) is spent just finding the documents distributed around the business, often in hard copy, or locked away in filing cabinets.

2. It’s expensive: External legal, consultants and remediation shops don’t come cheap – especially when the scope of the project inevitably expands past the initial parameters.

3. It’s ineffective: Little to no institutional knowledge is retained of the project, no new processes are put in place, and documents continue to get locked away in filing cabinets - meaning when the time comes to do it again firms have to start from scratch.

When you look at the number of major repapering initiatives over the past 10 years the amount of money spent on repapering projects is monumental. In the EU alone, regulations such as MiFID II, EMIR, GDPR, PPI, FATCA, Brexit and AIFMD have each required a huge repapering project. In 2020, LIBOR, Initial Margin Rules and SFTR will each require contract remediation programmes.

Doing ‘just another’ repapering exercise for LIBOR is a risky mistake. There is a better way.

Smarter data management and enabling tech solutions can help identify, classify and extract metadata from the huge volumes of LIBOR impacted documents at speed. The ability to extract and store contractual information as structured information at this scale allows firms’ the essential capabilities to understand and track their LIBOR exposure, assign priorities and maintain flexibility in a changing situation.

Firms that have fuller visibility of their legal contract information, retained as structured data, can avoid 80% of the typical repapering process, and focus their efforts on the remaining, critical, 20%.[1] The time spent manually identifying contractual needs, can be reallocated to the areas that matter, freeing up legal resource, budget, and project timelines – while simultaneously improving client relationships.

This should not be seen just as a repapering enabler, but a strategic capability. The opportunities afforded through data mining firms’ contractual estate for analytics are vast.

 

Doing ‘just another’ repapering exercise for LIBOR is a risky mistake. There is a better way

 

One possibility is the ability to connect contracts directly to trades. To accurately model the financial risk firms’ portfolios are exposed to via LIBOR when transitioning to a new rate, they will need a way to directly link, for example, multiple cash and derivative contracts to a single client. Firms are still a long way from this capability – but there are a growing number of sophisticated artificial intelligence solutions that can begin to address these types of use-cases.

Firms that build these capabilities now will materially reduce their risk exposures, improve liquidity and funding, build trust with their clients and be much better equipped to meet other pressing regulatory requirements such as Brexit, SFTR, CRD 5/6, Initial Margin (IM) rules, QFC and more.

 

[1] ‘Next steps on LIBOR transition’, January 2020, FCA & PRA https://www.fca.org.uk/publication/correspondence/dear-smf-letter-next-steps-libor-transition.pdf
[2] 2019 LIBOR Survey: Are you ready to transition?, September 2019, Accenture. https://www.accenture.com/_acnmedia/109/Accenture-2019-LIBOR-Survey-fixed.pdf#zoom=50
[3] ‘The end of Libor: the biggest banking challenge you've never heard of’, October 2019, Reuters.
[4] Firms will also need to consider whether any contract term they may rely on to amend a LIBOR-related product is fair under the Consumer Rights Act 2015 (the CRA) in respect of consumer contracts. FG18/7: Fairness of variation terms in financial services consumer contracts under the Consumer Rights Act 2015 contains factors that firms should consider when thinking about fairness issues under the CRA when they draft and review unilateral variation terms in their consumer contracts. https://www.fca.org.uk/markets/libor/conduct-risk-during-libor-transition
[5] Litigation risks associated with Libor transition: https://collyerbristow.com/longer-reads/litigation-risks-associated-with-libor-transition/
[6] UK Working Group on Sterling Risk-Free Reference Rates (RFR WG) 2020 Top Level Priorities. https://www.bankofengland.co.uk/-/media/boe/files/markets/benchmarks/rfr/rfrwgs-2020-priorities-and-milestones.pdf?la=en&hash=653C6892CC68DAC968228AC677114FC37B7535EE
[7] LIBOR: preparing for the end, https://www.fca.org.uk/news/speeches/libor-preparing-end
[8]  UK Working Group on Sterling Risk-Free Reference Rates (RFR WG) 2020 Top Level Priorities. https://www.bankofengland.co.uk/-/media/boe/files/markets/benchmarks/rfr/rfrwgs-2020-priorities-and-milestones.pdf?la=en&hash=653C6892CC68DAC968228AC677114FC37B7535EE
[9] Letter from Sam Woods: The prudential regulatory framework and Libor transition, Bank of England, https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/letter/2019/prudential-regulatory-framework-and-libor-transition.pdf?la=en&hash=55018BE92759217608D587E3C56C0E205A2D3AF4
[10] ‘Next steps on LIBOR transition’, January 2020, FCA & PRA https://www.fca.org.uk/publication/correspondence/dear-smf-letter-next-steps-libor-transition.pdf
[11] ‘Firms’ preparations for transition from London InterBank Offered Rate (LIBOR) to risk-free rates (RFRs): Key themes, good practice, and next steps.’, June 2019, FCA & PRA https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/2019/firms-preparations-for-transition-from-libor-to-risk-free-rates.pdf?la=en&hash=EA87BD3B8435B7EDF25A56C932C362C65D516577
[12] MiFID II – the long tail of legal documentation repapering, https://www.fintechfutures.com/2018/04/mifid-ii-the-long-tail-of-legal-documentation-repapering/

 


Intersecting the Old World with the New

It has always been a challenge for large corporations to adopt change.  There is constant change being experienced at all institutions but, despite the appetite for change, the size of an organisation often hamstrings its ability to execute on innovative initiatives.

