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.

 


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."

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"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."

[/et_pb_text][et_pb_text disabled_on="on|on|off" _builder_version="4.4.8" min_height="15px" custom_margin="452px||133px|||" custom_padding="8px|||||"]

"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."

[/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|||||"]

"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.

[/et_pb_blurb_extended][/et_pb_column][et_pb_column type="1_3" _builder_version="4.4.8"][et_pb_blurb_extended title="Accelerating the collection of ESG metrics using AI" use_icon="on" font_icon="%%389%%" icon_color="#ffffff" use_icon_font_size="on" icon_font_size="39px" icon_hover_color="#17a826" style_icon="on" icon_shape="use_circle" use_shape_border="on" shape_border_color="#ffffff" shape_border_hover_color="#17a826" title_hover_color="#17a826" _builder_version="4.4.8" header_text_align="left" header_text_color="#ffffff" header_font_size="17px" read_more_icon="%%20%%" text_orientation="center" custom_margin="5px|1px|5px|1px|false|false" custom_padding="0px|0px|0px|0px|false|false" animation_style="fade" locked="off"]

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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Contact Us

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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.

 


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.


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

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

ORX, The operational risk management association

 

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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).

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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.

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"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"

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

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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.

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row column_structure="1_3,1_3,1_3" _builder_version="3.25"][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][et_pb_blurb_extended title="Nick Fry | Strategy & Post-trade SME" blurb_layout="flipbox" fb_front_background="image" fb_front_background_image="https://leadingpointfm.com/wp-content/uploads/2020/04/Nick-white.jpg" fb_back_background="image" fb_back_background_image="https://leadingpointfm.com/wp-content/uploads/2020/04/Nick-Fry-BW-1.jpg" admin_label="BIO - Nick Fry" module_class="teammember" _builder_version="4.3.4" header_font="||||||||" text_orientation="center" background_layout="dark" link_option_url="#linkedin" locked="off"]

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

 
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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.

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

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

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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.

[/et_pb_text][et_pb_text _builder_version="4.3.4" min_height="15px" custom_margin="||100px|||" custom_padding="206px|||||"]

“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.”

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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.

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row column_structure="1_3,1_3,1_3" _builder_version="3.25"][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][et_pb_team_member name="Mitchell Robertson" position="Exchange Traded Derivatives SME. " image_url="https://leadingpointfm.com/wp-content/uploads/2020/03/Mitch.png" _builder_version="4.3.4" inline_fonts="Sarabun"]

Project Manager/BA, User Training and Development

Skilled in Trading, Broking, Futures, Options and Cash Equities.

Experience with both Buy-side and Sell-side.

 

 

 
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Change delivery professional over 17 years’ hands on experience in helping organisations deliver complex trading, market data, efficiency and compliance solutions. 

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Legal Risk: Too big to manage?

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

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“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.”

 

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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.

 

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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  

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

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row column_structure="1_3,1_3,1_3" _builder_version="3.25"][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][et_pb_team_member name="Meredith Gibson" position="Leading Point Financial Markets" image_url="https://leadingpointfm.com/wp-content/uploads/2019/05/meredith.jpg" _builder_version="4.3.4" inline_fonts="Sarabun"]

Senior regulatory lawyer with over 20 years’ experience in providing advice to a range of business areas in global banks. Content specialist and problem solver with expertise in regulatory change and legal programmes across a broad cross-section of EU regulatory initiatives, including MiFID, SFTR, MAR, PRIIPs, BRRD and shadow banking. Practical experience in legal, operational risk and technology solutions. Regular speaker at regulatory, operational risk and data management conferences. Solicitor of the Supreme Court of England and Wales.
[/et_pb_team_member][/et_pb_column][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][et_pb_team_member name="Alaric Gibson" position="Leading Point Financial Markets" image_url="https://leadingpointfm.com/wp-content/uploads/2019/05/alaric.jpg" _builder_version="4.3.4" inline_fonts="Sarabun"]

Regulatory 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.
[/et_pb_team_member][/et_pb_column][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][/et_pb_column][/et_pb_row][/et_pb_section]


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

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

[/et_pb_text][et_pb_text _builder_version="4.3.4" custom_padding="0px||19px|||"]

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.

