Legal Risk: Too big to manage?

23/03/2020Blog

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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.
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by Alaric Gibson

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

06/03/2020Blog

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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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by Alaric Gibson

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

05/03/2020Blog

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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
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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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by Alaric Gibson

LIBOR Signals Need for New Approaches to Legal Data

24/02/2020Blog

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 The Scope of LIBOR Remediation is the Problem

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

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

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

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

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

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

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LIBOR Repapering Not a ‘Find and Replace’ 

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

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

Similarly, there’s prudential risk. When the underlying contracts change, firms may find that the instruments they rely on for capital adequacy purposes may no longer be eligible, potentially even resulting in a sudden drop in a bank’s capital position. Similarly, there are several Counterparty Credit, Market, Liquidity, and Interest Rate Risks that will need to be reflected in firms’ approaches.  
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LIBOR is proving to be a real impetus for financial institutions to use technology that, to be honest, has been available in the marketplace for a long time now.

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Mindset Change is Needed to Manage Legal Data

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

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

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

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

Stephanie Vaughan, Global Legal AI Practice Director at iManage RAVN and ex-Allen & Overy, recently observed, “LIBOR is proving to be a real impetus for financial institutions to use technology that, to be honest, has been available in the marketplace for a long time now. While they may have dabbled with it in the past, due to the scale of the LIBOR remediation and the constantly changing regulatory challenges, it has finally hit home that such projects are a drain on resources and are delivering no business value.”
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Financial institutions have started every repapering project (e.g. MiFID II, Dodd Frank, Margin Rules) from scratch including going through the entire process of determining the clients, what the terms of engagement are, when the contracts expire and so on.

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Technology Can Make Repapering ‘Business as Usual’

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

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

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

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

The opportunity with more effective legal data management is huge and realisable. Building and incrementally strengthening capability through the strategic and proactive use of technology is potentially the only way for financial institutions to adapt to their new regulatory and business environment.
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The repapering of contracts isn’t as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR.

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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 1^st of a new series exploring the role of Legal Technology in Financial Services. Please stay tuned! https://leadingpointfm.com/insights/
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by Rajen Madan

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

06/02/2020Blog

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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 1^st 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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by Alaric Gibson

Intersecting the Old World with the New

05/02/2020Blog

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

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

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

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

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

Is it because Upstarts have more skills or able people to execute change?  Probably not, although one must believe Upstart people form a more focused collective.  It’s much simpler than that – it’s a matter of having the time and inclination to apply that collective focus to the achievement of a single objective.  Having, as a sole objective, creating and delivering industry augmenting technology will result in an executable product roadmap and realistic delivery timelines.
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Execution is the biggest differentiator between small, agile and nimble businesses and their much larger counterparts
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However, there is one area in which large corporates have the upper hand: domain expertise.  Upstarts, by virtue of their size, generally do not have the breadth of expertise of larger organisations.  There are many Upstarts who are capable and indeed do produce top of the line tech solutions.  However, often these same single solutions providers (focus!) struggle to appreciate and navigate the vast array of problems large FS organisations are looking to address. Due to these information gaps, solutions can often result in not being fully fit for purpose and therefore hinder an Upstarts ability to precisely satisfy the needs of large FS corporates.

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

While Innovation Labs may ensure large players don’t get left behind, there is a big opportunity being missed.  This is the integration of external innovation with internal processes and capabilities.  Acquisitions should be aligned with internal use cases i.e. known (or guessed at) issues with existing business workflows such as efficiency gains.  The main reason seems to be that each is located in its own silo.
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Having, as a sole objective, creating and delivering industry augmenting technology will result in an executable product roadmap and realistic delivery timelines
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So internal use cases (areas in need of improvement and change) are not connected to potential external innovative solutions.  And this is not to speak of the bigger challenge which is to identify those use cases in the first place.  This raises a number of questions:

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

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

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

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Entrepreneurs, especially the good ones, know that if failure is to happen, it happens fast.  This requires the ability to EXECUTE. 
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The common thread: entrepreneurship. Why?

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

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

We love to talk about this intersection and encourage free and open conversation so please feel free to get in touch to share your thoughts or indeed to hear more of ours.
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To bridge the gap between larger, more conventional-minded organisations and newer Upstarts, one must have the ability to “intersect the old world with the new”
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by Dishang Patel

IR35 & YOU

01/11/2019Blog

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by admin

Leading Point FM Shortlisted For Data Management Insight Awards

01/10/2019Blog

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

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

Leading Point has been nominated for four categories:

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

View the short list of our competition. 