So, what differentiates those who can deliver successful change versus those who cannot?  In one word: Execution!

Execution is the biggest differentiator between small, agile and nimble businesses and their much larger counterparts.  Even if you put to one side the classic large corporate roadblocks (such as organisational complexity and bureaucracy), it’s clear that those who decide to take the leap of faith and try to change the world by starting their own businesses seem to be able to avoid and, often, ignore convention to deliver significant change.

Innovation in large organisations must pass through many layers of change management and control which frequently ties the hands of those who are the agents of change. Equally frequently, organisational politics have an adverse impact.  This is not true of ‘Upstarts’.

‘Upstarts’ break the glass ceiling of ‘the norm’ to create change by significantly improving an existing system or reinventing a process, convention, etc.  But one must question why it is easier for Upstarts to achieve significant change where larger organisations struggle and fail to achieve the same success.

Is it because Upstarts have more skills or able people to execute change?  Probably not, although one must believe Upstart people form a more focused collective.  It’s much simpler than that – it’s a matter of having the time and inclination to apply that collective focus to the achievement of a single objective.  Having, as a sole objective, creating and delivering industry augmenting technology will result in an executable product roadmap and realistic delivery timelines.

Execution is the biggest differentiator between small, agile and nimble businesses and their much larger counterparts

However, there is one area in which large corporates have the upper hand: domain expertise.  Upstarts, by virtue of their size, generally do not have the breadth of expertise of larger organisations.  There are many Upstarts who are capable and indeed do produce top of the line tech solutions.  However, often these same single solutions providers (focus!) struggle to appreciate and navigate the vast array of problems large FS organisations are looking to address. Due to these information gaps, solutions can often result in not being fully fit for purpose and therefore hinder an Upstarts ability to precisely satisfy the needs of large FS corporates.

In addition, large organisations have deep pockets.  This allows them to research and develop solutions internally or to attract external innovation by setting up Innovation Labs, or both.  The main objective of these Labs is to experiment with and identify the kind of innovation that will create competitive advantage.  Upstarts may find themselves part of the Innovation Lab or even acquired in the process.

While Innovation Labs may ensure large players don’t get left behind, there is a big opportunity being missed.  This is the integration of external innovation with internal processes and capabilities.  Acquisitions should be aligned with internal use cases i.e. known (or guessed at) issues with existing business workflows such as efficiency gains.  The main reason seems to be that each is located in its own silo.

Having, as a sole objective, creating and delivering industry augmenting technology will result in an executable product roadmap and realistic delivery timelines

So internal use cases (areas in need of improvement and change) are not connected to potential external innovative solutions.  And this is not to speak of the bigger challenge which is to identify those use cases in the first place.  This raises a number of questions:

  • Does the right type of resource exist?
  • Can available internal staff ask the right questions?
  • Is an independent party better placed to conduct such an exercise?
  • Will this be prevented by internal politics?
  • Who’s going to pay for the work?
  • Who’s going to take ownership?
  • … and the list goes on.

Successful organisations engage the right people at the right level internally as well as identify and breakdown the ability of Upstarts to address wide ranging and often long-standing issues.  This takes a certain type of skill set including

  • The ability to face off across the corporate spectrum
  • Applying the correct level of domain expertise and insight, and
  • The ability and expertise to collaborate with Upstarts; to name but a few.

Entrepreneurs, especially the good ones, know that if failure is to happen, it happens fast.  This requires the ability to EXECUTE. 

The common thread: entrepreneurship. Why?

Entrepreneurs, especially the good ones, know that if failure is to happen, it happens fast.  This requires the ability to EXECUTE.  Getting the job done is very high on the agenda for any entrepreneur.  Lateral and cohesive thinking is also vital.  Steve Jobs once said, “creativity is just merging things” and entrepreneurs do this better than anyone and tend to find ways through means others don’t or won’t pursue through such approaches as marginal gains.

Entrepreneurs don’t have all the answers. Not at all.  But to bridge the gap between larger, more conventional-minded organisations and newer Upstarts, one must have the ability to “intersect the old world with the new”.  An excellent example of this was the event we ran Data Innovation Uncovered and the work we continue to do in the FinTech space including in Enterprise Blockchain and Client Lifecycle Management.

