Improving data access controls at a global insurer
"We approached Leading Point to support the enhancement of strategic data lake fine grained access controls capabilities. Their partnership approach working transversally across business and IT functions quickly surfaced root causes to be addressed as part of the improvement plan. Leading Point's approach to consulting services was particularly refreshing from a quality and cost stand point compared to some of the traditional players that we had consulted with before."
Head of Data Controls at Global Corporate Insurer
Helping Adjoint gain ISO 27001 information security certification to support its expansion strategy
Adjoint required ISO certification to comply with legislation, across multiple jurisdictions, and increase confidence in their brand. Due to the nature of their clients (fortune 500 and international companies), a widely recognised accreditation was required. The firm's incorporation of next generation processing, such as distributed ledger technology (DLT), increased the complexity to achieve certification. Their global teams in the UK, Switzerland and USA, were undergoing a heavy scaling-up.
We were asked to customise and implement an ISO 27001 framework for global accreditation in IT security management.
Our approach:
- Capture delivery requirements
- Create relevant policies, procedures and a controls framework, for applicable IT functions
- Perform gap analysis and risk assessment
- Establish clear roles and responsibilities and deliver a formal training program
- Conduct internal assurance audit to identify incidents and data breaches
- Lead external certification process with BSI, through Stage 1 and 2 completion
- Provide agile delivery through to completion
Our results:
- Effective coverage of all ISMS mandatory requirements surrounding ISO 27001
- A new performance management system to track controls in company processes, structure and focal points
- Global delivery, with clear road-mapping structure
- Scaled offerings in open APIs and raised brand in the market
- Improved sales process due to meeting client ISO requirements
Helping Adjoint, a DLT FinTech, with agile delivery management services to increase sales at pace
Adjoint required an experienced delivery partner to run technical delivery and build and manage client relationships, as well as create a scalable delivery model. They lacked a scalable platform and struggled to educate prospects and clients on the misconceptions between the benefits of DLT versus the noise created by other solutions.
We were asked to be the client and delivery partner, to deliver DLT solutions to fortune 50 clients, including tier 1 banks, insurers, and multinational corporations. The client wanted a scalable platform to manage internal and external work-streams, as well as internal and client resource prioritisation, to ensure better alignment of the product delivery team.
Our approach:
- Structured approach; using an Agile framework to deliver successful client PoCs and projects, whilst balancing PM, BA, Testing and DevOps deliverables
- Collaborative style; seamlessly adding capabilities and bringing delivery assets to the fore, through a low-risk delivery model, with a focus on outcomes
- Hands-on attitude; unravelling DLT, whilst enabling concrete application in treasury, captive insurance, inter-company lending, and securitisation, ensuring common messaging across clients
Our deliverables:
- Business requirements documents (BRDs)
- Testing artefacts
- Quick reference guides (QRGs)
- Support model
- Security policy
- Project plans
- Issue tracker
- Task management
Business benefits:
- Scalable, commercially attractive, and low-risk delivery model
- Optimisation of internal and external resource
- Market-ready DLT solutions with short term delivery timelines
- Recognised as an industry partner to work on value-add business use cases for DLT
- Senior stakeholder management (internal and external)
Helping Clarivate Analytics define a financial services (FS) go-to-market strategy for intellectual property data
We were asked by Clarivate to analyse their IP data and identify where it might be useful in financial services, based on our industry experience. We created and reviewed 39 use cases, interviewed 59 financial services specialists, and reviewed 150 potential partner companies.
We developed four value propositions and recommended 16 projects to execute the strategy.
Helping ARX, a cyber-security FinTech with interim COO services to scale-up their delivery
We were engaged by ARX to provide an interim COO as they gaining traction in the market and needed to scale their operations to support their new clients. We used our financial services delivery experience to take on UX/UI design, redesign their operational processes for scale, and be a delivery partner for their supply chain resilience solution.
Due to our efforts, ARX were able to meet their client demand with an improved product and more efficient sales & go-to-market approach.
Helping a global consultancy define & execute its UK FinTech Strategy
Our client had developed 39 FinTech value propositions and we were asked to assess the propositions and prioritise when, and how, to go to market. We used our financial services experience and FinTech network to plan the best approach, through outreach, warm introductions, and events.
Our approach led to successful introductions with new prospect FinTechs in payments, neo-banks, and crypto firms within four months.
Improving a DLT FinTech's operations enabling rapid scaling in target markets
"Leading Point brings a top-flight management team, a reputation for quality and professionalism, and will heighten the value of [our] applications through its extensive knowledge of operations in the financial services sector."
Chief Risk Officer at DLT FinTech
Developing a GTM strategy at a large alternative data provider to break into new financial services markets
"Leading Point’s delivery has been head and shoulders above any other consultancy I have ever worked with."
SVP Large Alternative Data Provider
AI in Insurance - Article 1 - A Catalyst for Innovation
How insurance companies can use the latest AI developments to innovate their operations
The emergence of AI
The insurance industry is undergoing a profound transformation driven by the relentless advance of artificial intelligence (AI) and other disruptive technologies. A significant change in business thinking is gaining pace and Applied AI is being recognised for its potential in driving top-line growth and not merely a cost-cutting tool.
The adoption of AI is poised to reshape the insurance industry, enhancing operational efficiencies, improving decision-making, anticipating challenges, delivering innovative solutions, and transforming customer experiences.
This shift from data-driven to AI-driven operations is bringing about a paradigm shift in how insurance companies collect, analyse, and utilise data to make informed decisions and enhance customer experiences. By analysing vast amounts of data, including historical claims records, market forces, and external factors (global events like hurricanes, and regional conflicts), AI can assess risk with speed and accuracy to provide insurance companies a view of their state of play in the market.
Data vs AI approaches
This data-driven approach has enabled insurance companies to improve their underwriting accuracy, optimise pricing models, and tailor products to specific customer needs. However, the limitations of traditional data analytics methods have become increasingly apparent in recent years.
These methods often struggle to capture the complex relationships and hidden patterns within large datasets. They are also slow to adapt to rapidly-changing market conditions and emerging risks. As a result, insurance companies are increasingly turning to AI to unlock the full potential of their data and drive innovation across the industry.
AI algorithms, powered by machine learning and deep learning techniques, can process vast amounts of data far more efficiently and accurately than traditional methods. They can connect disparate datasets, identify subtle patterns, correlations & anomalies that would be difficult or impossible to detect with human analysis.
By leveraging AI, insurance companies can gain deeper insights into customer behaviour, risk factors, and market trends. This enables them to make more informed decisions about underwriting, pricing, product development, and customer service and gain a competitive edge in the ever-evolving marketplace.
Top 5 opportunities
1. Enhanced Risk Assessment
AI algorithms can analyse a broader range of data sources, including social media posts and weather patterns, to provide more accurate risk assessments. This can lead to better pricing and reduced losses.
2. Personalised Customer Experiences
AI can create personalised customer experiences, from tailored product recommendations to proactive risk mitigation guidance. This can boost customer satisfaction and loyalty.
3. Automated Claims Processing
AI can automate routine claims processing tasks, for example, by reviewing claims documentation and providing investigation recommendations, thus reducing manual efforts and improving efficiency. This can lead to faster claims settlements and lower operating costs.
4. Fraud Detection and Prevention
AI algorithms can identify anomalies and patterns in claims data to detect and prevent fraudulent activities. This can protect insurance companies from financial losses and reputational damage.
5. Predictive Analytics
AI can be used to anticipate future events, such as customer churn or potential fraud. This enables insurance companies to take proactive measures to prevent negative outcomes.
Adopting AI in Insurance
The adoption of AI in the insurance industry is not without its challenges. Insurance companies must address concerns about data quality, data privacy, transparency, and potential biases in AI algorithms. They must also ensure that AI is integrated seamlessly into their existing systems and processes.
Despite these challenges, AI presents immense opportunities. Insurance companies that embrace AI-driven operations will be well-positioned to gain a competitive edge, enhance customer experiences, and navigate the ever-changing risk landscape.
The shift from data-driven to AI-driven operations is a transformative force in the insurance industry. AI is not just a tool for analysing data; it is a catalyst for innovation and a driver of change. Insurance companies that harness the power of AI will be at the forefront of this transformation, shaping the future of insurance and delivering exceptional value to their customers.
Download the PDF article here.
The Consumer Duty Regulation
Improving outcomes with the Consumer Duty Regulation
How can buy-side retail financial firms improve consumer outcomes and the wider economy?
The FCA introduced new guidelines, rules and policies last year in 2022, comprised as the Consumer Duty Regulation, to ensure products and services are delivered at fair value to customers, as well as a better standard of care. With the recent rise of the cost-of-living crisis, consumers are struggling and are faced with difficult times ahead, including the UK economy. This Duty lays out responsibilities for Boards and senior management within firms, to implement this regulation, to not only benefit consumers, but the wider economy.
In a recent review published by the FCA in January 2023, the FCA identified key areas where firms are meeting obligations, and where areas of improvement are required. As stated in the Policy Statement PS22/9, the FCA would like to see firms make full use of the implementation period of this three-year strategy, to implement the Duty effectively, and that by October 2022, ‘firm’s boards (or equivalent management body) should have agreed their plans for implementing the Duty’ and to have evidenced this, to ‘challenge their plans to ensure they are deliverable and robust’ (Consumer Duty Implementation Plans, FCA, Jan 2023).
This review published by the FCA, helps firms understand the FCA’s expectations, and to work together with firms to ensure the Duty is implemented effectively. The review identified that firms are behind with the implementation of the Duty and need to improve their approach. Three key areas were suggested where firms can focus on for the second half of the implementation period, the first being ‘effective prioritisation of the Duty’ – in order to reduce risk of poor customer outcomes, and to prioritise the implementation plans. The second ‘embedding substantive requirements’, on how firms are over-confident on their plans, and instead should focus on the substantive requirements laid out in the Duty, and review ‘their products and services, communications and customer journeys, they identify and make the changes needed to meet the new standards’ (Consumer Duty Implementation Plans, FCA, Jan 2023). The third area of focus identified was on how firms should work together with other firms, to share information in the distribution chain, to ensure the Duty can be implemented effectively and consistently (Consumer Duty Implementation Plans, FCA, Jan 2023).
What can retail financial firms do to improve and what are the implications of not meeting the Duty requirements?
From the FCA’s recent review, it has been determined there are still many areas by which firms are falling short, which raises the risks of not meeting the Duty obligation deadlines. From the governance aspect, the FCA’s review has established that the board members and senior management teams within firms, have no clearly defined and developed plans in place, neither timings, and lack engagement. When it comes to the plans compiled by firms, the project requirements and timelines are unclear, there is a lack of detail, explanation, and evidence on the implementation of the Duty, including how a firm’s purpose, culture and values are in alignment with the Duty.
Additionally, the review identified that firms also fail to define risks, and internal/external dependencies such as resource planning, budgeting, and technology resources, including working together with third parties, which as a result may impact the implementation plans. Further, firms fail to distinguish mitigation strategies and approaches or methodologies for conducting reviews and gap analysis of products, services, communications, and customer journeys, as part of implementation of the Four Outcomes within the Duty. Firms have also failed to provide in-depth details into the types of data they will require, and how this will be tested, and used, to better understand the customer outcomes, which is another key part of the Duty requirements.
How can Leading Point help to simplify this process?
At Leading Point, our team of expert practitioners can assist the board members and senior managers within retail financial firms, to conduct more in-depth project scope and planning, gap analysis, as well as workflow strategies, and assist to define clear methodologies and approaches to implement the Duty policies and rules. We are fully-equipped to help any organisation that is looking to improve their implementation plans for meeting the Consumer Regulations, to ensure deadlines are met, whilst reducing costs, and risks, with defined mitigation strategies, and enhanced quality of consumer data. This will not only better equip firms with meeting the Duty obligations, but will help to accelerate new business growth, to ensure high-quality products and services are delivered to consumers.
Appendix and Additional Information on the Duty Regulation
What is the Consumer Duty Regulation?
The FCA introduced the Consumer Duty Regulation, and published the Finalised Guidelines FG22/5, along with the Policy Statement PS22/9 in July 2022, which is a ‘standard of care firms should give to customers in retail financial markets’ (FG22/9, p.3).
The FCA states that the purpose of the Consumer Duty (‘the Duty’) is to provide ‘a fairer basis for competition’, to help ‘boost growth and innovation’ (What firms and customers can expect from the consumer duty and other regulatory reforms, FCA (Sept, 2022)).
The Duty is comprised of three key areas: A Consumer Principle; the Cross-Cutting Rules; and the Four Outcomes (FG22/9, p.3). Each of these three key areas focus on how firms should deliver suitable products and services, as well as good outcomes to consumers.
Which firms and who will it impact?
The FG22/5 Guidelines state that the Duty applies ‘across retail financial services’, and that ‘firms should review all examples in this guidance and consider how they may be relevant to their business models and practices’ (FG22/5).
As stated in the FG22/5 Guidance, it is the firms responsibility to identify which rules and principles are applicable to their firm, and ‘what they are required to do’ (FG22/5).
What is the timeline of this Regulation?
It has been proposed for the Duty to be enforced in two-phase implementation periods, the first being by the end of July 2023, whereby the Duty will apply to new and existing products and services that remain for sale or open for renewal, and the second date is by July 2024, whereby the Duty will come fully into force, and will apply to all closed products and services (PS22/9).
The following timeline has been extracted from the Policy Statement – Implementation Timetable (PS22/9):
Implementation Period | Timeline |
Firms’ boards (or equivalent management body) should have agreed their implementation plans and be able to evidence they have scrutinised and challenged the plans to ensure they are deliverable and robust to meet the new standards. Firms should expect to be asked to share implementation plans, board papers and minutes with supervisors and be challenged on their contents. | End of October 2022 |
Manufacturers should aim to complete all the reviews necessary to meet the four outcome rules for their existing open products and services by the end of April 2023, so that they can:
• Share with distributors by the end of April 2023 the information necessary for them to meet their obligations under the Duty (e.g., in relation to the price and value, and products and service outcomes)
| End of April 2023 |
Manufacturers should: • Identify where changes need to be made to their existing open products and services to meet the Duty and implement these remedies by the end of July 2023 | End of July 2023 |
The Duty will apply to all new products and services, and all existing products and services that remain on sale or open for renewal. This gives firms 12 months to implement the new requirements on the bulk of retail financial products and services, benefiting the majority of consumers | End of July 2023 |
The Duty will come fully into force and apply to all closed products and services. This extra 12 months will help those firms with large numbers of closed products and will also help mitigate some of the wider concerns firms raised about the difficulty of applying the Duty to these products (see Chapter 3). | End of July 2024 |
How should firms implement the Consumer Duty Regulation?
