About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Knock on Effect

Subscribe to our newsletter

The close link between data quality and better risk management has come under the spotlight in recent years as a result of the financial crisis and the ensuing regulatory crackdown on financial markets. Regulators such as the UK Financial Services Authority (FSA) and the US Securities and Exchange Commission (SEC) have even been making noises about the importance of the data underlying risk calculations and therefore have been more frequently drilling down into this data for supervisory purposes. However, the biggest driver by far has been the advent of Basel III and the fundamental changes being introduced as part of this new regulation, which brings risk management into the equation right from the front office to the back.

Basel III is aiming to raise the quality, consistency and transparency of firms’ capital bases, which as well as alterations to the makeup of their tier one, two and three levels of capital, also means the provision of more supporting data about these instruments. New regulatory reports and increased data transparency will obviously result in technology investment and a large proportion of this will initially need to go towards data management infrastructure.

Moreover, the enhancement of risk coverage is also a focus of Basel III that will mean stress testing will factor much more in risk modelling and analytics. Much the same as liquidity risk, firms will need to use stressed inputs and include factors such as “wrong way risk”, correlation multipliers and centralised exchange incentives (as the regulatory community continues in its crusade to force more instruments onto exchanges and via central clearers) in their calculations. All of this essentially means an increase in the data sets that must be dealt with by those involved in the risk management function and hence more data to be kept clean.

This plethora of new requirements has led to discussions about enterprise risk management strategies and how firms can move from their currently siloed approach to the risk function to a much more integrated one. After all, one of the basic tenets of conducting an integrated risk management function is the connecting of the multiple siloed data sets that must be used to feed into risk calculations, both historical and real-time.

As noted recently by Tom Dalglish, director and chief information architect at Bank Of America Merrill Lynch, regulatory and risk management pressures are therefore compelling firms to plough investment into their data infrastructures in order to be able to ensure the consistency of the basic reference data underlying their businesses. “The pressing requirement on the regulatory front is the ability to provide consistent data across the firm, track data flows and usage, leverage consistent identifiers and provide an auditable chain of custody for data as it traverses the enterprise,” says Dalglish.

“Firms need to focus on what they are doing across lines of business to guarantee that all users are looking at consistent data and at the same time reduce duplicate storage, improve the process of data entitlement and authentication and increase the auditability of data. There are anticipated regulatory requirements for providing evidence of a data governance policy and traceability of data,” he continues. Many of these requirements are in-built into Basel III, which includes specific references to the ability for regulators to be able to drill down into risk calculations and determine the quality of data used.

However, the changes required to meet Basel III requirements will not come cheap: according to an estimate by UBS last year, firms may need to raise US$375 billion of fresh capital to comply with the new rules. It is assumed that Basel III will also be implemented in a much quicker manner than its predecessor, which suffered endless delays, due to the appetite for regulatory change at the moment and the fact that a lot of the groundwork has already been done with the Capital Requirement Directives (CRDs). Of course, this will also mean firms will need to get their new systems online and ready to produce the altered risk calculations in a much tighter timeline.

This is a challenge that should prove tough alongside the liquidity risk reporting changes and other widespread reforms sweeping the market. Accounting changes are also a risk related challenge that is compelling investment in data management. In the post-crisis environment, the expected losses provisioning approach to accounting, for example, requires the incorporation of a broader range of credit information, both quantitative and qualitative, which must be drawn from banks’ risk management and capital adequacy systems. This data must be transparent and subject to appropriate internal and external validation by auditors, supervisors and other constituents.

The focus of the work has been on improving the “relevance” and “usefulness” of accounting standards and has thus been centred on increasing transparency and therefore the depth of the data provided with pricing and valuations. Regulators and end clients will require firms to provide a sufficient level of data around how they achieved their pricing and figures for accounting; much like for risk management. The changes should also lend to the cause of the chief risk officer (CRO) in endeavouring to get a better handle on a firm’s financial position.

The close link between reliable, high quality data and accurate risk calculations is well understood; it is now up to the industry to take action.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Meeting the challenges of regulatory change

Regulatory change is constant, complex and challenging, calling on financial institutions to attend to details of change whether relatively minor or large scale. Recent regulatory changes include MiFID II post-trade transparency requirements, including ESMA’s increase in data continuity checks that brokers must prepare for, and trading venues must make, when reporting instrument reference and quantitative...

BLOG

Buy to Build: How Providers Help Make Unique Trade Surveillance Systems Possible

By Ollie Cadman, Chief Product Officer, Eventus. “Buy versus Build” was a dilemma that financial institutions traditionally faced when working to create modern surveillance systems or other key elements in the risk technology stack. What groups were trying to figure out was whether purchasing products and services was more cost-effective and future-proofed than building a...

EVENT

RegTech Summit APAC

Now in its 2nd year, the RegTech Summit APAC will bring together the regtech ecosystem to explore how capital markets in the APAC region can leverage technology to drive innovation, cut costs and support regulatory change. With more opportunities than ever before for RegTech to add value, now is the time to invest for the future. Join us to hear from leading RegTech practitioners and innovators who will share insights into how they are tackling the challenges of adopting and implementing regtech and how to advance your RegTech strategy.

GUIDE

Regulatory Data Handbook 2022/2023 – Tenth Edition

Welcome to the tenth edition of A-Team Group’s Regulatory Data Handbook, a publication that has tracked new regulations, amendments, implementation and data management requirements as regulatory change has impacted global capital markets participants over the past 10 years. This edition of the handbook includes new regulations and highlights some of the major regulatory interventions challenging...