We love to talk about this intersection and encourage free and open conversation so please feel free to get in touch to share your thoughts or indeed to hear more of ours.

To bridge the gap between larger, more conventional-minded organisations and newer Upstarts, one must have the ability to “intersect the old world with the new”


Event: Law, Data & Machines: How can AI reduce the cost of client repapering?

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The deadline for LIBOR is fast approaching.

Many financial institutions are struggling with their re-papering exercise and are facing similar challenges due to the sheer size, scale and scope of the problem.

Firms are under huge pressure from regulators, clients and their competitors to manage their contractual obligations more effectively:

  • Volume – The sheer volume of legal documentation to track numbers in the millons for many institutions
  • Effort – Low levels of automation and digitisation of legal workflow and processes means high no. of resources and spend on professional services
  • Spend – Current and ongoing major client documentation remediation projects such as Brexit, LIBOR, and QFC
  • Risk – Inability to track legal documentation across silos, products, or clients leads to legal, reputational, and operational risk.

Leading Point FM and iManage are hosting an industry innovation session on the use of machine learning software to automate the review and repapering of documents affected by this and other remediation projects.

Participants will be guided by leading industry practitioners on topics including:

  • De-mystifying how technology can be used in the Finance Industry and the wider use cases it solves
  • Key challenges to implementation and how to overcome them
  • The immediate and future benefits that can be gained in this approach

At this event you have an opportunity to benchmark your organisation’s approach to LIBOR and other regulations that require repapering against your peers with practitioners from the Legal, COO, and Change & Compliance sectors.

Date: 26th February 2020
Venue: City Point, 1 Ropemaker Street, London, EC2Y 9AW
Time: 16:00-18:00 followed by drinks & networking

 
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The Data Kitchen | Does data need 'science'?

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Does data need science?

There is a huge skills gap in the data landscape. Europe needs 346,000 more data scientists in 2020 for the 47% of EU organisations struggling to fill data science roles.*

Financial Services is primed to take advantage of what data science can deliver in a wide variety of use-cases like risk analytics, customer behaviour analytics, fraud detection, customer data management, algorithmic trading, natural language services – to name just a few.

However, when an estimated 70% - 85% of data science projects fail, only 20% of analytics insights deliver business outcomes, and 80% of AI projects “remain alchemy, run by wizards”, it is clear that data science is no guarantee of business success.**

Often the problems faced by organisations don’t need data science to solve. Just because your business holds unstructured data, does it need to be analysed? When Data Scientists spend up to 80% of time on "data cleaning" in preparation for data analysis, statistical modelling, & machine learning it is clear that data science/analytics aren't yet ready for self-service at the vast majority of companies.

Companies who find success with data science have a very clear idea of what they want to do with data. They think very hard about how to collect it, how to store it, how to process it, what kinds of analyses they want to perform on it, what they want to do with the results, and how to communicate the results to stakeholders.

There is a wide world of data professionals who understand that focus on the data ‘fundamentals’ i.e. quality, structure, accessibility is essential to business outcomes. Many organisations are missing these fundamentals.

So, in an environment where the skills are difficult to find and expensive to hire, ROI is hard to realise, and the data to be studied is dirty or non-existent – Does data really need science?

*Oreilly Media, 2019, Evolving Data Infrastructure

** Gartner, 2019, Gartner Top Strategic Predictions for 2020 and Beyond

 

Come to the Data Kitchen to discuss:

• What does Data Science really mean in the Financial Services context? Is there a common definition?

• How does data engineering improve the speed and quality of data scientists' work?

• Are there best practices to delivering ROI in data science in Financial Services?

• Are traditional data roles being superseded by ‘scientists’?

Why should you come?

Learn from experienced FS practitioners about how they have delivered business initiatives with data as an asset

Share ideas on how you can position yourself in the dynamic world of data

Network with like-minded people from FS, Fintech, VC’s, and Data-Innovators and gain insights on career paths

Whether you are a recent graduate, a businessperson, a technologist, a data scientist or just work on data initiatives, come along to meet like-minded people.

 

Introducing The Data Kitchen

Food | The Kitchen is where people gather to eat, drink and spend time with family. But it is also a place of work. You can do both at the Data Kitchen.

Data | The Data Kitchen is a community of people interested in, or working with, data in Financial Services. Every event focuses on a different theme related to data as an asset or data as a liability and related innovative topics within Financial Services.

Community | We aim to provide a warm, conversational atmosphere to share ideas, learn and network over drinks and hot food. Our events are free and open to everyone.

Insight | The events are a great opportunity to listen to fascinating insight on the modern developments in data-innovations, AI, DLT in the industry through experiences of FS and Fintech professionals.

Tickets are available on a 1st come, 1st served basis.