[/et_pb_text][et_pb_text _builder_version="3.27.4" min_height="15px" custom_padding="206px|||||"]

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

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row column_structure="1_3,1_3,1_3" _builder_version="3.25"][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][et_pb_team_member name="Meredith Gibson" position="Leading Point Financial Markets" image_url="https://leadingpointfm.com/wp-content/uploads/2019/05/meredith.jpg" _builder_version="4.3.4" inline_fonts="Sarabun"]

Senior regulatory lawyer with over 20 years’ experience in providing advice to a range of business areas in global banks. Content specialist and problem solver with expertise in regulatory change and legal programmes across a broad cross-section of EU regulatory initiatives, including MiFID, SFTR, MAR, PRIIPs, BRRD and shadow banking. Practical experience in legal, operational risk and technology solutions. Regular speaker at regulatory, operational risk and data management conferences. Solicitor of the Supreme Court of England and Wales.
[/et_pb_team_member][/et_pb_column][et_pb_column type="1_3" _builder_version="3.25" custom_padding="|||" custom_padding__hover="|||"][et_pb_team_member name="Alaric Gibson" position="Leading Point Financial Markets" image_url="https://leadingpointfm.com/wp-content/uploads/2019/05/alaric.jpg" _builder_version="4.3.4" inline_fonts="Sarabun"]

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

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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.
The next Data Kitchen – ‘Innovative Data-Tech Start-Ups To Watch’ will be on the 22th April 2020!
Register here: https://www.eventbrite.co.uk/e/the-data-kitchen-innovative-data-tech-start-ups-to-watch-tickets-96061391207
[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row column_structure="1_3,1_3,1_3" _builder_version="4.3.4"][et_pb_column type="1_3" _builder_version="4.3.4"][/et_pb_column][et_pb_column type="1_3" _builder_version="4.3.4"][/et_pb_column][et_pb_column type="1_3" _builder_version="4.3.4"][et_pb_team_member name="Alaric Gibson" position="Leading Point Financial Markets" image_url="https://leadingpointfm.com/wp-content/uploads/2019/05/alaric.jpg" _builder_version="4.3.4" inline_fonts="Sarabun"]

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

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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].


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

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

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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.


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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

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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.


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

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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.
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Regulatory 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.
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Leading Point Financial Markets and iManage RAVN are hosting an industry workshop to discuss in more detail some of the issues addressed in this article and understand how smarter Data Management and Enabling Tech Solutions can realistically be used to reduce the cost, risk, and timelines of client outreach and repapering and improve client experience.

 

Industry practitioners can register interest here: https://leadingpointfm.com/event-regulatory-changes-understanding-the-challenge-with-repapering-and-how-to-reduce-the-cost/

This article is the 1st of a new series exploring the role of Legal Technology in Financial Services. Please stay tuned! https://leadingpointfm.com/insights/

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[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/

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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

 


Innovation is Not Perfect. Accept and Embrace It

ThushanThushan Kumaraswamy
Partner at Leading Point Financial Markets

 

It was my pleasure to attend Societe Generale's breakfast event on 9 November 2018 called "Implementing New Technologies" in Spitalfields, London on behalf of Leading Point Financial Markets. The event comprised of presentations about the FinTech innovation landscape and the use of Robotics Process Automation (RPA) in SocGen, followed by a panel discussion, hosted by Susanne Chishti, Founder of FinTech Circle.

Since there was so much good content and thinking at this event, I thought I would share my views on the event and how it ties to our propositions at Leading Point Financial Markets.

Do not ignore FinTech companies that are not 100% ready

There are thousands of FinTech (and RegTech, LegalTech, WealthTech, InsureTech, XYZTech!) companies just in the UK, let alone globally. Many of these are in different stages of their evolution.

Start-up Lifecycle

Source: The Startup Lifecycle

Financial services firms, especially larger firms, often resist adopting innovative technologies from companies who don't have a long record of existing clients. In such a fast-moving environment as FinTechs, this can mean losing out on the potential business benefits at a time when competition is squeezing margins and ever-increasing regulatory pressures are driving up costs.

