Transforming Data Management to Meet Regulatory Compliance Unlocks Wider Business Benefits

First published by International Banker, 26 February, 2024

Regulation within financial services is constantly changing, and with each new set of rules, more demands for accurate and timely reporting data come. These data demands place additional pressures on people, processes and systems within financial organisations when they’re already under the strain of suppressed margins, heightened competition and global political, economic and climate volatility.

Despite the challenges that new regulations and compliance requirements create, often depending on data that has previously been difficult to collect and analyse effectively and quickly, an opportunity for improving efficiency, client engagement, collaboration and innovation also presents itself. Fortunately, new approaches to handling vast amounts of disparate data effectively address these opportunities and create competitive advantages by enabling firms to process data from within and beyond their enterprises better. This approach is advantageous for regulatory purposes because it minimises the costs a business incurs in both time and money to achieve compliance.

By leveraging a 360-degree view of data from inside and outside their organisations, financial-services firms can enhance trading-activity visibility, better manage counterparty risk and capital consumption, and improve inter-departmental coordination, gaining a deeper understanding of business processes. The need to cleanse and standardise data arising from regulation will undoubtedly offer broader business benefits, too. This strategic approach to regulatory reporting can turn the drudgery of compliance into an opportunity for efficiency and growth.

The burdens regulators place on financial institutions can be significant: The Bank of England’s (BoE’s) “ The Future of Finance” report, for example, has highlighted that banks in the United Kingdom stack up a huge £2 billion to £4.5 billion in regulatory-reporting compliance costs annually.

In January 2020, the Bank initiated a dialogue on revolutionising data collection in the UK financial sector, aiming to reform the system over the next decade. This ambitious project acknowledged the need for significant, perhaps radical, changes. Discussions have focused on reducing the industry’s regulatory reporting load while enhancing data utilisation for supervision and peer comparison. The recent Prudential Regulation Authority’s (PRA’s) Banking Data Review (BDR) (a multi-year initiative designed to reduce unnecessary data collection and enhance proportionality) followed, with collaborative efforts from the Financial Conduct Authority (FCA).

Similarly, the European Banking Authority (EBA) and the European Securities and Markets Authority (ESMA) are considering how they can contribute to alleviating some of the heavy lifting required to comply with regulations. The EBA is re-examining reporting requirements, making infrastructure easier to use and exploring how technology can cut costs, while the ESMA is particularly interested in streamlining data, reducing duplication and inconsistency in requests, and exploring how newer technologies can help achieve its targets.

Despite all efforts so far, new initiatives such as Basel 3.1 and EMIR 3.0 (European Market Infrastructure Regulation 3.0) are continuing to add reporting pressures: The Prudential Regulation Authority in the UK plans to introduce 19 new and revise 12 existing COREP (Common Reporting) templates for Basel 3.1, and EMIR 3.0 will introduce more than 80 new data-field requirements.

The UK and European Union (EU) markets are not alone in their challenges to stay on top of regulations. Last August, the SEC (U.S. Securities and Exchange Commission) in the United States adopted its final Private Fund Adviser Rules, which legal experts regard as a significant development in the regulation of private-fund advisers. These rules include five regulations and are backed up with a large volume of summary materials. Thomson Reuters’ “2023 Cost of ComplianceReport”, which reviewed 1,374 regulators in 190 countries, highlights how regulatory workloads have increased globally. Its review of regulations found the number of “regulatory events” in the banking and finance sector across 2022 was 61,228—the third highest since 2008. Almost two-thirds (62 percent) of respondents reported they spent between one and seven hours tracking and analysing regulatory developments in an average week, and three-quarters of the 350 global respondents surveyed said they expected regulatory activity to increase.

A separate piece of global research by InterSystems, which surveyed 375 asset managers at mid-market firms, found that 44 percent of respondents considered responding to regulators to be one of their key data-management challenges. Eliminating errors and improving risk management were also cited among their top three challenges.

Fortunately, innovations in data management are enabling organisations to address all three challenges at once—by gaining real-time, on-demand visibility and utility across all their existing legacy enterprise data and applications.

Financial institutions can indeed unlock other opportunities from the data they must provide for compliance. Firstly, the transparency that compliance requires opens up a qualitatively different level of oversight. Firms can use this data to achieve greater risk-management efficiencies that will improve their bottom lines significantly.