Future Events

April 2020 Burrito vs Pastry chef - Does data need to be fancy?

June 2020 Farm to table for Data - How important are your data sources?

August 2020 Data Lasagne – Many cheesy layers?

October 2020 The Data Practitioners Cookbook
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Leading Point FM featured in IFTA 2019 Trade Handbook

Leading Point has been featured in the “India Fintech Awards - IFTA 2019” Trade Handbook highlighting 30 UK fintechs with a strong presence or interest in the Indian market. We are proud to be selected alongside Transferwise, Revolut, R5FX and Onfido. This demonstrates our ongoing partnerships with the East and sets us up for an exciting 2020!

Our team was part of the Fintech Trade Mission to India in May-June 2019 with the London Mayors Office and will be participating again in 2020.


Leading Point FM CEO Rajen Madan on Fintech Focus TV

Leading Point FM Founder & CEO Rajen Madan has been featured on Harrington Starr's Fintech Focus TV where he discussed the company's capabilities and solutions, the world of data, problems in the FS industry. He provides an overall picture of new technology and trends in the market with a growing focus on delivery and execution in companies!

 


Leading Point FM successfully delivers ISO 27001 certification for Fintech client

Leading Point led the certification process for external global accreditation ISO 27000 for one of their leading global Distributed Ledger Technology clients. ISO 27001 is an international Information Security Management System standard providing best practice in improving information security and also compliance with GDPR. The COO of Adjoint found Leading Point's steer in Stage 1 & 2 delivery and execution invaluable: 

"We partnered with Leading Point Financial Markets to define and implement our ISMS. Adjoint selected to partner with Leading Point on this project because they have extensive experience within the FinTech industry, this coupled with the expertise and experience within the information security domain, Leading Point were the obvious choice for this project. What should not be overlooked is Leading Point's influence and recommendations in deciding the most appropriate certification to go for as well as guidance on what ongoing maintenance would be best suited for our needs and match with those of the global certification provider."

 

About Leading Point Financial Markets:

Leading Point FM is a data-driven business solutions provider for transformative plays in Financial Services. It works with FinTech, RegTech, DataTech on the one hand and established Financial Institutions to deliver smoother, cost effective business operations. Global financial institutions use Leading Point FM for its Think Fast design, domain data assets and unique ability to deploy ML, AL and DLT in functions such as Client Lifecycle Management, Compliance, Legal, Risk and Data Analytics.

 

About Adjoint:

Adjoint Treasury is a powerful platform that unifies your treasury workstation, accounting record, and bank systems to enable real-time payments & settlements, cash management & flexible intercompany loans. Gain visibility, increase control and allow for instantaneous transfers without cumbersome reconciliations.

 


The Data Kitchen: 'Data & Risk: Have you left the stove on?'

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In our Data Kitchen event we reviewed the Cyber Security threat landscape, market trends and covered key questions regarding Information Security. It was a highly interactive session with insights on:

-        Where does Info Security fit in the organization in Fintech, Established Financial Institutions and what does the Info Security Solution Ecosystem look like

-        What role does tech play in Info Security?

-        What are the key business Data Risk challenges and focus for the next 5 years?

-        Where are the future opportunities and risk mitigation

 

The Recipe’ for tackling InfoSec problems in the rapidly evolving digital innovation landscape in financial services includes seven ingredients

  1. Culture – Cyber is not just a technology problem, it is a people problem. You cannot mitigate cyber risks with just technology; embeddin g the right culture in your people is vital.
  2. Knowing what is important – Data is expanding exponentially – you have to know what you need to protect. Only by defining importan t data, reducing the data “signal noise” and joining multiple data up can organisations look to protect it.
  3. Speed means risk – The speed of innovation is often faster than the ‘speed’ of safety. Understanding that as the world moves towards ‘real-time’, batch-processing operating models will be left behind. As technology and data adoption is rapidly changing, data protection has to keep up as well – there is little point in investing in technology until you really understand your risks and your exposure to those risks. This is increasingly true of new business-tech frameworks, including DLT, AI and Open Banking. In turn this should inform product design and business strategy of Fintech.
  4. Master the Basics – 80% of UK companies and startups are not even Cyber Essentials ready, which shows that real fundamentals are not bei ng dealt with. Larger companies are rigid and not sufficiently agile – more demands are being placed on teams but without sufficient resources and skills development. Large companies cannot innovate if they are not given the freedom to actually adapt.
  5. Collaboration – Plenty of innovative startups are created day-by-day and more to follow in the future. Large businesses need to be more open to collaborating with them to help speed up advancements in the Cyber Risk space.
  6. Technology Plays a Key Role – Emerging operating models are more open API’s Fintech, and organisations need to stitch together many poi nt solutions. Tech can help here if deployed correctly. To join up multiple data. To provide transparency of messages cross in and out of systems.  To execute and detect information security processes and controls with 100X efficiency and speed. This is material in the new world of FS.
  7. Take a holistic view of your data risk – Cyber risk (especially regarding data protection) is simultaneously a compliance problem (regul atory risk, legal risk etc.), an architecture problem (infrastructure, business continuity, etc.), and a business problem (reputational risk, loss of trust, ‘data poisoning’, competitor intelligence etc.). i.e. You can have the best Cyber Security software in the world, but it is worthless if your customer data server’s power supply is exposed on the outside of the building. There are existing risk assessment frameworks for managing operational risk (example: ORMF) – why not plug in?

