Jun 16, 2021

Refinitiv webinar: Reimagining banking post-COVID-19

digitalbanking
covid-19
Refinitiv
LondonStockExchangeGroup
2 min
A new webinar from Refinitiv, a London Stock Exchange Group business, promises to educate banking on post-COVID challenges, strategies, and opportunities

Currently available as an ‘on demand’ webinar (register to watch here), 'Reimagining Digital Banking: The Implications Post-Pandemic' acts as Refinitiv's guide for the banking industry during a time of unprecedented change.

The company is one of the world’s largest providers of data and infrastructure to the financial services market; at the time of writing, Refinitiv has over 40,000 customers and 400,000 end users spread across 190 countries and generates US$6.25bn in annual revenue.

Its acquisition in early 2021 by London Stock Exchange Group (LSEG) has only served to bolster its organisational strength and boost its services to the trading, banking, investment, wealth, third-party risk, and enterprise data sectors.

Refinitiv’s successful approach combines its open platform with cutting-edge data and leading expertise, granting customers both choice and opportunity. Its vision is driven by a desire to foster:

  • Financial inclusivity
  • Connectivity
  • Efficiency

Digital banking post-COVID

It is in the spirit of this vision that Refinitiv’s one-hour webinar seeks to build equity, create new opportunities, reduce complexity, and drive scale.

Join Steve Peacock, Chief Risk Officer at Think Money; Shana Krishnan, Policy Analyst at FATF; James Mirfin, Global Head of Digital Identity and Financial Crime Propositions at Refinitiv; and Aravind Narayan, Performance Director at Refinitiv, who will tell you how all this can be achieved.

“The world is exploding with digital connectivity,” says the company. “People, organisations, and internet-enabled devices of all kinds are interconnected. Global financial and payments systems face dynamic, persistent and rapidly escalating threats as technological developments in cybercrime make it easier than ever to commit fraud.”

As such, the company will explore the following topics:

  • Changing consumer behaviour and the fastest-growing types of financial crime
  • How COVID-19 is changing the threat of organised crime
  • Banks’ opportunity to realise value and review systems and controls while accelerating digital transformation (i.e. moving away from manual KYC to digital) post-pandemic
  • Strategies that banks can adopt for AML and mitigating fraud risk

Are you prepared for banking post-COVID? What’s your plan for reimagining digital services? Register and watch Refinitiv’s webinar now.

Image source: Refinitiv

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Jul 18, 2021

Reimagining operational risk management for business value

BroadwayTechnology
riskmanagement
Finance
AI
Tom Ballard, Program Manager, ...
6 min
Tom Ballard sets out a thorough new vision for operation risk management in finance, using advanced AI and analytics technology to drive business value

The events of 2020 and 2021 have fundamentally changed how we do business, upending every industry, including investment banking. Once bustling trading floors went silent as the switch to work from home led traders to disperse locations – and gave rise to new operational risk challenges. 

Today’s dynamic regulatory landscape coupled with ongoing technological innovations have made legacy approaches to operational risk management ill-suited to tackle current challenges and complexity. And while many financial institutions have turned to digital automation and transformation projects to adapt traditional ‘revenue generating’ functions to meet their challenges and help drive growth, they must now do the same with their Operational Risk Management (ORM) functions - or risk being left out in the cold. 

The Basel Committee defines operational risk as the “risk of loss resulting from inadequate or failed internal processes, people and systems or from external events.” Unfortunately, many financial institutions still view ORM as a regulatory and compliance necessity rather than a business function that delivers real value. That means executives and risk management departments must now change their risk approach to ensure they are dynamic and flexible, can guide their organizations through complex situations, and can readily meet the evolving expectations of regulators and their clients. 

Operational Risk Management is still a young field compared to other risk sectors in the financial markets, but it has always been viewed under a broad umbrella that encompasses risks and uncertainties difficult to quantify and manage in traditional manners. ORM has also been the convergence point where corporate governance issues overlap with revenue-generating business activities, causing potential confusion between departments. 

Investment banks have too often placed undue emphasis on creating governance frameworks designed to ensure they meet Basel Committee on Banking Supervision (BCBS) standards instead of recognizing that a sophisticated ORM function can bring quantifiable value. Their desire to merely meet BCBS standards and avoid historic risks has in effect led to an outdated, analogue approach in an increasingly digital world. Savvy investment banks have grasped the value potential of ORM and begun to drive a shift in awareness about the importance of a comprehensive risk identification, measurement, and mitigation program. 