According to the Guidance (FG22/5), it is a firm’s responsibility to identify which policies and rules apply and what they will be required to do (FG22/5). In addition to this, the Guidance has dedicated Chapter 10, on the Culture, Governance and Accountability that the Duty sets out for firms to give their customers. This is so that firms shift their focus on customer outcomes, and to ‘review the outcomes of their customers to ensure they are consistent with the Duty’ (PS22/9).
The Guidance (FG22/5) states the following:
- The rules require firms to ensure their strategies, governance, leadership, and people policies (including incentives at all levels) lead to good outcomes for customers. The rules also make clear that we expect customer outcomes to be a key lens for important areas, such as Risk and Internal Audit.
- A firm’s board, or equivalent governing body, should review and approve an assessment of whether the firm is delivering good outcomes for its customers which are consistent with the Duty, at least annually.
- Individual accountability and high standards of personal conduct in firms will ensure that firms are meeting their obligations under the Duty.
The Guidance (FG22/5) outlines four important drivers of culture that firms will need to ensure they deliver on from: Purpose; Leadership; People; and Governance. The Duty will also hold senior managers accountable via the Senior Managers & Certification Regime (SMCR) (FG22/5). A firm’s board will be responsible for the submission of a Board Report, which will be comprised of an assessment of whether the ‘firm is delivering good outcomes for its customers which are consistent with the Duty’ (FG22/5). Firms will also be required to monitor their outcomes, with a key focus of the Duty requiring firms to ‘assess, test, and understand’ and be able ‘to evidence the outcomes their customers are receiving’ (FG22/5), thus firms will be required to identify relevant sources of their data, to ensure they are consistent with meeting the obligations of the Duty, to their customers.
Unlocking the opportunity of vLEIs
Streamlining financial services workflows with Verifiable Legal Entity Identifiers (vLEIs)
Source: GLIEF
Trust is hard to come by
How do you trust people you have never met in businesses you have never dealt with before? It was difficult 20 years ago and even more so today. Many checks are needed to verify if the person you are talking to is the person you think it is. Do they even work for the business they claim to represent? Failures of these checks manifest themselves every day with spear phishing incidents hitting the headlines, where an unsuspecting clerk is badgered into making a payment to a criminal’s account by a person claiming to be a senior manager.
With businesses increasing their cross-border business and more remote working, it is getting harder and harder to trust what you see in front of you. How do financial services firms reduce the risk of cybercrime attacks? At a corporate level, there are Legal Entity Identifiers (LEIs) which have been a requirement for regulated financial services businesses to operate in capital markets, OTC derivatives, fund administration or debt issuance.
LEIs are issued by Local Operating Units (LOUs). These are bodies that are accredited by GLEIF (Global Legal Entity Identifier Foundation) to issue LEIs. Examples of LOUs are the London Stock Exchange Group (LSEG) and Bloomberg. However, LEIs only work at a legal entity level for an organisation. LEIs are not used for individuals within organisations.
Establishing trust at this individual level is critical to reducing risk and establishing digital trust is key to streamlining workflows in financial services, like onboarding, trade finance, and anti-financial crime.
This is where Verifiable Legal Entity Identifiers (vLEIs) come into the picture.
What is the new vLEI initiative and how will it be used?
Put simply, vLEIs combine the organisation’s identity (the existing LEI), a person, and the role they play in the organisation into a cryptographically-signed package.
GLEIF has been working to create a fully digitised LEI service enabling instant and automated identity verification between counterparties across the globe. This drive for instant automation has been made possible by developments in blockchain technology, self-sovereign identity (SSI) and other decentralised key management platforms (Introducing the verifiable LEI (vLEI), GLEIF website).
vLEIs are secure digitally-signed credentials and a counterpart of the LEI, which is a unique 20-digit alphanumeric ISO-standardised code used to represent a single legal organisation. The vLEI cryptographically encompasses three key elements; the LEI code, the person identification string, and the role string, to form a digital credential of a vLEI. The GLEIF database and repository provides a breakdown of key information on each registered legal entity, from the registered location, the legal entity name, as well as any other key information pertaining to the registered entity or its subsidiaries, as GLEIF states this is of “principally ‘who is who’ and ‘who owns whom’”(GLEIF eBook: The vLEI: Introducing Digital I.D. for Legal Entities Everywhere, GLEIF Website).
In December 2022, GLEIF launched their first vLEI services through proof-of-concept (POC) trials, offering instant digitally verifiable credentials containing the LEI. This is to meet GLEIF’s goal to create a standardised, digitised service capable of enabling instant, automated trust between legal entities and their authorised representatives, and the counterparty legal entities and representatives with which they interact” (GLEIF eBook: The vLEI: Introducing Digital I.D. for Legal Entities Everywhere, page 2).
“The vLEI has the potential to become one of the most valuable digital credentials in the world because it is the hallmark of authenticity for a legal entity of any kind. The digital credentials created by GLEIF and documented in the vLEI Ecosystem Governance Framework can serve as a chain of trust for anyone needing to verify the legal identity of an organisation or a person officially acting on that organisation’s behalf. Using the vLEI, organisations can rely upon a digital trust infrastructure that can benefit every country, company, and consumers worldwide”,
Karla McKenna, Managing Director GLEIF Americas
This new approach for the automated verification of registered entities will benefit many organisations and businesses. It will enhance and speed up regulatory reports and filings, due diligence, e-signatures, client onboarding/KYC, business registration, as well as other wider business scenarios.
Imagine the spear phishing example in the introduction. A spoofed email will not have a valid vLEI cryptographic signature, so can be rejected (even automatically), saving potentially thousands of £.
How do I get a vLEI?
Registered financial entities can obtain a vLEI from a Qualified vLEI Issuer (QVI) organisation to benefit from instant verification, when dealing with other industries or businesses (Get a vLEI: List of Qualified vLEI Issuing Organisations, GLEIF Website).
A QVI organisation is authorised under GLEIF to register, renew or revoke vLEI credentials belonging to any financial entity. GLEIF offers a Qualification Program where organisations can apply to operate as a QVI. GLEIF maintain a list of QVIs on their website.
Source: GLIEF
What is the new ISO 5009:2022 and why is it relevant?
The International Organisation of Standards (ISO) published the ISO 5009 standard in 2022, which was initially proposed by GLEIF, for the financial services sector. This is a new scheme to address “the official organisation roles in a structured way in order to specify the roles of persons acting officially on behalf of an organisation or legal entity” (ISO 5009:2022, ISO.org).
Both ISO and GLEIF have created and developed this new scheme of combining organisation roles with the LEI, to enable digital identity management of credentials. This is because the ISO 5009 scheme offers a standard way to specify organisational roles in two types of LEI-based digital assets, being the public key certificates with embedded LEIs, as per X.509 (ISO/IEC 9594-8), also outlined in ISO 17442-2, or for digital verifiable credentials such as vLEIs to be specified, to help confirm the authenticity of a person’s role, who acts on behalf of an organisation (ISO 5009:2022, ISO Website). This will help speed up the validation of person(s) acting on behalf of an organisation, for regulatory requirements and reporting, as well as for ID verification, across various business use cases.
Leading Point have been supporting GLEIF in the analysis and implementation of the new ISO 5009 standard, for which GLEIF acts as the operating entity to maintain the ISO 5009 standard on behalf of ISO. Identifying and defining OORs was dependent on accurate assessments of hundreds of legal documents by Leading Point.
“We have seen first-hand the challenges of establishing identity in financial services and were proud to be asked to contribute to establishing a new standard aimed at solving this common problem. As data specialists, we continuously advocate the benefits of adopting standards. Fragmentation and trying to solve the same problem multiple times in different ways in the same organisation hurts the bottom line. Fundamentally, implementing vLEIs using ISO 5009 roles improves the customer experience, with quicker onboarding, reduced fraud risk, faster approvals, and most importantly, a higher level of trust in the business.”
Rajen Madan (Founder and CEO, Leading Point)
Thushan Kumaraswamy (Founding Partner & CTO, Leading Point)
How can Leading Point assist?
Our team of expert practitioners can assist financial entities to implement the ISO 5009 standard in their workflows for trade finance, anti-financial crime, KYC and regulatory reporting. We are fully-equipped to help any organisation that is looking to get vLEIs for their senior team and to incorporate vLEIs into their business processes, reducing costs, accelerating new business growth, and preventing anti-financial crime.
Glossary of Terms and Additional Information on GLEIF
Who is GLEIF?
The Global Legal Entity Identifier Foundation (GLEIF) was established by the Financial Stability Board (FSB) in June 2014 and as part of the G20 agenda to endorse a global LEI. The GLEIF organisation helps to implement the use of the Legal Entity Identifier (LEI) and is headquartered in Basel, Switzerland.
What is an LEI?
A Legal Entity Identifier (LEI) is a unique 20 alphanumeric character code based on the ISO-17442 standard. This is a unique identification code for legal financial entities that are involved in financial transactions. The role of the structure of how an LEI is concatenated, principally answers ‘who is who’ and ‘who owns whom’, as per ISO and GLEIF standards, for entity verification purposes and to improve data quality in financial regulatory reports.
How does GLEIF help?
GLEIF not only helps to implement the use of LEI, but it also offers a global reference data and central repository on LEI information via the Global LEI Index on gleif.org, which is an online, public, open, standardised, and a high-quality searchable tool for LEIs, which includes both historical and current LEI records.
What is GLEIF’S Vision?
GLEIF believe that each business involved in financial transactions should be identifiable with a unique single digital global identifier. GLEIF look to increase the rate of LEI adoption globally so that the Global LEI Index can include all global financial entities that engage in financial trading activities. GLEIF believes this will encourage market participants to reduce operational costs and burdens and will offer better insight into the global financial markets (Our Vision: One Global Identity Behind Every Business, GLEIF Website).
Séverine Raymond Soulier's Interview with Leading Point
Séverine Raymond Soulier’s Interview with Leading Point
Séverine Raymond Soulier is the recently appointed Head of EMEA at Symphony.com – the secure, cloud-based, communication and content sharing platform. Séverine has over a decade of experience within the Investment Banking sector and following 9 years with Thomson Reuters (now Refinitiv) where she was heading the Investment and Advisory division for EMEA leading a team of senior market development managers in charge of the Investing and Advisory revenue across the region. Séverine brings a wealth of experience and expertise to Leading Point, helping expand its product portfolio and its reach across international markets.
ESG Operating models hold the key to ESG compliance
John Macpherson on ESG Risk
In my last article, I wrote about the need for an effective operating model in the handling and optimisation of data for Financial Services firms. But data is only one of several key trends amongst these firms that would benefit from a digital operating model. ESG has risen the ranks in importance, and the reporting of this has become imperative.
The Investment Association Engine Program, which I Chair, is designed to identify the most relevant pain points and key themes amongst Asset and Investment Management clients. We do this by searching out FinTech businesses that are already working on solutions to these issues. By partnering with these businesses, we can help our clients overcome their challenges and improve their operations.
While data has been an ever-present issue, ESG has risen to an equal standing of importance over the last couple of years. Different regulatory jurisdictions and expectations worldwide has left SME firms struggling to comply and implement in a new paradigm of environmental, sustainable and governance protocols.
ESG risk is different to anything we have experienced before and does not fit into neat categories such as areas like operational risk. The depth and breadth of data and models required for firms to make informed strategic decisions varies widely based on the specific issue at hand (e.g., supply chain, reputation, climate change goals, etc.). Firms need to carefully consider their own position and objectives when determining how much analysis is needed.
According to S&P Global, sustainable debt issuance reached a record level in 2021, and is only expected to increase further in the coming years. With this growth comes increased scrutiny and a heightened concern of so-called ‘greenwashing’, where companies falsely claim to be environmentally friendly. To combat this, participants need to manage that growth in a way that combats rising concerns about ‘greenwashing’.
Investors, regulators and the public, in general, are keen to challenge large companies’ ESG goals and results. These challenges vary wildly, but the biggest seen on a regular basis range from human rights to social unrest and climate change. As organisations begin to decarbonise their operations, they face the initially overlooked challenge of creating a credible near-term plan that will enable them to reach their long-term sustainability goals.
Investor pressure on climate change has historically focussed on the Energy sector. Now central banks are trying to incorporate climate risk as a stress testing feature for all Financial Services firms.
Source: S&P Global
Operating models hold the key to ESG transition and compliance. Having an operating model for how each of the firm’s functions intersect with ESG, requires new processes, new data, and new reporting techniques. This needs to be pulled across the enterprise, so firms have a process that is substantiated.
Before firms worry about ESG scores from their market data providers, they would do well to look closely at their own operating model and framework. In this way, they can then pull in the data required from the marketplace and use it in anger.
Leading Point is a FinTech business I am proud to be supporting. Their operating model system, modellr™ describes how financial services businesses work, from the products and services offered, to the key processes, people, data, and technology used to deliver value to their customers. This digital representation of how the business works is crucial to show what areas ESG will impact and how the firm can adapt in the most effective way.
Rajen Madan, CEO at Leading Point:
“In many ways, the transition to ESG is exposing the acute gap in firms of not being able to have meaningful dialogue with the plethora of data they already have, and need, to further add to for ESG”.
modellr™ harvests a company’s existing data to create a living dashboard, whilst also digitising the change process and enabling quicker and smarter decision-making. Access to all the information, from internal and external sources, in real time is proving transformative for SME size businesses.
Thushan Kumaraswamy, Chief Solutions Officer at Leading Point:
“ESG is already one of the biggest drivers of transformation in financial services and is only going to get bigger. Firms need to identify the impact on their business, choose the right change option, execute the strategy, and measure the improvements. The mass of ESG frameworks adds to the confusion of what to report and how. Tools such as modellr™ bring clarity and purpose to the ESG imperative.”
While most firms will look to sustainability officers for guidance on matters around ESG, Leading Point are providing these officers, and less qualified team members, with the tools to make informed decisions now, and in the future. We have established exactly what these firms need to succeed – a digital operating model.
Words by John Macpherson — Board advisor at Leading Point and Chair of the Investment Association Engine
The Challenges of Data Management
John Macpherson on The Challenges of Data Management
I often get asked, what are the biggest trends impacting the Financial Services industry? Through my position as Chair of the Investment Association Engine, I have unprecedented access to the key decision-makers in the industry, as well as constant connectivity with the ever-expanding Fintech ecosystem, which has helped me stay at the cutting edge of the latest trends.