Just a quick note to say thank you for your interest in The Data Kitchen!

We had an excellent turn out of practitioners from organisations including: Deutsche Bank, Lloyds Banking Group, Star Compliance Inc, Panaseer, JPMorgan, HSBC, Kubrick Group, Macquarie Group, Bank of America, Standard Chartered Bank, FinchCapital, Adjoint Inc, ICE, QVC, Flux and Mizuho at the latest Data Kitchen last week.

For our second Data Kitchen we thought our ‘chefs’ brought out some brilliant ingredients and insights from their experiences in addressing Cyber Security strategically, representing Fintech, Institutional, Investor and Tech viewpoints.

  • David Reynolds, SEED VC
  • Gary Wong, Razor Risk
  • Somil Goyal, Adjoint

…And Maître De - Rajen Madan, Leading Point FM

 We would like to thank our chef’s again and to all participants for sharing plenty of ideas on future topics, games and live solutions.

The next Data Kitchen – Does data need ‘science’? will be on the 20th Feb 2020!

Register here: https://www.eventbrite.co.uk/e/the-data-kitchen-does-data-need-science-tickets-84178635565

We are also proud to present a sequel to this Data Kitchen: Data & Risk ‘Have you left the stove on?’ for June 2020, where we will be bringing 5 high potential cybersecurity starts-ups to pitch and showcase their solutions – Stay tuned!
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Leading Point FM Shortlisted For Data Management Insight Awards

Leading Point Financial Markets has been shortlisted for the A-Teams Data Management Insight Awards.

Data Management Insight Awards, now in their seventh year, are designed to recognise leading providers of data management solutions, services and consultancy within capital markets.

Leading Point has been nominated for four categories:

  1. Most Innovative Data Management Provider
  2. Best Data Analytics Solution Provider
  3. Best Proposition for AI, Machine Learning, Data Science
  4. Best Consultancy in Data Management

View the short list of our competition. 

 

 

Areas of Outstanding Service & Innovation

Leading Form Index: Data readiness assessment, created by Leading Point FM, which measures firms data capabilities and their capacity to transform across 24 unique areas. This allows participating firms to understand the maturity of their information assets, the potential to apply new tech (AI, DLT) and benchmark with peers.

Chief Risk Officer Dashboard: Management Information Dashboard that specifies, quantifies, and visualises risks arising from firms’ non-financial, operational, fraud, financial crime, and cyber risks.

Leading Point FM ‘Think Fast’ Application: The application provides the ability to input use cases and solution journeys and helps visualise process, systems and data flows, as well as target state definition & KPI’s. This allows business change and technology teams to quickly define and initiate change management.

Anti-Financial Crime Solution: Data centric approach combined with Artificial Intelligence technology reimagines and optimises AML processes to reduce volumes of client due diligence, reduce overall risk exposure, and provide the roadmap to AI-assisted automation.

Treasury Optimisation Solution: Data content expertise leveraging cutting edge DLT & Smart Contract technology to bridge intracompany data silos and enable global corporates to access liquidity and efficiently manage finance operations.

Digital Repapering Solution: Data centric approach to sourcing, management and distribution of unstructured data combined with NLP technology to provide roadmap towards AI assisted repapering and automated contract storage and distribution.

Leading Form Practical Business Design Canvas: A practical business design method to describe your business goals & objectives, change projects, capabilities, operating model, and KPI’s to enable a true business-on-a-page view that is captured within hours.

ISO 27001 Certification - Delivery of Information Security Management System (ISMS) & Cyber risk mitigation with a Risk Analysis Tool

 


24th September: Leading Point FM Presenting to AIMA on Practical Challenges of the LIBOR transition

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EVENT: 24th September, 2019

Leading Point FM in partnership with Linklaters, DRS and AIMA are briefing buy-side hedge funds and asset managers on the practical challenges they face in the transition away from LIBOR at an AIMA membership briefing.

Interbank offered rates (IBORs) play a central role in financial markets and act as reference rates to hundreds of trillions of dollars in notional of derivatives and trillions of dollars in bonds, loans, securitizations and deposits.