Areas of Outstanding Service & Innovation

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

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

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

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

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

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

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

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

 
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by admin

Artificial Intelligence & Anti-Financial Crime

21/08/2019Blog

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Introduction

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.
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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?
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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

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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

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

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

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

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

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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

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

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

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

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

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

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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

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by Alaric Gibson

LIBOR Transition - Preparation in the Face of Adversity

21/03/2019Blog

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LIBOR TRANSITION IN CONTEXT

What is it?  FCA will no longer seek require banks to submit quotes to the London Interbank Offered Rate (LIBOR) – LIBOR will be unsupported by regulators come 2021, and therefore, unreliable

Requirement: Firms need to transition away from LIBOR to alternative overnight risk-free rates (RFRs)

Challenge: Updating the risk and valuation processes to reflect RFR benchmarks and then reviewing the millions of legacy contracts to remove references to IBOR

Implementation timeline: Expected in Q4 2021
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HOW LIBOR MAY IMPACT YOUR BUSINESS

Front office: New issuance and trading products to support capital, funding, liquidity, pricing, hedging

Finance & Treasury: Balance sheet valuation and accounting, asset, liability and liquidity management

Risk Management: New margin, exposure, counterparty risk models, VaR, time series, stress and sensitivities

Client outreach: Identification of in-scope contracts, client outreach and repapering to renegotiate current exposure

Change management: F2B data and platform changes to support all of the above
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WHAT YOU NEED TO DO

Plug in to the relevant RFR and trade association working groups, understand internal advocacy positions vs. discussion outcomes

Assess, quantify and report LIBOR exposure across jurisdictions, businesses and products

Remediate data quality and align product taxonomies to ensure integrity of LIBOR exposure reporting

Evaluate potential changes to risk and valuation models; differences in accounting treatment under an alternative RFR regime

Define list of in-scope contracts and their repapering approach; prepare for client outreach
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“[Firms should be] moving to contracts which do not rely on LIBOR and will not switch references rates at an unpredictable time”

Andrew Bailey, CEO,
Financial Conduct Authority (FCA)
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“Identification of areas of no-regret spending is critical in this initial phase of delivery so as to give a head start to implementation”

Rajen Madan, CEO,
Leading Point FM

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BENCHMARK TRANSITION KEY FACTS

• Market Exposure - Total IBOR market exposure >$370TN 80% represented by USD LIBOR & EURIBOR
• Tenor - The 3-month tenor by volume is the most widely referenced rate in all currencies (followed by the 6-month tenor)
• Derivatives - OTC and exchange traded derivatives represent > $300TN (80%) of products referencing IBORs
• Syndicated Loans - 97% of syndicated loans in the US market, with outstanding volume of approximately $3.4TN, reference USD LIBOR. 90% of syndicated loans in the euro market, with outstanding volume of approximately $535BN, reference EURIBOR
• Floating Rate Notes (FRNs) - 84% of FRNs inthe US market, with outstanding volume of approximately $1.5TN, reference USD LIBOR. 70% of FRNs in the euro market,with outstanding volume of approximately $2.6TN, reference EURIBOR
• Business Loans - 30%-50% of business loans in the US market, with outstanding volume of approximately $2.9TN, reference USD LIBOR. 60% of business loans in the euro market, with outstanding volume of approximately $5.8TN, reference EURIBOR

*(“IBOR Global Benchmark Survey 2018 Transition Roadmap”, ISDA, AFME, ICMA, SIFMA, SIFMA AM, February 2018)
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by admin

Event: Falsely Positive - Is AI the Silver Bullet for Anti-Financial Crime?

09/03/2019Blog

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ADDRESSING THE AFC BUSINESS CHALLENGES

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Firms are facing huge pressure to improve their Anti-Financial Crime (AFC) capabilities in 2019 across fraud, cyber, AML, sanctions, data security, ABAC.

The combination of new and evolving regulation, firms’ operational complexity and increases in cyber crime have led to dissatisfied clients, poor risk management, massive compliance costs and increased competition from challenger banks.

This situation is only getting worse as shortage of expertise, cultural resistance to change, and depleted internal resources create barriers to digital transformation in a fragmented solutions marketplace.

Maturing Artificial Intelligence (AI) technology is being positioned as ‘the answer’ - some estimating it can reduce costs in AFC by as much as 47%.*

*Autonomous, April 2018, “Machine Intelligence & Augmented Finance”
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 “There is no question that AI shows great promise in the long term – it could transform our industry…”

Rob Gruppetta,
Head of Financial Crime, Financial Conduct Authority (FCA)
Nov 2018
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HOW CAN DATA-DRIVEN AI APPROACHES HELP?