So, when I get asked, ‘what is the biggest trend that financial services will face’, for the past few years my answer has remained the same, data.
During my time as CEO of BMLL, big data rose to prominence and developed into a multi-billion-dollar problem across financial services. I remember well an early morning interview I gave to CNBC around 5 years ago, where the facts were starkly presented. Back then, data was doubling every three years globally, but at an even faster pace in financial markets.
Firms are struggling under the weight of this data
The use of data is fundamental to a company's operations, but they are finding it difficult to get a handle on this problem. The pace of this increase has left many smaller and mid-sized IM/ AM firms in a quandary. Their ability to access, manage and use multiple data sources alongside their own data, market data, and any alternative data sources, is sub-optimal at best. Most core data systems are not architected to address the volume and pace of change required, with manual reviews and inputs creating unnecessary bottlenecks. These issues, among a host of others, mean risk management systems cannot cope as a result. Modernised data core systems are imperative to solve where real-time insights are currently lost, with fragmented and slow-moving information.
Around half of all financial service data goes unmentioned and ungoverned, this “dark data” poses a security and regulatory risk, as well as a huge opportunity.
While data analytics, big data, AI, and data science are historically the key sub-trends, these have been joined by data fabric (as an industry standard), analytical ops, data democratisation, and a shift from big data to smaller and wider data.
Operating models hold the key to data management
Governance is paramount to using this data in an effective, timely, accurate and meaningful way. Operating models are the true gauge as to whether you are succeeding.
Much can be achieved with the relatively modest budget and resources firms have, provided they invest in the best operating models around their data.
Leading Point is a firm I have been getting to know over several years now. Their data intelligence platform modellr™, is the first truly digital operating model. modellr™ harvests a company’s existing data to create a living operating model, digitising the change process, and enabling quicker, smarter, decision making. By digitising the process, they’re removing the historically slow and laborious consultative approach. Access to all the information in real-time is proving transformative for smaller and medium-sized businesses.
True transparency around your data, understanding it and its consumption, and then enabling data products to support internal and external use cases, is very much available.
Different firms are at very different places on their maturity curve. Longer-term investment in data architecture, be it data fabric or data mesh, will provide the technical backbone to harvest ML/ AI and analytics.
Taking control of your data
Recently I was talking to a large investment bank for whom Leading Point had been brought in to help. The bank was looking to transform its client data management and associated regulatory processes such as KYC, and Anti-financial crime.
They were investing heavily in sourcing, validating, normalising, remediating, and distributing over 2,000 data attributes. This was costing the bank a huge amount of time, money, and resources. But, despite the changes, their environment and change processes had become too complicated to have any chance of success. The process results were haphazard, with poor controls and no understanding of the results missing.
Leading Point was brought in to help and decided on a data minimisation approach. They profiled and analysed the data, despite working across regions and divisions. Quickly, 2,000 data attributes were narrowed to less than 200 critical ones for the consuming functions. This allowed the financial institutions, regulatory, and reporting processes to come to life, with clear data quality measurement and ownership processes. It allowed the financial institutions to significantly reduce the complexity of their data and its usability, meaning that multiple business owners were able to produce rapid and tangible results
I was speaking to Rajen Madan, the CEO of Leading Point, and we agreed that in a world of ever-growing data, data minimisation is often key to maximising success with data!
Elsewhere, Leading Point has seen benefits unlocked from unifying data models, and working on ontologies, standards, and taxonomies. Their platform, modellr™is enabling many firms to link their data, define common aggregations, and support knowledge graph initiatives allowing firms to deliver more timely, accurate and complete reporting, as well as insights on their business processes.
The need for agile, scalable, secure, and resilient tech infrastructure is more imperative than ever. Firms’ own legacy ways of handling this data are singularly the biggest barrier to their growth and technological innovation.
If you see a digital operating model as anything other than a must-have, then you are missing out. It’s time for a serious re-think.
Words by John Macpherson — Board advisor at Leading Point, Chair of the Investment Association Engine
John was recently interviewed about his role at Leading Point, and the key trends he sees affecting the financial services industry. Watch his interview here
Leading Point Shortlisted For Data Management Insight Awards
Leading Point 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:
- Most Innovative Data Management Provider
- Best Data Analytics Solution Provider
- Best Proposition for AI, Machine Learning, Data Science
- Best Consultancy in Data Management
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
Severine Raymond Soulier joins the Leading Point advisory board
Severine Raymond Soulier joins the Leading Point advisory board
Leading Point™ are thrilled to welcome Severine Raymond Soulier as the newest member of their advisory board. Severine joins Leading Point™ to expand the product portfolio and its reach across international markets.
Severine is the recently appointed Head of EMEA at Symphony.com – the secure, cloud-based, communication and content sharing platform. Severine has over a decade of experience within the Investment Banking sector and following 9 years with Thomson Reuters (now Refinitiv) where she was heading the Investment and Advisory division for EMEA leading a team of senior market development managers in charge of the Investing and Advisory revenue across the region. Severine Raymond brings a wealth of experience and expertise to Leading Point.
Severine Raymond Soulier says: “I am delighted to join the Leading Point team, I have been truly impressed by the talents within the team and by the transformation projects they have run with key financial players so far and look forward to bringing the company to the next level. I also fully embrace the diverse and inclusive culture of Rajen’s team and I will surely be enriched by the team and hope they can benefit from my leadership in return."
Rajen Madan, Founder & CEO of Leading Point says, "We are excited to have Severine join Leading Point. She brings expertise in strategy, go-to-market and team building for global established FS firms. She has driven high growth in her current role at Symphony. Severine’s rich experience will help us expand our product portfolio and reach across international markets. Severine is passionate about helping create future female leaders and will be a great role model and mentor to our wider team.”
Who we are:
Leading Point is a fintech specialising in digital operating models. We are revolutionising the way operating models are created and managed through our proprietary technology, modellr™, and expert services delivered by our team of specialists.
Contact: rajen@leadingpoint.io
How Startups Can Increase Employee Freedoms Without Losing Control
How Startups Can Increase Employee Freedoms Without Losing Control
Introduction from Leading Point:
We love collaboration here at Leading Point and we are lucky enough to have some great clients and partners that feel the same. We work with some similar like-minded start-ups that share some of the same challenges and adventures as us. Below is a brilliantly informative article by our friends at Spendesk, explaining how startups can successfully create a positive working environment for their employees through trust and freedom. At Leading Point, this is something we firmly embody. Forging strong, meaningful relations is how we deliver our services, and without a satisfied, confident team, this simply can't be done. If you're a startup, and increasing employee freedoms without losing control is something your company is in need of, don’t fret, this piece will provide great tips on how to apply some quick and easy changes to make team building better and brighter for everyone. Overall, we are delighted to be office neighbours with Spendesk, and are looking forward to some more collaborations in the future. Watch this space!
Words by Ellen Masterson:
Every employer wants their team to be happy, efficient, and effective. Most recognise that the vast majority make good decisions and don’t need to be micromanaged.
And yet, because of concerns about risk and compliance, many companies create hurdles that slow down their teams and take power away from actors.
As HBR explains, “executives have trouble resolving the tension between employee empowerment and operational discipline. This challenge is so difficult that it ties companies up in knots. Indeed, it has led to decades’ worth of management experiments, from matrix structures to self-managed teams.”
Today, we have bad solutions to legitimate concerns. The answer to a need for process security isn’t to restrict access - it’s to create more secure processes. And as we’ll see, that doesn’t have to be complex.
In this article, we’ll explore the reasons why companies struggle allowing freedom, and how a few simple shifts can make all the difference.
What prevents employee freedoms today?
Before getting to the positive actions all businesses can take, let’s start by identifying why employees may not have the freedom they need to excel.
Here, we’re talking about two kinds of freedom:
- Freedom to make decisions and shape their own work scope and projects;
- Freedom from excessive administrative and managerial pressure.
Together, these lead to more productive employees, a happier work environment, and faster growth.
In particular, we can look at two crucial causes.
A systemic lack of trust
This is fundamental. Many businesses simply aren’t structured to let team members think for themselves. Every decision must be scrutinized, and every action needs sign-off.
Of course, some micromanaging is always to be expected. And some actions really do need sign-off. But many don’t, and it’s vital to consider the cost of always putting the breaks on as team members push forward.
A few simple questions to ask:
- Are our employees free to do their best work?
- Are the rules we have in place helping, or hurting?
- Can we trust our teams to make the right decisions, without always second guessing?
As we’ll see, there are plenty of positive ways to remove hurdles without losing control over what really matters.
Closed-off systems and gatekeepers
Aside from the broad principle that employees should be free to make choices, there are common corporate practices that limit freedom - and not always for good reasons. Whether there’s limited institutional knowledge or a lack of trust, we make certain people responsible for processes, and lock everyone else out.
A few examples:
- Key business data is only accessible by executive leadership. New revenue, customer churn, and average deal size can all help employees make smarter decisions. But many simply don’t have access.
- Corporate credit cards belong to a few select managers. This makes it very hard for anyone else to spend company money, creates hurdles, and slows down business.
Today, we have ways to give employees more hands-on access to these processes without creating new risks or losing control. Let’s take a look at these now.
How to increase freedom while retaining control
We have what seem to be two conflicting objectives. But employee freedom and organisational freedom can certainly co-exist. Just follow these four principles.
1. Recognise trust as a core company value
If you want employees to feel free to do their best work, you obviously need to trust them to do so. What’s more, they need to know that they’re trusted to make decisions. This is empowering.
Which means that trust needs to be enshrined as a company value. Many startups are now taking the time to carefully craft their culture code - this is seen as vital to startup success. It’s also hugely important in the hiring process, and helps you keep employees around for longer.
So one way or another, trust needs to be in there. At Spendesk, for example, one of our core values is ownership. Each employee owns their scope and is empowered to make decisions. Which is another way of saying that the company trusts us.
2. Build systems that everyone can use
We mentioned above the trouble with having closed-off systems. This manifests itself in two main ways:
- Systems are so complex that only those with specific skills can use them;
- Most employees literally cannot access them - they lack the permissions or the tools to do so.
And of course, there is occasionally good reason for this. Average employees shouldn’t have access to the company bank account, for example. Which leads many finance teams to believe they need control over all spending. Or that only managers should have the right to spend company money. Neither of which are true.
Instead, you need systems that guide employees, set out limits and rules, and prevent them from making costly mistakes. Team members are free to make choices, just within certain parameters.
One example is replacing company credit cards and expense claims with more tailored spend management solutions. These let you set the rules per employee or team, create spending limits, and require managerial approval above certain thresholds.
So there you have full control. But employees have their own access - they don’t need to come begging for the corporate card - and finance teams don’t have to hold people’s hands throughout. The software guides them through each payment.
That was one just one example. But similar systems exist for HR and payroll, invoice processing, accounting, and a wide array of other corporate procedures.
3. Speak in plain language
Another simple error that many companies make is in communication. If you make policies harder to understand than they need to be, you actually reduce the likelihood that teams follow them. Which then leads to two outcomes:
- Reduced control, since people aren’t following the rules you create;
- Slower outcomes, because a manager or finance team member has to explain every transaction to employees one-to-one.
So the simple and impactful choice here is to ensure that internal policies and processes can be followed with no intervention. In practice, this means:
- No lengthy policy documents. The more you trust your team, the shorter you can make your travel and expense policy, for example.
- Keep jargon to a minimum. Documents should be easy to understand.
- Build policies into processes. Even better than cross-referencing policy documents is to have them actually built-into systems. Assume that people haven’t read the document, so have systems that guide them through the process and keep them within boundaries.
- Communicate clearly and repeat yourself. At a higher level, company values and expectations should be expressed openly and reiterated often.
Overall, don’t confuse freedom with a lack of rules. Employees need the freedom to make choices within clearly set boundaries. Knowing what’s expected and allowed is freeing.
4. Remove obvious administrative hurdles
One clear impediment to freedom is creating hurdles and hoops to jump through. If employees can’t work smoothly and independently - and are always catching up on paperwork - it’s hard to say that they’re operating freely.
But we can’t remove all admin for good. Instead, here are principles to make processes as painless as possible, while still maintaining compliance and control.
- Go paperless. The very act of filing a form by hand, only to digitize it later adds time and effort. Replace all paper-based systems with digital-first alternatives, and things will move faster and freer.
- Make processes and data easy to find. Employees should be able to answer their own questions and find solutions quickly. Otherwise, you’re forcing them to rely on others - usually HR and finance teams - which can quickly lead to interpersonal issues.
- Make approvals fast and efficient. Purchases will usually need a manager’s approval. As will other areas of compliance. Make this smoother with automated approval workflows, and with systems that track approvals asynchronously. In other words, it shouldn’t require an email chain to find out who approved a particular transaction. Build this into your systems.
We often think of admin as a necessary evil if we want to keep control and compliance. But you can have free-flowing, fast processes without creating unnecessary roadblocks along the way.
Conclusion
As mentioned above, it’s natural to micromanage and to seek control over company decisions. But it’s not good. You’ve hired team members for their skills and ingenuity, so why would you restrict their use of them?
Brian Carney and Isaac Getz offer this example of a liberated company’s manager: “When her team shares a problem or an opportunity with her, she will not offer a solution. Instead, she asks them to find their own—after ensuring that there isn’t something she’s doing that would get in the way.”
For some businesses, achieving liberated company status would be a tectonic shift. It’s a worthwhile project, but one that will take years and plenty of soul searching.
But we’ve seen examples above of precise, easy-to-implement changes that have profound effects. Start with a few of these, and gradually work towards becoming a company that puts employee trust on a par with corporate control.
After all, the two can naturally co-exist with no issue.
Author:
Ellen Masterson: Ellen Masterson is a UK and Ireland market expert at Spendesk, where she helps startups and scaleups establish simple yet robust spend management processes.
GDFM & Leading Point Partnering for Smarter Regulatory Health Management
GDFM and Leading Point collaborate to deliver innovative and efficient regulatory risk management to our clients and through the SMART_Dash product; enabling consistent, centralised, accessible regulatory health data to assist responsible and accountable individuals with ensuring adequate transparency, for risk mitigation decision making and action taking. This is complemented by a SMART_Board suite for Board level leadership and a more detailed SMART_Support suite for regulatory reporting teams.
We are delighted that SMART_Dash has been shortlisted in 3 categories in this year's prestigious RegTech Insight Awards in Europe, which recognises both established solution providers and innovative newcomers, seeking to herald and highlight innovative RegTech solutions across the global financial services industry.