The FCA will no longer seek require banks to submit quotes to the London Interbank Offered Rate (LIBOR) – LIBOR will be unsupported by regulators come 2021, and therefore, unreliable. The rate is referenced by over $350trillion of existing financial products. It is instrumental in the derivatives, credit and bond markets as well as being embedded in modelling and accounting systems. LIBOR’s replacement is the largest task the financial markets have ever faced - the clock is ticking.

Please join Leading Point FM and market experts from a wide range of disciplines to discuss the challenges of the cessation of LIBOR.:
- The regulatory backdrop to LIBOR’s demise
- The size and scope of the challenge
- The new risk-free rate replacements
- The practical challenges and opportunities posed by the end of LIBOR

This event is open to AIMA members only. Please contact AIMA here: https://www.aima.org/events.html

 
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Speakers -

Nick Railton Edwards - Head of Research, DRS

Mark Brown - Derivatives and Structured Products Partner, Linklaters

Rajen Madan – Founder & CEO, Leading Point Financial Markets
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Artificial Intelligence & Anti-Financial Crime

Leading Point Financial Markets recently hosted a roundtable event to discuss the feasibility of adopting Artificial Intelligence (AI) for Anti-Financial Crime (AFC) and Customer Lifecycle Management (CLM).

A panel of SMEs and an audience of senior execs and practitioners from 20+ Financial Institutions and FinTechs discussed the opportunities and practicalities of adopting data-driven AI approaches to improve AFC processes including KYC, AML, Payment Screening, Transaction Monitoring, Fraud & Client Risk Management.

“There is no question that AI shows great promise in the long term – it could transform our industry…” Rob Gruppetta, Head of the Financial Crime Department, FCA, Nov 2018

EXECUTIVE SUMMARY

AFC involves processing and analysing vast volume and variety of data; it’s a challenge to make accurate & timely decisions from it.

Industry fines, increasing regulatory requirements, a steep rise in criminal activities, cost pressures and legacy infrastructures is putting firms under intense pressure to up their game in AFC.

90% expressed the volume and quality of data as a top AFC/CLM challenge for 2019.

Applying standards to internal data and client documents were deemed as quick wins to improving process

80% agreed that client risk profiling and the analysis across multiple data sources can be most improved - AI can improve KPI’s on False Positives, Client Risk, Automation & False Negatives.

While the appetite for AI & Machine Learning is increasing but firms need to develop effective risk controls pre-implementation

Often the end to end process is not questioned; firms need to look beyond the point tech, and define the use case for value

Illuminating anecdotes shared on how to make the business case for AI/ Tech. Business, AFC Analysts and Ops have different needs

Firms face a real skills gap in order to move from a traditional AFC approach to an intelligent-data led one. Where are the teachers?

60% of respondents had gone live with AI in at least one business use-case or were looking to transition to an AI-led operating model

AI & Anti-Financial Crime 

Whether it is a judgement on the accuracy of a Client’s ID, an assessment of the level of money laundering risk they pose, or a decision on client documentation, AI has the potential to improve accuracy and speed in a variety of areas of the AFC and CLM process.

AI can help improve speed and accuracy of AFC client verification, risk profiling, screening and monitoring with a variety approaches. The two key ways AI can benefit AFC are:

  • Process automation – AI can help firms in taking the minimum number of steps and the data required to assemble a complete KYC file, complete due diligence, and to assign a risk rating for a client
  • Risk management – AI can help firms better understand and profile clients into micro-segments, enabling more accurate risk assessment, reducing the amount of false positives that firms have to process

Holistic examination of the underlying metadata assembled and challenging AI decisions will be necessary to prevent build up of risk and biases

Mass retraining will be necessary when AI becomes more integral to businesses

KYC / Customer Due Diligence (CDD)

Key challenge: How can anti-money laundering (AML) operations be improved through machine learning?

Firms’ KYC / CDD processes are hindered by high volumes of client documentation, the difficulty in validating clients’ identity and the significant level of compliance requirements

AI can link, enrich and enhance transactions, risk and customer data sets to create risk-intelligence allowing firms to better assess and predict clients’ risk rating dynamically and in real-time based on expected and ongoing behaviour - this improves both the risk assessment and also the speed of onboarding

AI can profile clients through the use of entity resolution which establishes confidence in the truth of the clients identity by matching them against their potential network generated by analysis of the initial data set provided by client

Better matches can be predicted by deriving additional data from existing and external data sources to further enhance scope & accuracy of client’s network

The result is a clear view of the client’s identity and relationships within the context of their environment underpinned by the transparent and traceable layers of probability generated by the underlying data set

 

To improve data quality, firms need to be able to set standards for their internal data and their client’s documentation

 

82% of respondents cited ‘Risk Analysis & Profiling’ as having the most opportunity for improvement through AI

 

If documentation is in a poor state, you've got to find something else to measure for risk – technology that provides additional context is valuable

 

Transaction Screening

Key pains faced by firms are the number of false positives (transactions flagged as risky that are subsequently found to be safe), the resulting workload in investigating them, as well as the volume of ‘false negatives’ (transactions that are flagged as risky, but released incorrectly)

AI can help improve the accuracy and efficiency of transaction and payment screening at a tactical and strategic level

Tactically, AI can reduce workload by carrying out the necessary checks and transactions analysis. AI can automate processes such as structuring of the transaction, verification of the transaction profile and discrepancy checks

Strategically, AI can reduce the volume of checks necessary in the first place by better assessing the client’s risk (i.e., reducing the number of high risk clients by 10% through better risk assessment reduces the volume of investigatory checks).