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[AI] has the potential to slash the costs of the [regulatory] challenge … by reducing false positives in monitoring systems and redirecting the efforts of human experts to other, more productive, areas

World Economic Forum,
Jan 2019
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What outcomes do organisation stakeholder groups seek from their Client Journey, Risk Management and AFC Operating Models?

Business: Reduce onboarding and maintenance bottlenecks to accelerate timelines and improve client journeys, enable data-driven granular understanding of clients.

COO & CTO: Improve the efficiency, accuracy, and adaptability of screening and transaction monitoring workflows to provide efficiency gains and improved KPIs.

Regulatory & Compliance: Automate governance of complex models and reporting tools to support regulatory review and put compliance in the front-line

Risk Management: Segment clients according to contextual and transactional behaviour to better evaluate emerging AFC threats and improved risk thresholds
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HOW CAN FIRMS GRASP THE AI OPPORTUNITY?

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How can organisations grasp the AI opportunity? Is AI a Silver Bullet or a Red-Herring?

What best practices and practical implementation insights are available for organisations to up their game in client digital journeys, risk management & AFC?

An executive workshop of leaders & practitioners from Business, CIO, COO, AFC and Change will assess the opportunity of adopting data-driven AI approaches and discuss practical ways to solve business issues related to AML / AFC. Whether you are an AI skeptic, evangelist or pragmatist, attend this session to:

• Understand AI and how it relates to AFC, Client Journey & Risk Management
• See 3 core business use cases of AI in action with live solutions
• Understand how to structure the implementation journey & pitfalls to avoid

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1. Understand the business challenges & where you can up your game in AFC?

2. Live solutions: 3 core AFC business use cases with AI

3. How to remove barriers & implement with success
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by admin

Innovation is Not Perfect. Accept and Embrace It

10/01/2019Blog

Thushan 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.

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.

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

• 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.

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.

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)

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.

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

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by Thushan Kumaraswamy

How will the FCA business plan impact organisations over the next two years?

04/12/2018Blog

Leading Point of View
How will the FCA business plan impact organisations over the next two years?

Introduction

The FCA has recently issued its business plan (1) and focus for the upcoming four quarters. Kicking off with some stats – a mix of sobering and positive, the paper gives a clear outline of its proposed, cross-sector, regulatory oversight. One of the greatest challenges for the industry at present is the implementation of MiFID II provisions.
The FCA makes the point that this will facilitate the introduction of ‘major reforms to improve resilience and strengthen integrity and competition in wholesale markets’. Furthermore, work around market abuse will be enhanced. We highlight notable elements of the business plan and their implications for organisations, below.

Cybersecurity

Across all financial sectors lies the risk of cyber-attacks. With the impending implementation and governance of the General Data Protection Regulation, and potential fines of up to 4% of company revenue, organisations’ technological and operational resilience must be second to none. The FCA deems these qualities pivotal pieces of the cyber security jigsaw; it aims to police cyber capabilities and monitor financial crime and all major outages
during the upcoming year.

Senior Managers and Certification Regime

Whilst 2015/2016 saw banks and insurers bring about the operational changes borne out of SMCR, during 2017/2018, the FCA plans to oversee the resulting culture and governance of this significant shift in responsibility. Currently under consultation is the extension, to be implemented by 2018, of SMCR to all firms covered by FSMA. This would cement the prevailing accountability of senior managers’ individual areas of business within the industry.

Customer Engagement & Competition

The theme driving the most recent directives and regulations is placing the ball in the customers’ court. The dramatically changing financial landscape is being molded by the General Data Protection Regulation, the Payment Services Directive 2, to name but a few. The Open API world further allows the customer to have greater choice and engagement with their banking decisions. The FCA is likely to zero in on firms’ development in digitisation and automation and stewardship of customer data with a critical eye, to ensure there is no abuse.

Buy-side | Asset Management

MiFID II implications are beginning to take shape, however there is much to be done. The FCA recognises MiFID II as post-crisis regulation; it is driving reforms that will promote cross-sector market integrity and competition,
and consumer protection. Firms’ annual budgets will now, more than ever, be targeted towards improving IT systems and infrastructure, develop data capabilities, and ensure operational risk is kept at bay.

 

Leading Point Financial Markets brings compelling value at the intersection of Data, Governance & Compliance, and Digital and Operating Model Change initiatives. If you would like to further consider any of these impacts on your organisation, please contact saskia.blake@leadingptconsulting.com or rajen.madan@leadingptconsulting.com.

(1) https://www.fca.org.uk/publications/corporate-documents/our-business-plan-2017-18

 

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by Rajen Madan