GD Financial Markets Head of Regulatory Compliance Practice and SMART_Dash Co-creator Sarah Peaston "Centralised, consolidated, consistent regulatory health transparency and tracking is key to identifying and managing regulatory and operating risk. I am delighted that SMART_Dash has been recognised as a new breed of solution that practically assists Managers, Senior Managers and Leadership with managing their regulatory health through the provision of the right information, at the right level to the right seniority”.
Leading Point CEO Rajen Madan "Our vision with SMART_Dash is to accelerate better regulatory risk management approaches and vastly more efficient RegOps. As financial services practitioners we are acutely aware of the time managers spend trying to make sense of their regulatory and operating risk areas from a multitude of inconsistent reports. SMART_Dash enables the shift to an enhanced way of risk management, which creates standardisation and makes reg data work for your business. We are very grateful to the COO, CRO and CFOs whom have contributed to its development and help the industry move forward”.
GDFM and Leading Point are rolling out the SMART_Dash suite to the first set of industry consortium partners progressively in H1 2021, and thereafter open to a wider set of institutions.
The Composable Enterprise: Improving the Front-Office User Experience
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By Dishang Patel, Fintech & Growth Delivery Partner, Leading Point Financial Markets.
The past six months have by no means been a time of status quo. During this period of uncertainty, standards have been questioned and new ‘norms’ have been formed.
A standout development has been the intensified focus on cloud-based services. Levels of adoption have varied, from those moving to cloud for the first time, to others making cloud their only form of storage and access, and with numerous ‘others’ in between.
One area affected adversely (for those who weren’t ready) but positively (for those who were) is software. ‘Old-school’ software vendors – whose multi-million-pound solutions were traditionally implemented on premise at financial institutions, whether as part of a pure ‘buy’ or broader ‘build’ approach – have worked hard to offer cloud-based services.
The broad shift to working from home (WFH) as a result of the Covid-19 pandemic has tested the end-user experience all the way from front to back offices in financial institutions. Security, ease of access and speed are all high on the agenda in the new world in which we find ourselves.
The digitisation journey
With workforces operating globally, it is difficult to guarantee uniform user experiences and be able to cater for a multitude of needs. To achieve success in this area and to ensure a seamless WFH experience, financial institutions have moved things up a level and worked as hard as software providers to offer cloud-based solutions.
All manner of financial institutions (trading firms, brokerages, asset managers, challenger banks) have been on a digitisation journey to make the online user experience more consistent and reliable.
Composable Enterprise is an approach that those who have worked in a front office environment within financial services may have come across and for many could be the way forward.
Composable Enterprise: the way forward
Digitisation can come in many forms: from robotic process automation (RPA), operational excellence, implementation of application-based solution, interoperability and electronification. Interoperability and electronification are two key components of this Composable Enterprise approach.
Interoperability – whether in terms of web services, applications, or both – is an approach that can create efficiencies on the desktop and deliver improved user experience. It has the potential to deliver business performance benefits, in terms of faster and better decision making with the ultimate potential to uncover previously untapped alpha. It also has two important environmental benefits:
1) Reducing energy spend;
2) Less need for old hardware to be disposed of, delivering the reduced environmental footprint that organisations desire.
Electronification, for most industry players, may represent the final step on the full digitisation journey. According to the Oxford English Dictionary, electronification is the “conversion to or adoption of an electronic mode of operation,” which translates to the front office having all the tools they need to do their jobs to the best of their ability.
The beauty of both interoperability and electronification is that they work just as well in a remote set up as they do in an office environment. This is because a good implementation of both results in maximising an organisation’s ability to use all the tools (trading platforms, market data feeds, CRMs, and so on) at their disposal without needing masses of physical infrastructure.
Because of the lower barriers (such as time and cost) of interoperability, financial institutions should start their digitisation journeys from this component and then embark on a larger and more complicated move to electronification.
Composable Enterprise is about firms being able to choose the best component needed for their business, allowing them to be more flexible and more open in order to adapt to new potential revenue opportunities. In these challenging times, it is no surprise that more and more financial institutions are adding Composable Enterprise as a key item on their spending agenda.
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"The broad shift to working from home as a result of the Covid-19 pandemic has tested the end-user experience all the way from front to back offices in financial institutions."
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"It has the potential to deliver business performance benefits, in terms of faster and better decision making with the ultimate potential to uncover previously untapped alpha."
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"The beauty of both interoperability and electronification is that they work just as well in a remote set up as they do in an office environment."
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Responsible for delivering digital FS businesses.
Transforming delivery models for the scale up market.
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Contact Us
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Information Security in a New Digital Era
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Shifting priorities
The 2020’s pandemic, subsequent economic turmoil and related social phenomena has paved the way for much-needed global digital transformation and the prioritisation of digital strategies. The rise in digitisation across all businesses, however, has accelerated cyber risk exponentially. With cloud-based attacks rising by 630% between January and April 2020(1), organisations are now turning their focus on how to benefit from digitisation whilst maintaining sufficiently secure digital environments for their services and clients.
A global challenge
A new digital setup could easily jeopardise organisations’ cyber safety. With data becoming companies’ most valuable asset, hackers are getting creative with increasingly-sophisticated threats and phishing attacks. According to the 2019 Data Breach Investigation Report(2) by Verizon, 32% of all verified data breaches appeared to be phishing.
As data leaks are increasing (3,800 alone in 2019), so is the cyber skill shortage. According to the MIT Technology Review report(3), there will be 3.5 million unfulfilled cybersecurity jobs in 2021; a rise of 350%. As a result of Covid-19 and digitised home working, cybersecurity professionals are high in demand to fill the gaps organisations’
currently face.
The way forward
Although tackling InfoSec breaches in the rapidly-evolving digital innovation landscape is not easy, it is essential to keep it as an absolute priority. In our work with regulated sector firms in financial services, pharma and energy as well as with fintechs, we see consistent steps that underpin successful information security risk management. We have created a leaderboard of 10 discussion points for COOs, CIOs and CISOs to keep up with their information security needs:
- Information Security Standards
Understand information security standards like NIST, ISO 27001/2 and BIP 0116/7 and put in place processes and controls accordingly. These are good practices to keep a secure digital environment and are vital to include in your risk mitigation strategy. Preventing cyber attacks and data breaches is less costly and less resource-exhaustive than dealing with the damage caused by these attacks. There are serious repercussions of security breaches in terms of cost and reputational damage, yet organisations still only look at the issue after the event. Data shows that firms prefer to take a passive approach to tackle these issues instead of taking steps to prevent them in the first place.
- Managing security in cloud delivery models
2020 has seen a rise in the use of SaaS applications to support employee engagement, workflow management and communication. While cloud is still an area in its preliminary stages, cloud adoption is rapidly accelerating. But many firms have initiated cloud migration projects without a firm understanding and design for the future business, customer or end user flows. This is critical to ensuring a good security infrastructure in a multi-cloud operating environment. How does your firm keep up with the latest developments in Cloud Management?
- Operational resilience
70% of Operational Risk professionals say that their priorities and focus have changed as a result of Covid-19(4). With less than half of businesses testing their continuity and business-preparedness initiatives(5), Coronavirus served as an eye-opener in terms of revisiting these questions. Did your business continuity plan prove successful? If so, what was the key to its success? How do you define and measure operational resilience in your business? Cross-functional data sets are increasingly vital for informed risk management.
- Culture
Cyber risk is not just a technology problem; it is a people
problem. You cannot mitigate cyber risks with just technology;
embedding the right culture within your team is vital. How do you make sure a cyber-secure company culture is kept up in remote working environments? Does your company already have an information security training plan in place?
- Knowing what data is important
Data is expanding exponentially – you have to know what you need to protect. Only by defining important data, reducing the signal-to-data noise and aggregating multiple data points can organisations look to protect them. As a firm, what percentage of your data elements are defined with an owner and user access workflow?
- Speed of innovation means risk
The speed of innovation is often faster than the speed of safety. As technology and data adoption is rapidly changing, data protection has to keep up as well – there is little point in investing in technology until you really understand your risks and your exposure to those risks. This is increasingly true of new business-tech frameworks, including DLT, AI and Open Banking. When looking at DLT and AI based processes - how do you define the security and thresholds?
- Master the basics
80% of UK companies and startups are not Cyber Essentials ready, which shows that the fundamentals of data security are not being dealt with. Larger companies are rigid and not sufficiently agile – more demands are being placed on teams but without sufficient resources and skills development. Large companies cannot innovate if they are not given the freedom to actually adapt. What is the blocker in your firm?
- Collaborate with startups
Thousands of innovative startups tackling cyber security currently exist and many more will begin their growth journey over the next few years. Larger businesses need to be more open to collaborating with them to help speed up advancements in the cyber risk space.
- The right technology can play a key role in efficiency and speed
We see the emerging operating models for firms are open API based, and organisations need to stitch together many point solutions. Technology can help here if deployed correctly. For
instance, to join up multiple data, to provide transparency of
messages crossing in and out of systems, to execute and detect
information security processes and controls with 100x efficiency and speed. This will make a material difference in the new world of
financial services.
- Transparency of your supply chain
Supply chains are becoming more data-driven than ever with increased number of core operations and IT services being outsourced. Attackers are using weak supplier controls to compromise client networks and dispersed dependencies create increased reliance and risk exposure from entities outside of your direct control. How do you manage the current pressure points of your supplier relationships?
Next steps
Cyber risk (especially regarding data protection) is simultaneously a compliance problem (regulatory risk, legal risk etc.), an architecture problem (infrastructure, business continuity, etc.), and a business problem (reputational risk, loss of trust, ‘data poisoning’, competitor intelligence etc.). There are existing risk assessment frameworks for managing operational risk (example: ORMF) – why not plug in?
Getting the basics right, using industry standards, multi-cloud environments and transparency of supply chain are good places to start. These are all to do with holistic data risk management (HRM).
While all these individual issues pose problems on their own, they can be viewed through inter-relationships applying a holistic approach where a coordinated solution can be found to efficiently manage these issues as a whole. The solution lies in taking a more deliberate approach to cyber security and following this 4-step process:
IDENTIFY
ORGANISE
ASSIGN
RESOLVE
Find out more on Operational Resilience from Leading Point:
https://leadingpointfm.com/operational-resilience-data-infrastructure-and-aconsolidated-risk-view-is-pivotal-to-the-new-rules-on-operational-risk/#_edn2
Find out more on Data Kitchen, a Leading Point initiative:
https://leadingpointfm.com/the-data-kitchen-does-data-need-science/
(1) https://www.fintechnews.org/the-2020-cybersecurity-stats-you-need-to-know/
(2) https://www.techfunnel.com/information-technology/cyber-security-trends/
(5) https://securityintelligence.com/articles/these-cybersecurity-trends-could-get-a-boost-in-2020/
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"With data becoming companies’ most valuable asset, hackers are getting creative with increasingly-sophisticated threats and phishing attacks."
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"Preventing cyber attacks and data breaches is less costly and less resource-exhaustive than dealing with the damage caused by these attacks."
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"70% of Operational Risk professionals say that their priorities and focus have changed as a result of Covid-19."
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Rajen Madan
Founder & CEO
rajen@leadingpoint.io
Delivering Digital FS businesses. Change leader with over 20 years’ experience in helping firms with efficiency, revenue and risk management challenges
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Aliz Gyenes
Leading Point
Data Innovation, InfoSec, Investment behaviour research Helping businesses understand and improve their data strategy via the Leading Point Data Innovation Index
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How Leading Point can help
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3 Reasons Why All Startups Should Embrace ESG
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Environmental, Social & Governance (ESG) issues are firmly on the board agendas of large, publicly-listed companies. 2021 marks the year in which VC-backed startups need to follow suit. What is the best way to achieve this change?
Some smaller companies have already made the move. A recent survey (1) of pre-seed and series A startups found that almost two thirds already have some ESG policies in place. Of those who didn’t, over half were now seriously considering them.
Startups can benefit from an ESG focus for three key reasons: a higher chance of investment, attracting better talent and risk mitigation.
Increased investment
Over the last five years there has been an explosion in VC funds focusing on startups in the ESG space. One such fund is DBL Partners. They are currently looking to raise $450m for their fourth fundt. Their mission involves investing in companies which provide capital returns while also enabling environmental and social benefits.
More recently, an increasing number of non-ESG focused VC firms are embedding ESG values into the companies they invest in. For example, Christine Tsai, CEO of 500 Startups, one of the most active global early stage venture capital firms whose “unicorn investments” include Credit Karma, Canva, Grab and Talkdesk, said that startups should implement ESG early on (2).
If startups want to stand out, they should embed ESG policies into their business model, principles and culture at the beginning rather than trying to “retro-fit” policies later under the pressure of investors or others.
Top talent attraction and retention
Startups with ESG values embedded in the business are more attractive to the best talent. This gives them a tangible competitive advantage.
Millennials currently make up 50% of the global workforce (3). A recent study (4) found that more than 40% said they had joined a firm because they performed better on sustainability. The same study showed that they are 70% more likely to stay longer if they feel the company has a strong sustainability plan.
However, relying on ESG policies and reporting (internally and externally) alone is not enough to benefit. Startups need to embrace a culture of openness at the core of their business. They must be honest to their stakeholders about their ESG weaknesses as well as their strengths. Only then will their ESG communications be authentic and have real impact on talent attraction and more importantly retention.
Risk mitigation
ESG policies can de-risk young companies as policy adoption becomes more difficult as they grow. A recent white paper (5) argued that startups are even more vulnerable to negative reputational impacts compared to more established firms, given their relatively small size and high growth characteristics.
For example, German fintech success story Wirecard shook the financial world earlier this year as it became clear that over $2bn was missing from their balance sheet (6). Also, in late 2019, it was reported that the CEO and founder of luggage startup AWAY, which had raised over $31 million, openly bullied and belittled her employees (7). This led to a media backlash against the company which greatly impacted their growth and market position.
With stronger governance policies and procedures, these scandals may have been avoidable. Startups which embed strong governance policies early on are much less likely to run into such issues.
How to integrate ESG into a VC-backed startup
It can be difficult for founders to decide which ESG policies to apply, which areas to focus on and how to communicate their outcomes authentically to stakeholders. Yet this is something which investors and top talent are increasingly looking for.
ESG action plans should follow a staged approach, with a roadmap assessed and realigned at each funding round:
- Map your current ESG strengths
Work out what you are already doing right, supported by resources such as the Sustainable Accounting Standards Board Materiality Map to work out which ESG policies and metrics are relevant for your industry. Also, map out the ecosystem of the different stakeholders your company interacts with, including customers, suppliers, regulators and employees.