AI can assist in automating the corresponding investigative processes, which are currently often highly manual, email intensive with lots of to-and-fro.

 

A ‘White List’ of transactions allows much smoother processing of transactions compared to due diligence whenever a transaction is flagged

 

82% of respondents cited ‘Risk Analysis & Profiling’ as a key area that could be most improved by AI applications

 

Transaction Monitoring

Firms suffer from a high number of false positives and investigative overhead due to rules-based monitoring and coarse client segmentation

AI can help reduce the number of false positives and increase the efficiency of investigative work by allowing monitoring rules to target more granular types of clients (segments), updating the rules according to client’s behaviour, and intelligently informing investigators when alerts can be dispositioned.

AI can expand the list of features that you can segment clients on (e.g. does a retailer have an ATM on site?) and identify the hidden patterns that associate specific groups of clients (e.g., Client A, an exporter, is transacting with an entity type that other exporters do not). It can use a firm’s internal data sources and a variety of external data sources to create enriched data intelligence.

Reinforcement learning allows firms to adjust their own algorithms and rules for specific segments of clients and redefine those rules and thresholds to identify correlations and deviations, so different types of clients get treated differently according to their behaviour and investigative results

 

Survey Results

90% of respondents to Leading Point FM’s survey on AI and Anti-Financial Crime cited ‘Volume & Quality of Data’ as being one of the top 3 biggest challenges for CLM and AFC functions in 2019

82% of respondents to cited ‘Risk Analysis & Profiling’ as having the most opportunity for improvement through AI

60% of respondents had gone live with Artificial Intelligence in at least one business use case or were looking to transition to an AI-led operating model.

However, 40% were unclear on what solutions were available 60% of respondents cited ‘Immaturity of Technology’ or ‘Lack of Business Case’ as the biggest obstacle to adopting AI applications

Conclusion

To apply AI practically requires an understanding of the sweet spot between automation and assisting, leveraging human users’ knowledge and expertise

AI needs a well-defined use case to be successful as it can’t solve for all KYC problems at the same time. In order to deliver value, clarity on KPI’s that matter and reviewing AI considering the end-to-end business process is important.

Defining the core, minimal data set needed to support a business outcome, meet compliance requirements, and enable risk assessment will help firms make decisions on what existing data collection processes/ sources are needed, and where AI tech can support enrichment. It is possible to reduce data collection by 60-70% and significantly improve client digital journeys.

There are significant skills gaps in order to move from a traditional AFC op model to more intelligent-data AI led one. When AI becomes more integral to business, mass re-training will be necessary. So, where are the teachers?

The move from repetitive low value-added tasks to more intelligent-data based operating models. Industry collaborations & standards will help, but future competitive advantage will be a function of what are you doing with data that no one else is.

70% of respondents cited ‘Effort. Fatigue & False Positives’ as one of the top 3 biggest challenges for CLM and AFC functions in 2019?

 

More data isn’t always better. There is often a lot of redundant data that is gathered unnecessarily from the client.

 

Spotting suspicious activity via network analysis can be difficult if you only have visibility to one side of the transactions

 

If there's a problem worth solving, any large organisation will have at least six teams working on it – it comes down to the execution

 


The Data Kitchen: From Ingredients to Recipe

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We had an excellent turn out on Tuesday to Leading Point FM's inaugural Data Kitchen event!

Practitioners from organisations such as: 10X Banking, LSE, Brevan Howard, Scotiabank, Legal & General, Liberum, Zercuity, Kings College, Oxford, Barclays, JPMorgan, Fundscape, Deutsche Bank, Nomura, Adjoint, Citi, UBS, IHS Markit, Consilience, LHV Bank, Capital on Tap.

We thought our panellist ‘chefs’ brought out some brilliant insights from their experiences on how to build a personal brand in their careers as entrepreneurs, data leaders, innovators, VC and business executives.