Embracing a data-driven approach

Market players now recognize that adopting a digital strategy will allow them to deploy diverse and agile risk management mechanisms. It will also empower them to develop a strong and dynamic understanding of risks while adding real value to the business. This value goes beyond meeting regulatory and compliance mandates introduced as part of the Standardized Measurement Approach developed under Basel 3. A robust approach to risk allows the ORM functions to provide actionable intelligence to support business decision-making and assume a more commercial role that supports the various business units’ day-to-day activities. And that requires an intelligent, data-driven approach with a mandate to match, one that is championed at all levels of the organization.

This type of aggressive approach and embrace of digital transformation can also strengthen how ORM functions handle ambiguous and/or improbable events, especially as traditional methods of risk analysis prove unable to manage the ever-increasing volume of data. In 2010, the total amount of data created, captured, copied and consumed equaled about two zettabytes, compared to 2018 when volumes reached about 33 zettabytes. This 26% compounded annual growth rate means that if the rate of growth steadily continues by 2024, we can expect 149 zettabytes of data created per annum. 

Available data levels will make it difficult for analogue ORM functions to successfully meet the executive expectations, however organizations that adopt a data-driven approach will find increased data volumes provide them the insights to gain a competitive advantage and ability to proactively manage their risk. 

Leveraging AI and advanced analytics for high impact

Cognitive computing technologies like artificial intelligence (AI), data mining and natural language processing (NLP) can supplement a data-driven approach and help financial institutions confidently automate decisions, optimize processes and provide a deeper insight into available data. These cognitive computing technologies can help reduce or eliminate time-intensive and repetitive tasks, often related to data collection, handling and analysis which are better suited to automation. That in turn can free up critical employees to deploy their experience, knowledge of policies, and powers of assessment to support ORM functions and achieve their goals and focus on high-impact, high-value deliverables. 

Cognitive computing can teach computers to recognise and identify risk, which is especially useful to handle and evaluate unstructured data – the kind of data that doesn’t fit neatly into structured rows and columns on a spreadsheet. Natural language processing (NLP) can analyze text to derive insights and sentiments from unstructured data, which a 2015 study by the International Data Group estimates accounts for 90% of all data generated daily. When combined with the estimated future data volumes, cognitive computing functionality presents an immense opportunity for ORM functions to add additional business value in ways previously impossible. A detection model built on cognitive analytics can manage risk on a near real-time basis and can also unlock organizations’ historic datasets that have been compiled for internal, regulatory, or compliance purposes. These datasets often contain free text descriptions that contain a potential wealth of untapped, institution-specific information and could provide valuable insight into historic operational risk losses, providing data to augment employee’s qualitative experiences.    

Teaching an old dog new tricks

There are certainly challenges to launching digital transformation projects, implementing new data-driven approaches, and introducing cognitive computing technologies, including employee uncertainty and ethical considerations. That means financial institutions must preemptively address and prepare for potential challenges before they adopt a technology-enabled approach to Operational Risk Management. They must also secure employee buy-in to ensure stakeholders use these new technologies to their full potential and to assuage any concerns that technology diminishes employees’ important role in the organization.  

It’s critical that investment banks now shift their Operational Risk Management functions and focus on becoming more adaptive and agile in an increasingly volatile, complex, and uncertain world. Over 66% of banking executives report that adopting new technologies like AI and NLP will be a key driver in IBs development through to 2025. Yet for many investment banks, their ORM functions do not leverage the powerful new tools available to them – including increased computing power, digitization, advanced analytics, and data visualization techniques – much less harness the power of cognitive computing technologies. Until ORM functions leverage these tools, executive leadership cannot allocate resources and solidify ORM’s role in business strategy, performance, and decision-making processes. 

Old habits die hard, but it’s time for ORM functions to keep pace with these new technologies, methodologies, and approaches to position themselves and their organizations for success in today’s ever-changing world. If they do not adapt, there is a real risk they may stifle the wider organization, impede new opportunities and inhibit paths to valuable business growth.

This article was contributed by Tom Ballard, Program Manager, Broadway Technology

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