- Develop your goals and measure your progress
Collect the relevant data to work out your current baseline and decide goals for the short, medium and long term, building a dashboard incorporating relevant Key Performance Indicators (KPIs) to track progress. ESG standards are complex and can need a multitude of different data points depending on the type of industry.
- Communicate your position
Regularly collect and communicate your ESG data to relevant stakeholders including investors, employees, regulators, consumers and the media. Publish your ESG successes and milestones on your social media channels and your recruitment page. You might also want to consider inviting in third party auditors to validate your ESG data and methods of collecting it, and look into external certification e.g B-corp status.
This brief overview may not answer all your questions.
If you would like to hear more about how we can help VCs and startups manage, improve and communicate their ESG impact please get in touch.
1. 500 Startups (2020) Survey results: The Impact of Covid-19 on the Early-Stage Investment Climate, https://survey.500.co/investor-survey-report-download/
2.Venture Capital Journal (Jun 2020) 500 Startups makes ESG top of mind going forward,https://www.venturecapitaljournal.com/500-startups-makes-esg-top-of-mind-going-forward/
3.KMPG (2017) Meet the millennials https://home.kpmg/content/dam/kpmg/uk/pdf/2017/04/Meet-the-Millennials-Secured.pdf
4. Fast Company (Feb 2019) Most millennials would take a pay cut to work at a environmentally responsible company,https://www.fastcompany.com/90306556/most-millennials-would-take-a-pay-cut-to-work-at-a-sustainable-company
5. CDC investment works & FMO Entrepreneurial Investment Bank (Jan 2020) Responsible venture capital Integrating environmental and social approaches in early-stage investing, https://assets.cdcgroup.com/wp-content/uploads/2020/01/16092500/Responsible-Venture-Capital.pdf
6. Markets Insider (Jun 2020) How $2 billion vanished from the balance sheet of Wirecard, according to a forensic financial expert, https://markets.businessinsider.com/news/stocks/wirecard-scandal-numbers-financial-forensic-expert-breakdown-2020-6-1029332810
7.The Verge (Dec 2019) Away’s founders sold a vision of travel and inclusion, but former employees say it masked a toxic work environment, https://www.theverge.com/2019/12/5/20995453/away-luggage-ceo-steph-korey-toxic-work-environment-travel-inclusion
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"Startups can benefit from an ESG focus for three key reasons: a higher chance of investment, attracting better talent and risk mitigation."
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"If startups want to stand out, they should embed ESG policies into their business model, principles and culture at the beginning rather than trying to “retro-fit” policies later under the pressure of investors or others."
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"ESG policies can de-risk young companies as policy adoption becomes more difficult as they grow."
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Environmental Social & Governance (ESG) and Sustainable Investment
Client propositions and products in data-driven transformation in ESG and Sustainable Investing.
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Responsible for delivering digital FS businesses.
Transforming delivery models for the scale up market.
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Upcoming blogs:
This is the fourth in a series of blogs that will explore the ESG world: its growth, its potential opportunities and the constraints that are holding it back. We will explore the increasing importance of ESG and how it affects business leaders, investors, asset managers, regulatory actors and more.
Artificial Intelligence: the Solution to the ESG Data Gap? In the second part of our Environmental, Social and Governance (ESG) blog series, Anya explores the potential opportunities surrounding Artificial Intelligence and responsible investing.
Riding the ESG Regulatory Wave: In the third part of our Environmental, Social and Governance (ESG) blog series, Alejandra explores the implementation challenges of ESG regulations hitting EU Asset Managers and Financial Institutions.
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How Leading Point can help
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By using our cloud-based data visualisation platform to bring together relevant metrics, we help organisations gain a standardised view and improve your ESG reporting and portfolio performance. Our live ESG dashboard can be used to scenario plan, map out ESG strategy and tell the ESG story to stakeholders.
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AI helps with the process of ingesting, analysing and distributing data as well as offering predictive abilities and assessing trends in the ESG space. Leading Point is helping our AI startup partnerships adapt their technology to pursue this new opportunity, implementing these solutions into investment firms and supporting them with the use of the technology and data management.
[/et_pb_blurb_extended][/et_pb_column][et_pb_column type="1_3" _builder_version="4.4.8"][et_pb_blurb_extended title="Assisting companies to implement upcoming EU ESG regulations" use_icon="on" font_icon="%%392%%" icon_color="#ffffff" use_icon_font_size="on" icon_font_size="39px" icon_hover_color="#17a826" style_icon="on" icon_shape="use_circle" use_shape_border="on" shape_border_color="#ffffff" shape_border_hover_color="#17a826" title_hover_color="#17a826" _builder_version="4.4.8" header_text_align="left" header_text_color="#ffffff" header_font_size="17px" read_more_icon="%%20%%" text_orientation="center" custom_margin="5px|1px|5px|1px|false|false" custom_padding="0px|0px|0px|0px|false|false" animation_style="fade" locked="off"]
Implementing ESG regulations and providing operational support to improve ESG metrics for banks and other financial institutions. Ensuring compliance by benchmarking and disclosing ESG information, in-depth data collection to satisfy corporate reporting requirements, conducting appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.
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Artificial Intelligence: The Solution to the ESG Data Gap?
The Power of ESG Data
It was Warren Buffett who said, “It takes twenty years to build a reputation and five minutes to ruin it” and that is the reality that all companies face on a daily basis. An effective set of ESG (Environment, Social & Governance) policies has never been more crucial. However, it is being hindered by difficulties surrounding the effective collection and communication of ESG data points, as well a lack of standardisation when it comes to reporting such data. As a result, the ESG space is being revolutionised by Artificial Intelligence, which can find, analyse and summarise this information.
There is increasing public and regulatory pressure on firms to ensure their policies are sustainable and on investors to take such policies into account when making investment decisions. The issue for investors is how to know which firms are good ESG performers and which are not. The majority of information dominating research and ESG indices comes from company-reported data. However, with little regulation surrounding this, responsible investors are plagued by unhelpful data gaps and “Greenwashing”. This is when a firm uses favourable data points and convoluted wording to appear more sustainable than they are in reality. They may even leave out data points that reflect badly on them. For example, firms such as Shell are accused of using the word ‘sustainable’ in their mission statement whilst providing little evidence to support their claims (1).
Could AI be the complete solution?
AI could be the key to help investors analyse the mountain of ESG data that is yet to be explored, both structured and unstructured. Historically, AI has been proven to successfully extract relevant information from data sources including news articles but it also offers new and exciting opportunities. Consider the transcripts of board meetings from a Korean firm: AI could be used to translate and examine such data using techniques such as Sentiment Analysis. Does the CEO seem passionate about ESG issues within the company? Are they worried about an investigation into Human Rights being undertaken against them? This is a task that would be labour-intensive, to say the least, for analysts to complete manually.
In addition, AI offers an opportunity for investors to not only act responsibly, but also align their ESG goals to a profitable agenda. For example, algorithms are being developed that can connect specific ESG indicators to financial performance and can therefore be used by firms to identify the risk and reward of certain investments.
Whilst AI offers numerous opportunities with regards to ESG investing, it is not without fault. Firstly, AI takes enormous amounts of computing power and, hence, energy. For example, in 2018, OpenAI found the level of computational power used to train the largest AI models has been doubling every 3.4 months since 2012 (2). With the majority of the world’s energy coming from non-renewable sources, it is not difficult to spot the contradiction in motives here. We must also consider whether AI is being used to its full potential; when simply used to scan company published data, AI could actually reinforce issues such as “Greenwashing”. Further, the issue of fake news and unreliable sources of information still plagues such methods and a lot of work has to go into ensuring these sources do not feature in algorithms used.
When speaking with Dr Thomas Kuh, Head of Index at leading ESG data and AI firm Truvalue Labs™, he outlined the difficulties surrounding AI but noted that since it enables human beings to make more intelligent decisions, it is surely worth having in the investment process. In fact, he described the application of AI to ESG research as ‘inevitable’ as long as it is used effectively to overcome the shortcomings of current research methods. For instance, he emphasised that AI offers real time information that traditional sources simply cannot compete with.
A Future for AI?
According to a 2018 survey from Greenwich Associates (3), only 17% of investment professionals currently use AI as part of their process; however, 40% of respondents stated they would increase budgets for AI in the future. As an area where investors are seemingly unsatisfied with traditional data sources, ESG is likely to see more than its fair share of this increase. Firms such as BNP Paribas (4) and Ecofi Investissements (5) are already exploring AI opportunities and many firms are following suit. We at Leading Point see AI inevitably becoming integral to an effective responsible investment process and intend to be at the heart of this revolution.
AI is by no means the judge, jury and executioner when it comes to ESG investing and depends on those behind it, constantly working to improve the algorithms, as well as the analysts using it to make more informed decisions. AI does, however, have the potential to revolutionise what a responsible investment means and help reallocate resources towards firms that will create a better future.
[1] The problem with corporate greenwashing
[2] AI and Compute
[3] Could AI Displace Investment Bank Research?
[4] How AI could shape the future of investment banking
[5] How AI Can Help Find ESG Opportunities
"It takes twenty years to build a reputation and five minutes to ruin it"
AI offers an opportunity for investors to not only act responsibly, but also align their ESG goals to a profitable agenda
Environmental Social Governance (ESG) & Sustainable Investment
Client propositions and products in data driven transformation in ESG and Sustainable Investing. Previous roles include J.P. Morgan, Morgan Stanley, and EY.
Upcoming blogs:
This is the second in a series of blogs that will explore the ESG world: its growth, its potential opportunities and the constraints that are holding it back. We will explore the increasing importance of ESG and how it affects business leaders, investors, asset managers, regulatory actors and more.
Riding the ESG Regulatory Wave: In the third part of our Environmental, Social and Governance (ESG) blog series, Alejandra explores the implementation challenges of ESG regulations hitting EU Asset Managers and Financial Institutions.
Is it time for VCs to take ESG seriously? In the fourth part of our Environmental, Social and Governance (ESG) blog series, Ben explores the current research on why startups should start implementing and communicating ESG policies at the core of their business.
Now more than ever, businesses are understanding the importance of having well-governed and socially-responsible practices in place. A clear understanding of your ESG metrics is pivotal in order to communicate your ESG strengths to investors, clients and potential employees.
By using our cloud-based data visualisation platform to bring together relevant metrics, we help organisations gain a standardised view and improve your ESG reporting and portfolio performance. Our live ESG dashboard can be used to scenario plan, map out ESG strategy and tell the ESG story to stakeholders.
AI helps with the process of ingesting, analysing and distributing data as well as offering predictive abilities and assessing trends in the ESG space. Leading Point is helping our AI startup partnerships adapt their technology to pursue this new opportunity, implementing these solutions into investment firms and supporting them with the use of the technology and data management.
We offer a specialised and personalised service based on firms’ ESG priorities. We harness the power of technology and AI to bridge the ESG data gap, avoiding ‘greenwashing’ data trends and providing a complete solution for organisations.
Leading Point's AI-implemented solutions decrease the time and effort needed to monitor current/past scandals of potential investments. Clients can see the benefits of increased output, improved KPIs and production of enhanced data outputs.
Implementing ESG regulations and providing operational support to improve ESG metrics for banks and other financial institutions. Ensuring compliance by benchmarking and disclosing ESG information, in-depth data collection to satisfy corporate reporting requirements, conducting appropriate investment and risk management decisions, and to make disclosures to clients and fund investors.
Scaling a cyber-security FinTech with our interim COO leadership
"Leading Point have been instrumental in helping us cover our COO needs at a critical stage for the business from a product readiness and a go-to-market perspective. They have developed our client implementation capability with fit-for-purpose processes, systems and methodologies, significantly improving our engagement with our target customers and our time to market. We look forward to our continued alliance with Leading Point as our implementation partner to help us grow in the right way."
CEO @ Information & Cyber Risk Startup
Time to Reset?
We see the varnish from the old oil painting of government, enterprise, business and leadership fade a bit every day. 2020 has already shown us how interconnected our world has become - a true Butterfly Effect. Interconnectivity is not a bad thing. It is the fragility, the brittleness of modern economies that is cause for concern. I believe this is a result of critical imbalances we have allowed to build up, without questioning. Now as the varnish from the old oil painting comes off, we have a once in a decade opportunity to reset and tackle these imbalances. To make bold brush strokes.
Where can we start?
Big Government or Small?
Do we need a Big Government or Small? The term ‘Big Government’ here is not intended to be derogatory. We see national priorities and decisions that don’t match that of the city, the village, or the council. Great plans and budgets that don’t translate into change on the ground. Equally, in the face of this crisis, we see barriers breaking down. A C-19 COVID Symptom tracker app, which each of us can use, allows a judicious allocation of scarce testing and treatment resources at a national and grassroot level. The opportunity is to examine the flow from the national to the level of council. Provide transparency and allow engagement. If it doesn't exist it should be created. Direct channels for us citizens to highlight problems, propose solutions, be data-driven and monitor implementation. It is not a question of a big government versus small. It is one that works transparently that matters.
Public or Private Sector Enterprise?
A key debate going into 2020 was about which sector provides a better service, is more efficient with resources - private or public sector enterprise? Think about the NHS, Transport, Energy, Manufacturing, Financial Services, Agriculture, Technology and Utilities. Healthy arguments and examples are cited to show the merits of both public and private sector. I believe the public-private argument completely misses the point. Whether an enterprise provides a good service or poor, spends judiciously or not is not down to public or private sector. It is down to some key principles - how it is governed, how accountable is its team and partners, does it know what good service looks like and is it equipped to provide these services. Enterprises can be funded by either public or private sector resources. The opportunity ahead is in data and tech enabled service delivery models, going digital. And public-private collaboration funding models can ignite innovation and value added services. The key to provide good service is not public or private sector, it is to provide a good service!
Role of Business
Businesses are standing out in two ways in these times. Those that care about their employees and partners and are doing their bit to help their communities and those that pretend to. People will remember businesses that care. Those that don't, will fall out of favour. That most of our essential "front line" staff in the face of a pandemic are paid low/ minimum wages is cowardly. It shows the scale of imbalances we have allowed to build up and seem to be comfortable with. Colleagues in maintenance, cleaning, nursing, restaurant, retail, agriculture, driving, security, manufacturing and teaching professions amongst others need to be compensated fairly. The opportunity here is to go after skewed compensation models, unviable business models and poor productivity with vigour. The tax structures reportedly exploited by big tech and conglomerates are ripe for reform and become principle driven. Likewise business owners having billions and calling for government bailouts or larger profitable companies using furlough schemes to offload their responsibilities to the public should face the consequence. This is a failure of law and the will of successive governments. Let us get it right this time. Bashing businesses and entrepreneurs is not the answer. They are born from the risk-reward equation and are the lifeblood of any economy.