‘The Recipe’ for building your personal brand in the rapidly evolving data landscape in financial services is:

  1. Delivery – People associate you with the outcomes you deliver and your ability to help others meet their goals and commitments.
  2. Use data to support ‘the mission’ – One of the biggest weaknesses that face professionals regarding data is the ability to tell a story around what it *really* means to their audience.
  3. Communicate – Communicate with relevant stakeholders in business terms and relate the data to the business’ pain or gain.
  4. Focus on the end-user/client – Ultimately, they are the arbiter of your success
  5. Do what you enjoy! - Confidence and passion come from finding what you are good at and success will follow.
  6. Find your ‘quirk’ – Embrace the thing that makes you different. People remember your quirks and respect authenticity.
  7. Balance ‘Fail fast’ with perseverance – People shouldn’t apply ‘fail fast’ mentality to building a bridge. Some things require perseverance, planning, problem solving and delivery.
  8. Experimentation – Knowing which skills and roles fit you best is a matter of trial and error. Take on a variety of roles and see which fits best. You’ll grow in skills and capabilities. Always up-skill and re-skill as the situation and market changes.

We had plenty of ideas from the community on topics, games and live solutions for the next Data Kitchen - Watch this space!

Register interest for the October Session here: https://bit.ly/2Yx5t7T

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The Data Kitchen: Data - A Key Ingredient For Your Personal Brand

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Data - A key Ingredient for Your Personal Brand.

 

Data, Data, Data. Whether it's 'Big', 'Structured', 'Personal' or 'Meta', in a lake, silo or vault - More data was created in the last 5 years than in the entirety of human history. Whether it’s on your smartphone, excel, social media or tableau, people are interacting with more and more data every day.

Financial services and Fintechs are actively looking at ways to be more data-led businesses, unlock revenue from their data, better support their client journeys, meet regulatory requirements and manage the risks and liabilities involved in handling the sheer volume and variety of data these days. What’s important and what’s not? How do you distinguish yourself from the crowd? How do you build a career in data-led businesses?

Come to the Data Kitchen for an informal, non-technical discussion with experienced financial services and fintech professionals on how they have practically delivered business outcomes using data as an asset, and how they have grown their personal brand and career with data.

Why should you come?

  • Learn from experienced FS practitioners about how they have delivered business initiatives with data as an asset
  • Share ideas on how you can position yourself in the dynamic world of data
  • Network with like-minded people from FS, Fintech, VC’s, and Data-Innovators and gain insights on career paths

Whether you are a recent graduate, a businessperson, a technologist, a data scientist or just work on data initiatives, come along to meet like-minded people.

 

Participants include: 

 

Peter Krishnan | JPMorgan

Ieva Elvyra Kazakeviciute | Revolut

Milan Kutmutia | Deutsche Bank

Rajen Madan | Leading Point Financial Markets

 

Introducing The Data Kitchen

 

Food | The Kitchen is where people gather to eat, drink and spend time with family. But it is also a place of work. You can do both at the Data Kitchen.

Data | The Data Kitchen is a community of people interested in, or working with, data in Financial Services. Every event focuses on a different theme related to data as an asset or data as a liability and related innovative topics within Financial Services.

Community | We aim to provide a warm, conversational atmosphere to share ideas, learn and network over drinks and hot food. Our events are free and open to everyone.

Insight | The events are a great opportunity to listen to fascinating insight on the modern developments in data-innovations, AI, DLT in the industry through experiences of FS and Fintech professionals.

Tickets are available on a 1st come, 1st basis.

 

Future Events

 

September 2019 Data is brewing

October 2019 Hester Blumenthal or Hairy Biker - Does data need 'science'?

November 2019 Data & Risk: Have you left the stove on?

January 2020 Burrito vs Pastry chef - Does data need to be fancy?

February 2020 Farm to table for Data - How important are your data sources?

March 2020 Data Lasagne – Many cheesy layers?

April 2020 The Data Practitioners Cookbook

 
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Falsely Positive - Event Highlights

 

Leading Point Financial Markets hosted a roundtable event to discuss the feasibility of adopting Artificial Intelligence (AI) for Anti-Financial Crime (AFC) and Customer Lifecycle Management  (CLM). A panel of SMEs and an audience of senior execs and practitioners from 20+ Financial Institutions and FinTechs undertook a detailed discussion on the opportunity and practicality of adopting data-driven AI approaches to solve business issues AFC business issues.

The discussion centred AI solutions’ feasibility within 3 key AFC process examples, Customer Due Diligence (CDD), Transaction Screening & Transaction Monitoring. Participants attending included: Financial Conduct Authority, JP Morgan, HSBC, Deutsche Bank, Credit Suisse, Morgan Stanley, Barclays, BAML, UBS, Santander, CBA, as well as the Financial Times and a variety of challenger FinTechs.

We’ll be releasing a report of the event, including survey results of the audience, over the next few weeks – so watch this space. If you weren’t able to attend and would like a copy of the report – please take our survey and leave your email address here - https://lnkd.in/dt-Tgcp