Imagine being able to run a pilot or proof-of-concept for a small area of the business, with an identified strategy of goals and specific objectives, to demonstrate to the senior management team how such a new technology could be used to deliver real business benefits. This kind of pilot can be run in an agile fashion, but require business and IT teams are fully on-board and involved with the project. Since the scope is small, the resource commitment is also smaller than a normal implementation.

There is a significant opportunity for financial services firms who are willing to start these small-scale projects with innovation companies who might not be 100% ready (in the Validating or Scaling phases above) alongside implementation partners who know the technology, have the domain knowledge and understand operating models.

Don't automate a bad process

Robotics Process Automation (RPA) as a concept is easy enough to understand; computer programs (the "robots" or "bots"), using a set of pre-defined rules replicate what humans would do using computer systems in a repetitive fashion. For example, daily copying of client names from an Excel sheet to a CRM (Customer Relationship Management) system. This basic automation can free up the human workers to do more valuable work.

Rapid evolution of robotics

Source: Robots Join The Team

This is all good stuff. However, before jumping straight to implementing RPA solutions, it is worth considering what the business process is actually doing. Is this Excel-to-CRM method the best way of getting client details into the CRM system? Is it possible to improve the process first? As part of an RPA implementation, you should be looking at process improvement strategies first, then automating what is left. This way, you save on the number of bots you would need and increase the efficiency of the process as a bonus. Process experts can document existing processes and identify opportunities for improvement prior to any RPA technology implementation.

How does a bot change a password when accessing a core system?

There are some potential gotchas when using bots, like the above question, which can cause problems during day-to-day running. If a bot uses a specific login to access a core system and that login has a password expiry, what happens then? Is the bot expected to define a new password? Should a human get involved? Also, consider licences on existing software platforms; are there any clauses that prevent the use of bots? There may not be right now, but it is not difficult to foresee software companies bringing in new clauses to control the potential uptick of system usage through bots.

Panel Discussion: Selecting and Implementing New Technologies

Panel discussion

  • Susanne Chishti, Founder of FinTech Circle (Host)
  • Anthony Woolley, Head of Innovation, Societe Generale
  • Vasu Vasudevan, Digital Enablement Capbility Lead, Schroders
  • Richard Archer, Director, EY
  • Keith Phillips, Executive Director, The Investment Association and Velocity

The first question was about trends in innovation. The guests talked about the bleed of innovation between FinTechs, RegTechs, LegalTechs, but also into manufacturing and other industry sectors. The biggest topics being:

  • Artifical Intelligence (AI) and Machine Learning (ML)
  • Big Data
  • Cloud
  • Distributed Ledger Technology (DLT) / Blockchain
  • Social & Mobile
  • Robotics & Automation

As mentioned above, the twin drivers of competition shrinking margins and regulatory compliance increasing costs are forcing companies to come up with new ways of thinking. This may not come naturally to the larger, older financial services firms. They may have pockets of innovation but sometimes struggle to create a company-wide innovation culture.

Chalkbaord

The importance of customer-centricity was raised to a question on technological advancements. Building a single view of client will enable improved service to clients and increased revenue growth using data analysis across large cross-referenced data sets to be more specific with marketing and cross-selling.

An interesting question about how to bridge the gap between legacy platforms and new innovations was put to the panel next. It was noted that capacity is required to do this. How do companies get that capacity? By using technologies like RPA to free up people to generate this real value for the business.

Another technique is to use APIs (Application Programming Interfaces) as wrappers around your legacy platforms to make them easier to connect to other, more modern, applications. Using APIs turns your legacy platforms into building blocks that be linked together. A COBOL API can let other systems use the data held in the COBOL system, without the need for expensive COBOL programmers.

Intro to APIs

Source: Intro to APIs

This brings additional data protection concerns though, as customer data held in these legacy platforms may not have up-to-date data security and data protection applied to them and exposing the data through APIs could potentially increase risk of data loss.