Lessons in Leadership
As much as it is tempting to draw leadership lessons from the current pandemic, they are unique to the situation and not a one size fits all. But I find the war analogy somewhat flawed. The chancellor of the exchequer, Rishi Sunak said “we will be judged by our capacity for compassion and individual acts of kindness” – does that sound like a war? If anything, the lesson for future leaders is to be that much more focused on ensuring their team’s wellbeing, ensuring they are equipped with relevant resources. Good leaders will understand the importance of the informal and the invisible stuff – collaboration, unconventional thinking, meaningful conversations and problem solving over formal organisation structures. The world we have to navigate in is increasingly unpredictable and non-linear, command and control team structures and top-down change will not work.
Everyday we are seeing concrete examples of what is working in business, government and leadership and what is not. We can allow 2020 to be one mired in tragedy, lost lives, lost livelihoods and failed businesses or we can seize the once in a decade opportunity to reset and create the government, the enterprise, the business and leaders that we want and have lacked for some time. This is within reach.
What steps do you think will help create better business, government and leaders?
Please feel free to comment and share. Keep well!
Change leader with over 20 years’ experience in helping financial markets with their toughest business challenges in data, operating model transformation in sales, CRM, Ops, Data, Finance & MI functions, and delivery of complex compliance, front-to-back technology implementations. Significant line experience. Former partner in management consulting leading client solution development, delivery and P&L incl. Accenture. Specialities – Operating Models, Data Assets, Compliance, Technology Partnerships & Solutions in Capital Markets, Market Infrastructure, Buy-Side, Banking & Insurance.
"2020 has already shown us how interconnected our world has become - a true Butterfly Effect."
"It is not a question of a big government versus small. It is one that works transparently that matters."
"Businesses are standing out in two ways in these times. Those that care about their employees and partners and are doing their bit to help their communities and those that pretend to."
"We can allow 2020 to be one mired in tragedy, lost lives, lost livelihoods and failed businesses or we can seize the once in a decade opportunity to reset and create the government, the enterprise, the business and leaders that we want and have lacked for some time"
Legal Technology in FS – The need for a new legal services operating model
Law, data, machines – these are not words that historically have had much to do with one another.
However, as the number of laws increases, communications traffic increases, and, as the fabric of the law can be read by machines, the interaction between these words will become ever more important.
90% of data in the world has been created in the last two years – and it’s not slowing down. [1] As regulation increases, the ability of financial institutions to manage the legal risk flowing from that regulation becomes ever more challenged. The resources being devoted to this increase every year and lawyers are starting to turn to technology to assist.
Recent research[2] found 82% of General Counsel have introduced various forms of technology into their department but 60% of lawyers don’t understand how that technology could help them. This, at a time where the pressure on resources (both human and financial) means that there is a real need for technological assistance.
The regulatory environment has imposed an unprecedented burden on firms. Legal risk has become increasingly complex and difficult to manage but is under-examined and often poorly understood. Due to the massive technological, political, regulatory and cultural shift over the past 30 years, the model by which we manage legal risk is outdated. This has led to increased fines, customer loss and higher operational costs at the least.
Poor management of data results in missed opportunities and increased costs as businesses rerun regulatory change and other projects. Effective management and exploitation of legal data could provide new business opportunities in addition to saving costs for business as usual (BAU). There needs to be a more formalised data flow between Business and Legal, leading to an effective and efficient end-to-end framework.
The in-house legal model needs to change. Technology can help.
But while the market is saturated with ‘RegTech’ and other legal solutions, these are disparate point solutions that do not address the underlying issues. Lawyers are reluctant to spend time training machines unless results are proven. This reluctance has resulted in suboptimal take up of the various solutions.
Machines are best at repetitious, low level tasks. Much of the law is to do with context, relationships between ideas and situations and nuance at which humans are better. While the race is on for machines to solve the problem of unstructured data, a tool pointed currently at the unstructured data lake that is ‘legal data’ results in unhelpful returns.
A new legal services operating model is needed to diminish the disjointed nature of legal and business issues. This new operating model needs to take into account not only new technology, but also the underlying data efficiencies to appropriately assemble and deploy solutions seamlessly across legal and business units.
Firms can gain most value by structuring data to best deploy legal technology. If firms do not make decisions about these issues now they will find themselves trapped in a never-ending loop of manually adjusting data to achieve the required results.
The hardest part of adoption of an “in the round” solution is implementing a framework within the firm which allows the various legal software tools to work optimally. A clear pathway needs to be created to reduce silos, create standards, appoint golden sources and create an enterprise architecture.
Law, data and machines can all work together successfully but it will take vision and hard work.
[This is part 1 of a 10 part series where we will consider the role of Legal Technology within Financial Services, how it can and should be applied, and what a ‘utopian’ target operating model for in-house legal departments looks like in FS]
[1] Presentation by Dr Joanna Batstone, VP IBM Watson & Cloud Platform, Legal and Technology Procurement 2018 – Thomson Reuters conference 8 November 2018
[2] Legal Technology: Looking past the hype, LexisNexis UK, Autumn 2018
There needs to be a more formalised data flow between Business and Legal, leading to an effective and efficient end-to-end framework.
A new legal services operating model is needed that takes into account not only new technology, but also the underlying data efficiencies to appropriately assemble and deploy solutions seamlessly across legal and business units.
the market is saturated with ‘RegTech’ and other legal solutions, these are disparate point solutions that do not address the underlying issues.
Excel Ninjas & Digital Alchemists – Delivering success in Data Science in FS
In February 150+ data practitioners from financial institutions, FinTech, academia, and professional services joined the Leading Point Data Kitchen community and were keen to discuss the meaning and evolving role of Data Science within Financial Services. Many braved the cold wet weather and made it across for a highly productive session interspersed with good pizza and drinks.
Our expert panellists discussed the “wild” data environment in Financial Services inhabited by “Excel Ninjas”, “Data Wranglers” and “Digital Alchemists”. But agreed that despite the current state of the art being hindered by legacy infrastructure and data siloes there are a number of ways to find success.
Here is the Data Kitchen’s ‘Recipe’ for delivering success in Data Science in Financial Services:
1. Delivery is key – There is a balance to strike between experimentation and delivery. In commercial environments, especially within financial services there is a cost of failure. ROI will always be in the minds of senior management, and practitioners need to understand that is the case. This means that data science initiatives will always be under pressure to perform, and there will be limits on the freedom to just experiment with the data.
2. Understand how to integrate with the business – Understanding what ‘good’ delivery looks like for data science initiatives requires an appreciation of how the business operates and what business problem needs to be solved. Alongside elements of business analysis, a core skill for practitioners is knowing how to ‘blend in’ with the rest the business – this is essential to communicate how they can help the business and set expectations. “Data translators” are emerging in businesses in response.
3. Soft skills are important – Without clear articulation of strategy and approach, in language they can understand, executives will often either expect ‘magic’ or will be too nervous to fully invest. Without a conduit between management and practitioners many initiatives will be under-resourced or, possibly worse, significantly over-resourced. Core competencies around stakeholder and expectation management, and project management is needed from data practitioners and to be made available to them.
4. Take a product mindset – Successful data science projects should be treated in a similar way to developing an App. Creating it and putting it on the ‘shelf’ is only the beginning of the journey. Next comes marketing, promotion, maintenance, and updates. Many firms will have rigorous approaches to applying data quality, governance etc. on client products, but won’t apply them internally. Many of the same metrics used for external products are also applicable internally e.g. # active users, adoption rates etc. Data science projects are only truly successful when everyone is using it the way it was intended.
5. Start small and with the end in mind – Some practitioners find success with ‘mini-contracts’ with the business to define scope and, later, prove that value was delivered on a project. This builds a delivery mindset and creates value exchange.
6. Conduct feasibility assessments (and learn from them) – Feasibility criteria need to be defined that take into account the realities of the business environment, such as:
- Does the data needed exist?
- Is the data available and accessible?
- Is management actively engaged?
- Are the technology teams available in the correct time windows?
If you run through these steps, even if you don’t follow through with a project, you have learned something – that learning needs to be recorded and communicated for future usage. Lessons from nearly 100+ use cases of data science in financial services and enterprises, suggest that implementing toll-gates for entry and exit criteria is becoming a more mature practice in organisations.
7. Avoid perfection - Sometimes ‘good’ is ‘good enough’. You can ‘haircut’ a lot of data and still achieve good outcomes. A lot of business data, while definitely not perfect, is being actively used by the business – glaring errors will have been fixed already or been through 2-3 existing filters. You don’t always need to recheck the data.
8. Doesn’t always need to be ‘wrangled’ – Data Scientists spend up to 80% of time on "data cleaning" in preparation for data analysis but there are many data cleansing tools now in the market that really work and can save a lot of time (e.g. Trifacta). Enterprises will often have legacy environments and be challenged to connect the dots. They need to look at the data basics – an end to end data management process, the right tools for ingestion, normalisation, analysis, distribution and embedding outputs as part of improving a business process or delivering insights.
Our chefs believed Data Science will evolve positively as a discipline in the next three years with more clarity on data roles, a better qualification process for data science projects, application of knowledge graphs, better education and cross pollination of business and data science practitioners and the need for more measurable outcomes. The lessons from failures are key to make the leap to data-savvy businesses.
Just a quick note to say thank you for your interest in The Data Kitchen!
We had an excellent turn out of practitioners from organisations including: Deutsche Bank, JPMorgan, HSBC, Schroders, Allianz Global Investors, American Express, Capgemini, University of East London, Inmarsat, One corp, Transbank, BMO, IHS Markit, GFT, Octopus Investments, Queen Mary University, and more.
And another Thank You to our wonderful panellists!
- Peter Krishnan, JP Morgan
- Ben Ludford, Efficio
- Louise Maynard-Atem, Experian
- Jacobus Geluk, Agnos.ai
…And Maître De – Rajen Madan, Leading Point FM
We would like to thank our chef’s again and to all participants for sharing plenty of ideas on future topics, games and live solutions.
LIBOR Signals Need for New Approaches to Legal Data
The Scope of LIBOR Remediation is the Problem
Time is now of essence – with the end of 2021 deadline looming, financial institutions need to reduce their ‘stock’ of legacy LIBOR contracts to a minimum as a matter of priority, writes Rajen Madan, CEO, Leading Point.
The challenge is of course colossal. Firms need to find every reference to IBORs embedded in every contract they hold; update each contract with fallback provisions / reflect the terms of the alternative reference rate they are migrating to; and communicate the results with clients.
LIBOR’s retirement potentially impacts over $350 trillion of contracts and requires all LIBOR transactions (estimated at over 100 million documents) to be examined and most likely repapered. LIBOR is embedded in every asset class – mortgages and retail loans, to commodities, derivatives, bonds and securities.
It’s estimated that large banks may be exposed to more than 250,000 contracts directly referencing LIBOR maturing after 2021, and indirectly exposed to many thousands more embedded in servicing activities, supplier agreements and such.
Only 15 percent of Financial Institutions are ready to deal with this volume of contract remediation, deal restructuring, and repapering activities required for the scale of their legacy contract back-book; 14 of the world’s top banks expect to spend more than $1.2 billion on the LIBOR transition.
Firms that have comprehensive visibility of their legal contract information via retained structured data, can avoid 80 percent of the typical repapering process, and focus their efforts on the remaining, critical, 20 percent.
LIBOR Repapering Not a ‘Find and Replace’
The repapering of contracts isn’t as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR.
Risks are many including conduct, legal, prudential and regulatory. Consider ‘conduct’ risk. In the UK, the Treating Customers Fairly (TCF) regime is particularly concerned with how customers are affected by firms’ LIBOR transition plans. Before contracts can be updated, firms will need to ensure that LIBOR linked products and services have ‘fair’ replacement rates that operate effectively.
Similarly, there’s prudential risk. When the underlying contracts change, firms may find that the instruments they rely on for capital adequacy purposes may no longer be eligible, potentially even resulting in a sudden drop in a bank’s capital position. Similarly, there are several Counterparty Credit, Market, Liquidity, and Interest Rate Risks that will need to be reflected in firms’ approaches.
LIBOR is proving to be a real impetus for financial institutions to use technology that, to be honest, has been available in the marketplace for a long time now.
Mindset Change is Needed to Manage Legal Data
Most historic repapering exercises have involved hastily identifying the documents impacted, outsourcing the difficult issues to law firms (at huge cost) and throwing manpower (again at substantial cost) at the problem to handle the contract updates and communications with counterparties. The exact same process has been repeated for every repapering project. Despite the substantial costs, many financial institutions still don’t meet the deadline. MiFID II is an example.
With ample evidence of regulators continually tightening their grip on financial institutions through reform – alongside an increasingly dynamic global business environment (e.g. LIBOR, Brexit) – it is time organisations acknowledged and accepted repapering as a ‘business as usual’ activity.
A change in mindset and a smarter approach is needed to manage legal data. Financial institutions need to ensure that LIBOR or indeed any future business repapering exercise does not compromise client well-being or negatively impact client experience. For instance, to accurately model the financial risk firms’ portfolios are exposed to via LIBOR when transitioning to a new rate, they need a way to directly link, say, multiple cash and derivative contracts to a single client. Furthermore, in an environment where most firms are product driven, the scenario of multiple repetitive communications, requests for information and re-papering contract terms looms on the horizon for firms’ customers.
It is heartening to see that LIBOR is beginning to pique the interest of financial institutions to develop a long-term vision to create smarter capabilities that will deliver business advantages in the future.
Stephanie Vaughan, Global Legal AI Practice Director at iManage RAVN and ex-Allen & Overy, recently observed, “LIBOR is proving to be a real impetus for financial institutions to use technology that, to be honest, has been available in the marketplace for a long time now. While they may have dabbled with it in the past, due to the scale of the LIBOR remediation and the constantly changing regulatory challenges, it has finally hit home that such projects are a drain on resources and are delivering no business value.”
Financial institutions have started every repapering project (e.g. MiFID II, Dodd Frank, Margin Rules) from scratch including going through the entire process of determining the clients, what the terms of engagement are, when the contracts expire and so on.
Technology Can Make Repapering ‘Business as Usual’
A strategic approach to managing legal data requires all stakeholders in a financial institution to come on board – from business units and the compliance department through to legal operations and the General Counsel. This is instrumental to ensuring genuine cross-functional recognition and support for strategic directional change.