Firstly, achieving compliance requires a transparent oversight of data management that naturally creates other positive side effects. Accurate data devoid of errors greatly reduces the risk of infringement and, therefore, the possibilities of financial and reputational damages occurring—as well as decreasing the costs in time and resources required for data processing.

Other secondary benefits are the enhanced visibility of processes, enabling banks to identify and strengthen areas of weakness in performance, and the increased collaboration, as the compliance requirement compels different functions in front and back offices and risk management to work more closely together to compile required data.

Most importantly, from a data perspective, regulatory developments may also require improved data hygiene—such as the PRA stressing data standardisation. Initiatives to bring different reporting regimes into close alignment will increase the need for more harmonised data. Cleaner and more standardised data will be a necessary first step before more sophisticated models can be implemented and adopted.

Faced with the need to provide streams of highly accurate and detailed data from a mass of internal sources, an organisation will need to innovate and adopt new approaches. For example, many asset-management firms currently find fast and timely access to reliable data nearly impossible. Research from InterSystems found that 68 percent of firms struggled with consolidating disparate data, and only 35 percent used data no more than 24 hours old.

Legacy systems and applications with their own databases create enormous complexities and prevent organisations from accessing and processing clean, standardised data that will not only be needed for regulatory reporting but will also transform operations. Firms that use spreadsheets, data warehouses, data marts and data lakes to store their data can fall short of what is required to achieve desired operational efficiencies. Harmonising data and rendering it usable and meaningful can be time-consuming and costly, with research finding that two-thirds of firms employ between six and nine people to complete this task. The result is that compliance functions cannot access the data they need in usable formats in time.

One of the most promising innovations is the smart data fabric, which can provide the clean and harmonised data financial teams need for effective reporting. It is an approach to data management that delivers results in near real-time. As an architectural layer, it simplifies complex data infrastructures without replacing existing systems or engaging in drawn-out IT (information technology) projects, maximising existing investments in technology.

Instead, the data fabric sits on top of a firm’s infrastructure, complementing it and connecting data across the enterprise to deliver a unified version of the data. The result is access to timely, error-free data on which an organisation’s compliance function can rely for reporting.

The smart data-fabric approach to data-fabric architecture enables the all-important end-to-end aggregation and integration essential for high-quality data. It incorporates embedded analytics, giving fast access to data to those who need it for reporting and investment decisions. It does this without copying data—reducing errors and inconsistencies that constantly undermine confidence and risk problems with regulators.

In a heavily regulated industry, with regulations increasing in both volume and complexity, access to a single source of truth helps to reduce risks and enables organisations to understand their allocations of assets better and employ them more profitably to comply with the complexities of regulations. This enhanced insight into risks and exposures improves compliance, while ease of access to the right data fulfils the need to respond quickly to regulators’ reporting requirements.

Providing all departments across both front and back offices with access to timely and accurate data has a transformative effect. Access to a greater depth of insight gives financial-services firms the ability, for example, to spot a behaviour indicating a customer is about to withdraw his or her investment, saving a significant amount of financial cost associated with churn. Predictive and prescriptive analytics enable them to be ready for upcoming regulations and compliance events and provide immediate access to powerful insights when fast reactions are called for to seize new opportunities or minimise risks.

In an era when hyper-personalisation attracts new customers and helps retain those who already have investments or accounts, fast access to data about customer activities and behavioural characteristics gives institutions the 360-degree view they need to maximise revenues.

Customers with investments are no longer satisfied with quarterly updates and want to see how their money is performing in near real-time. Accustomed to accessing financial services from a phone app, many customers value this speed and accuracy above more traditional interactions. However, it is only through having access to reliable, clean data that banks can innovate and build the new services that customers demand.

Using the insights uncovered from their data, firms can launch new products and services dynamically, keeping pace with changing customer needs. This is important because success in banking today depends on many factors, including having multiple services and products. Without having the correct data foundations in place, this is simply not possible.

By transforming their data management to meet regulatory requirements, financial-services institutions can build machine learning (ML) models to create more efficient risk management and streamline back- and middle-office processes. Reporting can be automated to provide more accurate and timely performance monitoring and meet bespoke client requirements. These models can provide greater transparency about fees and charges and adapt to changing market conditions and competitors’ activities far more rapidly and effectively.

In other words, by employing innovations such as smart data fabrics, many financial-services organisations can access the kind of data-driven capabilities that will transform their performances beyond the requirements of regulators. They will become far more innovative, agile and personalised when meeting the requirements of dynamic and demanding customers.