A concern raised by the panel was about the use of RPA as a concrete sticking plaster rather than as a purely temporary fix for the use of legacy technology. The temptation is there once an RPA solution is doing its work, to leave it there rather than address the legacy platform.

The panel were asked about their top three technologies. The answers covered:

  • Data aggregation, clustering & consolidation
  • AI and ML
  • Blockchain
  • Data analytics (behavioural analysis for active asset management)
  • Digital passports (recording clients' digital identities)
  • Intelligent automation (robotics)
  • Unstructured to structured data
  • Document intelligence (text mining)
  • RPA
  • Collaboration tools in investment operations
  • Natural language processing (voice recognition)
  • Cloud (along with data and APIs)
Emerging Techs

Source: Top 30 Emerging Technologies

One important factor for digital was considering how people interacted with their devices. Many people of a certain age feel comfortable using on-screen keyboards and touch gestures. Some younger people prefer voice interactions through assistants like Alexa, Siri or Google and that audience is only going to grow.

A vital question was put to the panel about how to implement new technologies. FinTechs often feel like they are in a zoo. Potential clients come to see what they can do, have some meetings, but then don't connect again. There are some activities that can improve the relationship-building on both sides for FinTechs trying to scale-up or break into financial services; along with the obvious (but not always followed) things like respecting each other and being collaborative, there is a need to not destroy the start-up's spirit. Go in to the relationship with the understanding that the technology partner is young and may need some support and guidance.

The idea of changing the culture of the financial services firms was discussed. It was believed that this needed both top-down leadership & funding and also bottom-up drive. An internal innovation fund was set up that enabled small teams working on-the-ground to prepare a business case and pitch over six months to present. Over 70 of these teams took up the challenge, with some generating real business benefits. But, it is more than those end success stories that matter; it is the change in mindset across the company that demonstrates that innovating is part of business-as-usual for everyone in the firm, not just a select few tucked away in an innovation lab.

Other key factors were having both business and IT teams engaged and willing to work together as partners, being able to run projects in an agile (or Agile) fashion and accepting projects that "fail fast", but test and learn quickly. It was interesting to see how business architecture could help in these situations by mapping commonalities across the business using capability models and describing roadmaps aligned to customer journeys.

Practical business design

Source: Practical Business Design

One of the major blockers to building an innovation culture was the procurement process in many large financial services firms. These bureaucratic processes can take over eight months to allow a start-up to being implementing a solution, which can destroy the innovation impetus. A fast-track procurement process, enabling implementation of new technologies, perhaps in some protected sandbox environment, taking eight weeks would be a massive enabler. It feels like there is work required to develop streamlined procurement processes, specifically for innovation technologies.

An audience member asked how many start-ups typically fail. In any typical innovation portfolio, an angel investor may have invested in ten start-up companies. Five of these will likely go bust. Three may remain as the "living dead", where they plod along, just existing as a private company, without any hope of getting a return on the investment. The other two may become "superstars", where they go public with a bang and these two pay off the investment in the other eight start-ups.

I believe that, with more help in providing a consistent analysis of these start-ups on behalf of private equity firms and venture capitalists, the ratio of failures:living dead:superstars could be improved.

This was a very interesting panel discussion and my thanks go to Societe Generale for running the event, the guest speakers on the panel & presenting and to Susanne Chishti for hosting. The themes of technological innovations and the challenges of implementing them in financial services were very familiar to what I have seen in my own experience, but these challenges are not insurmountable with the right support.

If you don't use these new innovations in your business, for example in the field of anti-financial crime, where do you think the criminals are going to go when your competitors
do use them?

Final thought: You cannot wait for the perfect innovation. By the time that happens, your competition may be far ahead of you. You would be better off using what innovation can offer now, but work together with the technology companies to complete that picture for your business.

The right partner can help intersect the old world with the new.

#innovation #event #socgen #data #technology #startup #scaleup #financialservices #ai #ml #rpa #robotics #blockchain #bigdata #cloud #fintech #regtech #legaltech #wealthtech #insuretech #implementingnewtechnologies #leadingpointfinancialmarkets #leadingpointfm #lpfm