Financial institutions need to build a strong, technology-supported foundation for remediation projects. Thus far, financial institutions have started every repapering project (e.g. MiFID II, Dodd Frank, Margin Rules) from scratch including going through the entire process of determining the clients, what the terms of engagement are, when the contracts expire and so on.
Hereafter, with LIBOR and Brexit, extracting, classifying, storing and maintaining all these data points as structured, base level information on customers on a single technology platform, will provide institutions with capabilities to quickly understand their exposure, assign priorities and flexibly make contractual changes in tune with evolving requirements.
This approach is proven. Firms that have comprehensive visibility of their legal contract information via retained structured data, can avoid 80 percent of the typical repapering process, and focus their efforts on the remaining, critical, 20 percent. Financial institutions will then also be well poised to take advantage of new bolt on capabilities that leverage artificial intelligence for application to specific use-cases – which in turn can deliver business value from contract search, contract classification, clause management, to real time analytics, contract generation and integration with operational, risk and compliance systems.
The opportunity with more effective legal data management is huge and realisable. Building and incrementally strengthening capability through the strategic and proactive use of technology is potentially the only way for financial institutions to adapt to their new regulatory and business environment.
The repapering of contracts isn’t as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR.
LIBOR: Manual Approaches are no Longer Enough to Manage FS Legal Data
The transition away from LIBOR is the biggest contract remediation exercise in Financial Services history – and firms are under prepared.
As the Bank of England and FCA lays out in bold font, in their January 2020 letter to CEOs, “LIBOR will cease to exist after the end of 2021. No firm should plan otherwise.”[1] As a result, Financial Institutions have very little time to reduce their “stock of legacy LIBOR contracts to an absolute minimum before end-2021”.
The challenge is this:
1. Firms have to find every reference to IBORs embedded in every contract they hold.
2. Update each contract with fallback provisions or to reflect the terms of the alternative reference rate they are migrating to.
3. Communicate the results with clients
This is much easier said than done due to the sheer scale of the task.
LIBOR’s retirement has the potential to impact over US$ 350 trillion of contracts and will require all LIBOR transactions (estimated at over 100 million documents) to be examined and most likely repapered. LIBOR is embedded in far more than just derivative contracts. Every asset class is affected; from mortgages and retail loans, to commodities, bonds or securities. The resolution of Lehman Brothers after 2008 gives some idea of the scale of the repapering effort for each firm – Lehman was party to more than 900,000 derivatives contracts alone.
The scope of the problem is part of the problem. Hard numbers are difficult to come by as no-one really knows exactly what their exposure is, or how many contracts they need to change.
Current estimates say large banks’ may be exposed to more than 250,000 contracts directly referencing LIBOR maturing after 2021, and indirectly exposed to many thousands more embedded in servicing activities, supplier agreements or more.
Only 15% of Financial Institutions are ready to deal with this volume of contract remediation, deal restructuring, and repapering activities required for the scale of their legacy contract back-book.[2] Fourteen of the world’s top banks expect to spend more than $1.2 billion on the LIBOR transition[3].
To approach the LIBOR transition manually will likely require years of man-hours and cost millions of dollars, with significant potential for human error
There are a wide variety of risks to consider.
But it’s not as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR. Firms face huge operational, conduct, legal and regulatory risk arising from both the difficulties in managing the vast volumes of complex client contractual documentation but also the downstream impacts of that documentation having been changed.
Conduct Risk: In the UK, the Treating Customers Fairly (TCF) regime is particularly concerned with how customers are affected by firms’ LIBOR transition plans. Before contracts can be updated, firms will need to ensure that LIBOR linked products and services have ‘fair’ replacement rates that operate effectively.[1] Firms will also need to ensure that any changes made are applied across the entire customer ‘class’ to comply with TCF rules and avoid preferential treatment issues.
Legal Risk: There is a huge amount of legal risk arising from disputes in what interest rates should be paid out in amended agreements referencing alternative reference rates.[2] The ISDA protocol expected to be published in Q2 2020 should help with, but not solve, these problems.[3]
This is not to mention the legacy contracts that cannot legally be converted or amended with fallbacks – named by Andrew Bailey at the FCA as the ‘tough legacy’.[4] The UK Working Group on Sterling Risk Free Reference Rates (RFRWG) is due to publish a paper on ‘tough’ legacy contracts in the second half of Q1 2020.[5]
The realism of firms’ assessments of the number of contracts requiring renegotiation should be considered a legal risk in itself – a realised 10% increase in this number would likely incur serious, additional legal fees.
Prudential Risk: When the underlying contracts change, firms may find themselves in a position where suddenly the instruments they rely on for capital adequacy purposes may no longer be eligible - “This could result in a sudden drop in a bank’s capital position.” [6] For similar reasons, there are a number of Counterparty Credit, Market, Liquidity, and Interest Rate Risks that will need to be reflected in firms’ approaches.
Regulatory Risk: Regulators are closely monitoring firms’ transition progress – and they are not happy with what they are seeing. Financial Policy Committee (FPC) stated in January, 2020, has made clear that they are ‘considering’ the supervisory tools that authorities could use to “encourage the reduction in the stock of legacy LIBOR contracts to an absolute minimum before end-2021.”[7] This is regulatory code for ‘we will either fine or increase the capital requirements for firms we judge to be dropping the ball’. The PRA and FCA laid out their expectations for the transition in June 2019 – this is required reading for any LIBOR transition project manager.[8]
It’s not as straightforward as a ‘Find and Replace’ on legal terminology referencing LIBOR
What this means for firms is that they need:
1. The capability to quantify their LIBOR exposure – Firms need a good understanding of their LIBOR contractual exposure that can quantify a) firms’ contractual population (i.e. which documents are affected) b) the legal, conduct and financial risk posed by the amendment of those documents
2. The ability to dynamically manage and track this exposure over time – As strategies evolve, the regulatory environment changes, and new scenarios develop, so will firms’ exposure to LIBOR change. Without good quality analytics that can track this effectively, in the context of this massive change project, firms will be strategically and tactically ‘flying blind’ in the face of the massive market shifts LIBOR will bring about.
3. The capability to manage documentation - Jurisdictional, product, or institutional differences will necessitate large client outreach efforts to renegotiate large populations of contracts, manage approvals & conflict resolution, while tracking interim fall-back provisions and front office novation of new products to new benchmarks.
Accomplishing the above will require enterprise-wide contract discovery, digitisation, term extraction, repapering, client outreach and communication capabilities – and the ability to tie them all together in a joined-up way.
To approach the LIBOR transition manually will likely require years of person-hours and cost millions of dollars, with significant potential for human error.
Accomplishing the above will require enterprise-wide contract discovery, digitisation, term extraction, repapering, client outreach and communication capabilities – and the ability to tie them all together in a joined-up way
LIBOR cannot be treated as ‘just one more’ repapering exercise.
Firms are continually hit with new requirements which require the update, negotiation and amendment of client contracts.
The reaction is always the same: Scramble to identify the documents impacted, outsource the thornier problems to external legal, and hire huge teams of consultants, remediation armies and legal operations to handle the contract updates and communications with counterparties.
Once complete - often months past the deadline - everyone stands down and goes home. Only to do the same thing again next year in response to the next crisis. While this gets the job done, there are number of problems with this project by project approach:
1. It’s inefficient: Vast amounts of time (and money) is spent just finding the documents distributed around the business, often in hard copy, or locked away in filing cabinets.
2. It’s expensive: External legal, consultants and remediation shops don’t come cheap – especially when the scope of the project inevitably expands past the initial parameters.
3. It’s ineffective: Little to no institutional knowledge is retained of the project, no new processes are put in place, and documents continue to get locked away in filing cabinets - meaning when the time comes to do it again firms have to start from scratch.
When you look at the number of major repapering initiatives over the past 10 years the amount of money spent on repapering projects is monumental. In the EU alone, regulations such as MiFID II, EMIR, GDPR, PPI, FATCA, Brexit and AIFMD have each required a huge repapering project. In 2020, LIBOR, Initial Margin Rules and SFTR will each require contract remediation programmes.
Doing ‘just another’ repapering exercise for LIBOR is a risky mistake. There is a better way.
Smarter data management and enabling tech solutions can help identify, classify and extract metadata from the huge volumes of LIBOR impacted documents at speed. The ability to extract and store contractual information as structured information at this scale allows firms’ the essential capabilities to understand and track their LIBOR exposure, assign priorities and maintain flexibility in a changing situation.
Firms that have fuller visibility of their legal contract information, retained as structured data, can avoid 80% of the typical repapering process, and focus their efforts on the remaining, critical, 20%.[1] The time spent manually identifying contractual needs, can be reallocated to the areas that matter, freeing up legal resource, budget, and project timelines – while simultaneously improving client relationships.
This should not be seen just as a repapering enabler, but a strategic capability. The opportunities afforded through data mining firms’ contractual estate for analytics are vast.
Doing ‘just another’ repapering exercise for LIBOR is a risky mistake. There is a better way
One possibility is the ability to connect contracts directly to trades. To accurately model the financial risk firms’ portfolios are exposed to via LIBOR when transitioning to a new rate, they will need a way to directly link, for example, multiple cash and derivative contracts to a single client. Firms are still a long way from this capability – but there are a growing number of sophisticated artificial intelligence solutions that can begin to address these types of use-cases.
Firms that build these capabilities now will materially reduce their risk exposures, improve liquidity and funding, build trust with their clients and be much better equipped to meet other pressing regulatory requirements such as Brexit, SFTR, CRD 5/6, Initial Margin (IM) rules, QFC and more.
[1] ‘Next steps on LIBOR transition’, January 2020, FCA & PRA https://www.fca.org.uk/publication/correspondence/dear-smf-letter-next-steps-libor-transition.pdf
[2] 2019 LIBOR Survey: Are you ready to transition?, September 2019, Accenture. https://www.accenture.com/_acnmedia/109/Accenture-2019-LIBOR-Survey-fixed.pdf#zoom=50
[3] ‘The end of Libor: the biggest banking challenge you've never heard of’, October 2019, Reuters.
[4] Firms will also need to consider whether any contract term they may rely on to amend a LIBOR-related product is fair under the Consumer Rights Act 2015 (the CRA) in respect of consumer contracts. FG18/7: Fairness of variation terms in financial services consumer contracts under the Consumer Rights Act 2015 contains factors that firms should consider when thinking about fairness issues under the CRA when they draft and review unilateral variation terms in their consumer contracts. https://www.fca.org.uk/markets/libor/conduct-risk-during-libor-transition
[5] Litigation risks associated with Libor transition: https://collyerbristow.com/longer-reads/litigation-risks-associated-with-libor-transition/
[6] UK Working Group on Sterling Risk-Free Reference Rates (RFR WG) 2020 Top Level Priorities. https://www.bankofengland.co.uk/-/media/boe/files/markets/benchmarks/rfr/rfrwgs-2020-priorities-and-milestones.pdf?la=en&hash=653C6892CC68DAC968228AC677114FC37B7535EE
[7] LIBOR: preparing for the end, https://www.fca.org.uk/news/speeches/libor-preparing-end
[8] UK Working Group on Sterling Risk-Free Reference Rates (RFR WG) 2020 Top Level Priorities. https://www.bankofengland.co.uk/-/media/boe/files/markets/benchmarks/rfr/rfrwgs-2020-priorities-and-milestones.pdf?la=en&hash=653C6892CC68DAC968228AC677114FC37B7535EE
[9] Letter from Sam Woods: The prudential regulatory framework and Libor transition, Bank of England, https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/letter/2019/prudential-regulatory-framework-and-libor-transition.pdf?la=en&hash=55018BE92759217608D587E3C56C0E205A2D3AF4
[10] ‘Next steps on LIBOR transition’, January 2020, FCA & PRA https://www.fca.org.uk/publication/correspondence/dear-smf-letter-next-steps-libor-transition.pdf
[11] ‘Firms’ preparations for transition from London InterBank Offered Rate (LIBOR) to risk-free rates (RFRs): Key themes, good practice, and next steps.’, June 2019, FCA & PRA https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/2019/firms-preparations-for-transition-from-libor-to-risk-free-rates.pdf?la=en&hash=EA87BD3B8435B7EDF25A56C932C362C65D516577
[12] MiFID II – the long tail of legal documentation repapering, https://www.fintechfutures.com/2018/04/mifid-ii-the-long-tail-of-legal-documentation-repapering/
Intersecting the Old World with the New
It has always been a challenge for large corporations to adopt change. There is constant change being experienced at all institutions but, despite the appetite for change, the size of an organisation often hamstrings its ability to execute on innovative initiatives.
So, what differentiates those who can deliver successful change versus those who cannot? In one word: Execution!
Execution is the biggest differentiator between small, agile and nimble businesses and their much larger counterparts. Even if you put to one side the classic large corporate roadblocks (such as organisational complexity and bureaucracy), it’s clear that those who decide to take the leap of faith and try to change the world by starting their own businesses seem to be able to avoid and, often, ignore convention to deliver significant change.
Innovation in large organisations must pass through many layers of change management and control which frequently ties the hands of those who are the agents of change. Equally frequently, organisational politics have an adverse impact. This is not true of ‘Upstarts’.
‘Upstarts’ break the glass ceiling of ‘the norm’ to create change by significantly improving an existing system or reinventing a process, convention, etc. But one must question why it is easier for Upstarts to achieve significant change where larger organisations struggle and fail to achieve the same success.
Is it because Upstarts have more skills or able people to execute change? Probably not, although one must believe Upstart people form a more focused collective. It’s much simpler than that – it’s a matter of having the time and inclination to apply that collective focus to the achievement of a single objective. Having, as a sole objective, creating and delivering industry augmenting technology will result in an executable product roadmap and realistic delivery timelines.
Execution is the biggest differentiator between small, agile and nimble businesses and their much larger counterparts
However, there is one area in which large corporates have the upper hand: domain expertise. Upstarts, by virtue of their size, generally do not have the breadth of expertise of larger organisations. There are many Upstarts who are capable and indeed do produce top of the line tech solutions. However, often these same single solutions providers (focus!) struggle to appreciate and navigate the vast array of problems large FS organisations are looking to address. Due to these information gaps, solutions can often result in not being fully fit for purpose and therefore hinder an Upstarts ability to precisely satisfy the needs of large FS corporates.
In addition, large organisations have deep pockets. This allows them to research and develop solutions internally or to attract external innovation by setting up Innovation Labs, or both. The main objective of these Labs is to experiment with and identify the kind of innovation that will create competitive advantage. Upstarts may find themselves part of the Innovation Lab or even acquired in the process.
While Innovation Labs may ensure large players don’t get left behind, there is a big opportunity being missed. This is the integration of external innovation with internal processes and capabilities. Acquisitions should be aligned with internal use cases i.e. known (or guessed at) issues with existing business workflows such as efficiency gains. The main reason seems to be that each is located in its own silo.
Having, as a sole objective, creating and delivering industry augmenting technology will result in an executable product roadmap and realistic delivery timelines
So internal use cases (areas in need of improvement and change) are not connected to potential external innovative solutions. And this is not to speak of the bigger challenge which is to identify those use cases in the first place. This raises a number of questions:
- Does the right type of resource exist?
- Can available internal staff ask the right questions?
- Is an independent party better placed to conduct such an exercise?
- Will this be prevented by internal politics?
- Who’s going to pay for the work?
- Who’s going to take ownership?
- … and the list goes on.
Successful organisations engage the right people at the right level internally as well as identify and breakdown the ability of Upstarts to address wide ranging and often long-standing issues. This takes a certain type of skill set including
- The ability to face off across the corporate spectrum
- Applying the correct level of domain expertise and insight, and
- The ability and expertise to collaborate with Upstarts; to name but a few.
Entrepreneurs, especially the good ones, know that if failure is to happen, it happens fast. This requires the ability to EXECUTE.
The common thread: entrepreneurship. Why?
Entrepreneurs, especially the good ones, know that if failure is to happen, it happens fast. This requires the ability to EXECUTE. Getting the job done is very high on the agenda for any entrepreneur. Lateral and cohesive thinking is also vital. Steve Jobs once said, “creativity is just merging things” and entrepreneurs do this better than anyone and tend to find ways through means others don’t or won’t pursue through such approaches as marginal gains.
Entrepreneurs don’t have all the answers. Not at all. But to bridge the gap between larger, more conventional-minded organisations and newer Upstarts, one must have the ability to “intersect the old world with the new”. An excellent example of this was the event we ran Data Innovation Uncovered and the work we continue to do in the FinTech space including in Enterprise Blockchain and Client Lifecycle Management.
We love to talk about this intersection and encourage free and open conversation so please feel free to get in touch to share your thoughts or indeed to hear more of ours.
To bridge the gap between larger, more conventional-minded organisations and newer Upstarts, one must have the ability to “intersect the old world with the new”
LIBOR Transition - Preparation in the Face of Adversity
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
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
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
“[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)
“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
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)
Data Innovation, Uncovered
Leading Point Financial Markets recently partnered with selected tech companies to present innovative solutions to a panel of SMEs and an audience of FS senior execs and practitioners across 5 use-cases Leading Point is helping financial institutions with. The panel undertook a detailed discussion on the solutions’ feasibility within these use-cases, and their potential for firms, followed by a lively debate between Panellists and Attendees.
EXECUTIVE SUMMARY
“There is an opportunity to connect multiple innovation solutions to solve different, but related, business problems”
- 80% of data is relatively untapped in organisations. The more familiar the datasets, the better data can be used
- On average, an estimated £84 million (expected to be a gross underestimation) is wasted each year from increasing risk and delivery from policies and regulations
- Staying innovative, while staying true to privacy data is a fine line. Solutions exist in the marketplace to help
- Is there effective alignment between business and IT? Panellists insisted there is a significantly big gap, but using business architecture can be a successful bridge between the business and IT, by driving the right kinds of change
- There is a huge opportunity to blend these solutions to provide even more business benefits
CLIENT DATA LIFECYCLE (TAMR)
- Tamr uses machine learning to combine, consolidate and classify disparate data sources with potential to improve customer segmentation analytics
- To achieve the objective of a 360-degree view of the customer requires merging external datasets with internal in a appropriate and efficient manner, for example integrating ‘Politically Exposed Persons’ lists or sanctions ‘blacklists’
- Knowing what ‘good’ looks like is a key challenge. This requires defining your comfort level, in terms of precision and probability based approaches, versus the amount of resource required to achieve those levels
- Another challenge is convincing Compliance that machines are more accurate than individuals
- To convince the regulators, it is important to demonstrate that you are taking a ‘joined up’ approach across customers, transactions, etc. and the rationale behind that approach
LEGAL DOCS TO DATA (iManage)
- iManage locates, categorises & creates value from all your contractual content
- Firms hold a vast amount of legal information in unstructured formats - Classifying 30,000,000 litigation documents manually would take 27 years
- However, analysing this unstructured data and converting it to structured digital data allows firms to conduct analysis and repapering exercises with much more efficiency
- It is possible to a) codify regulations & obligations b) compare them as they change and c) link them to company policies & contracts – this enables complete traceability
- For example, you can use AI to identify parties, dates, clauses & conclusions held within ISDA contract forms, reports, loan application contracts, accounts and opinion pieces
DATA GOVERNANCE (Io-Tahoe)
- Io-Tahoe LLC is a provider of ‘smart’ data discovery solutions that go beyond traditional metadata and leverages machine learning and AI to look at implied critical and often unknown relationships within the data itself
- Io-Tahoe interrogates any structured/semi-structured data (both schema and underlying data) and identifies and classifies related data elements to determine their business criticality
- Pockets of previously-hidden sensitive data can be uncovered enabling better compliance to data protection regulations, such as GDPR
- Any and all data analysis is performed on copies of the data held wherever the information security teams of the client firms deems it safe
- Once data elements are understood, they can be defined & managed and used to drive data governance management processes
FINANCIAL CRIME (Ayasdi)
- Ayasdi augments the AML process with intelligent segmentation, typologies and alert triage. Their topological data analysis capabilities provide a formalised and repeatable way of applying hundreds of combinations of different machine learning algorithms to a data set to find out the relationships within that data
- For example, Ayasdi was used reason-based elements in predictive models to track, analyse and predict complaint patterns. over the next day, month and year.
- As a result, the transaction and customer data provided by a call centre was used effectively to reduce future complaints and generate business value
- Using Ayasdi, a major FS firm was able to achieve more than a 25% reduction in false positives and achieved savings of tens of millions of dollars - but there is still a lot more that can be done
DATA MONETISATION (Privitar)
- Privitar’s software solution allows the safe use of sensitive information enabling organisations to extract maximum data utility and economic benefit
- The sharp increase in data volume and usage in FS today has brought two competing dynamics: Data protection regulation aimed at protecting people from the misuse of their data and the absorption of data into tools/technologies such as machine learning
- However, as more data is made available, the harder it is to protect the privacy of the individual through data linkage
- Privitar’s tools are capable of removing a large amount of risk from this tricky area, and allow people to exchange data much more freely by anonymisation
- Privitar allows for open data for innovation and collaboration, whilst also acting in the best interest of customers’ privacy
SURVEY RESULTS
- Encouragingly, over 97% of participants who responded confirmed the five use cases presented were relevant to their respective organisations
- Nearly 50% of all participants who responded stated they would consider using the tech solutions presented
- 70% of responders believe their firms would be likely to adopt one of the solutions
- Only 10% of participants who responded believed the solutions were not relevant to their respective firms
- Approximately 30% of responders thought they would face difficulties in taking on a new solution
Innovation is Not Perfect. Accept and Embrace It
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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Rules of Data
On 24 October, it was reported that the Financial Conduct Authority launched an investigation into the US credit checking company Equifax; almost 700,000 Britons had their personal data misappropriated between mid-May and July this year. The FCA gave evidence on this matter to the Treasury Select Committee on 31 October because of the significant public interest. The FCA has the power to fine Equifax, or strip it of its right to operate in the UK, if it is found to have been negligent with its customers’ data. With European Union governments formally stating that cyber-attacks can be an ‘act of war,’ data protection cannot be taken seriously enough. The Equifax data breach is by no means a solitary data breach – several large organisations such as Dun & Bradstreet, Verifone, Whole Foods, Deloitte, DocuSign, Yahoo! are already part of the mix.
The Government is aligning domestic data legislation with the European Union in an effort at continuity, despite our plans to leave the EU. The Data Protection Bill, is proof that the Government seeks to keep the UK au courant with the newest data law of EU provenance.
The number of internet users is now close to 4 billion. Businesses continue to move their products and services online in order to service their customers. Data continues to grow exponentially and will persist in its travel far and wide – enabled by technology proliferation. The EU’s General Data Protection Regulation (‘GDPR’) has been precipitated by acute necessity. Companies need to review and revise their approach to privacy, security and governance of their data. A holistic, data protection framework is needed that is centred on the customer and encompasses their interactions, experience, sentiment, along with those of advocacy groups, shareholders, and regulators. This is a non trivial exercise and requires interventions at the mindset, policy, information governance & security and process levels, along with enabling technology.
Businesses are heading in the right direction with GDPR, but there is still a long way to go. Implementing this change with the right spirit is fundamental to building trust with customers and partners. Leading Point’s experience helping organisations with these requirements suggests that while significant compliance hurdles exist, a risk-based approach that focuses on five core areas, will be instrumental to success.
1. Give your customers control over their data – a mindset change
Bearing in mind the territorial scope of the GDPR – across the current 28 EU member states, plus, anyone dealing with the EU, most teams within organisations will benefit from the ethos behind the Regulation. A mindset shift from owning your customers’ data to stewarding your customers’ data is required. Give your customers control over their data. Any legal or natural person processing data must believe in the spirit of this sea change – the need
to assume responsibility for stewarding your customers’ data and to provide them with confidence in your processes. GDPR expands on the list of ‘rights’ each data subject is afforded: the right to be informed, the right to
access data records, the right to data erasure, to name a few. Tone at the top matters immensely.
2. Achieve Data Protection by Design
Which department is leading your organisation’s GDPR compliance efforts? A cross-functional team will help in deploying a holistic data protection framework. To start with, the focus must be on classification of the data, its
supply chain and its governance. Therefore, leveraging existing data management initiatives to embed data privacy requirements can really help in ‘data protection by design’. In practical terms, companies need a clear picture on: ‘what types of data do they hold on their customers;’ ‘which types of data is sensitive and requires enhanced security levels;’ ‘who has access to customers’ sensitive data;’ ‘where is this data processed and distributed;’ ‘how does it flow;’ ‘what is its quality;’ and ‘are their checks and controls in place around its flow and access’? The rules are more stringent now, as companies establish the depth of customer data – their interactions, experiences, sentiments – what impressions are left in an organisation’s data stores. The definition of personal data and its inherent breadth has been redefined – ‘Personal data shall be adequate, relevant and not excessive in relation to the purpose or purposes for which they are processed.’ And so the notion of data minimisation is born. We believe that while there are increasing numbers of quick-fix GDPR solutions in the market, achieving data protection goals is less about technology, and more about energising the organisation into becoming 100% data aware.
Building trust in your data will allow for effective process and controls for data protection, security and governance.
3. The Art of the Process
Focus must be on the ‘process’ exercise – visibility of customer journeys – which processes interact with customer data and the ensuing data lifecycle. Knowing which functions have client-facing processes and ensuring these are
adapted is called for. Threading through specific processes for data collection, data storage, data sharing, access requests and breaches is the focus. Having a command of what happens to personal data, who is involved in gathering it, and responding to Subject Access Requests is important, not least because you will have only a month to respond and cannot routinely charge the current £10. What steps to take in the event of a data breach, how to manage contracts which hold personal data: these are all explicit in the Regulation. For all data processors, we must double down on education and training – on policies, on data governance, on processes and new rules of data. This means highlighting a consistent approach to the different scenarios. Surely the best protection is a body of staff that is wholly informed?
4. Integrating data protection with a risk-based approach
By taking an inventory of obligations to customers via existing contracts and business agreements, organisations can start to manage their stated responsibilities linked to customer data and its management and use. This is a
quick-win.
Data classification and governance exercises will highlight the sensitivity, breadth and depth of data, the access and use of the data held. Data flow will highlight the data processors and third-parties and internal functions involved. Data quality will highlight where data management controls are required to be shored up. In turn, this will flag up priority remediation exercises on customer data.
The aforementioned ‘process’ exercise will highlight key customer-facing process changes, or a requirement to deploy specific data processes referenced by GDPR. Organisations can road-test these processes against the required process turn-around times. For example, data breaches must be reported within 72 hours, and as mentioned above, data subject access requests – one month. Involve your customer services team actively with data protection and security breach scenarios – this will build memory and promote mindset change.
The overarching governance in an organisation will be a key cog in the data protection ecosystem; the Regulation has duly led to the genesis of the Data Protection Officer. Enabling these responsibilities with existing data management governance responsibilities, and appointing data champions, can be an effective approach. Data protection is indisputably everyone’s responsibility, so the emphasis must be on organisational cooperation.
5. Cascading to Third Parties & a Cloud
Third party contracts and the framework that dictates how these are established, must wholeheartedly reflect any changes to the requisite data protection and security obligations. A compliance policy which standardises how third party contracts are established can also be a useful instrument. Data transference should be shored up with model contractual clauses, which allow all parties to clearly realise their responsibilities. We are alive to the persistent risk of cyber attacks, so it is crucial to remember that your data on the cloud is a business issue, as well as an IT issue. Are you fully apprised of where your business stores its data; on the premises, in the cloud, or both? The increasing trend to shift data and infrastructure to a public or private cloud no doubt presents an economic benefit and technology road map for some organisations. But make no mistake, organisations are accountable for their customer data content, its usage, and their security policy for cloud-based storage. Measures such as encryption, pseudonymisation and anonymisation will help, and should be employed as a matter of course, as well as remaining open to select technologies that help underpin cyber defence.
To conclude
When implementing change, evidence-based decision making shouldn’t be the only strategy; knowing which cogs in an organisation interlink cohesively in practice will greatly assist in a robust framework that threads through to
a mindset shift, policy, data, process and third parties. To reinforce an earlier perspective, data is only growing. So are data breaches and cyberattacks. The garnering of our data to feed algorithms and ‘machine learning’, borne
out of the Silicon Valley revolution, is leading to inevitable change in our lives, but we must strive for a democratic jurisdiction for our data. Organisations must give customers control of their data and the confidence in their data
management processes. Rather than penalty-based scaremongering, think of this as an opportunity to build your brand, to send a robust message to your customers and partners, demonstrating care and respect of their data.
To close, a soundbite from the Information Commissioner’s Office: ‘Data protection challenges arise not only from the volume of the data but from the ways in which it is generated, the propensity to find new uses for it, the complexity of the processing and the possibility of unexpected consequences for individuals.’
Leading Point Financial Markets brings compelling value in the intersection of Data, Compliance, Governance and Operating Model Change initiatives.