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Data management at the heart of regulatory compliance
How lenders can win the data management game
18 September 2017
The financial services industry today faces numerous data management challenges to become both customer-centric and meet regulatory requirements. However, many lenders continue to face the challenge of aggregating, managing and creating value from their data.
Data underpinning credit risk is one of the most important assets of financial services organisations. The efficiency of storage, ease of access and logical definitions of the data are key to allowing firms to harness the power of this information.
In addition, lenders are likely to have at least one significant project this year to improve data management, IT infrastructure and reporting as they face regulatory deadlines, such as IFRS 9, stress testing and BCBS 239. The challenge of getting to grips with data is highlighted in particular by BCBS 239, where the biggest issue is the expertise and resource bandwidth to apply data quality, data governance and data management techniques.
The pitfalls of 'quick-fix' solutions
All of this adds greater pressure for a quick-fix solution. However, half measures are unlikely in the end to be sufficient. Regulators have become increasingly concerned about how weaknesses in risk data systems may compromise financial reporting. And many lenders are still unable to provide the required data, or find themselves coordinating manual and ad-hoc intervention to assemble the data demanded by their management teams or by regulators.
Create 'one version of the truth'
To excel in data management requires what we call one version of the truth to ensure enterprise transparency, auditability and executive oversight of risk. All business functions need one data source they can trust. With today's growing use of dashboards and the focus on managing through key metrics, having one version of the truth is becoming even more important.
How lenders can win
A good place to start is by clearly understanding the business requirements for data management in line with your strategic plan - all too often business requirements are constrained by perceived technical challenges in data acquisition. While such constraints should be a consideration, the focus must be on servicing end-user requirements effectively and efficiently.
Be proactive in addressing the difficult challenges - it is human nature to continue to refine things that are understood and working, as this is easy. However, this only results in percentage point improvements. Big gains can only be achieved by being brave enough to tackle the difficult challenges.
Don't be afraid to ask for external help - the requirements for data management in financial services are ever increasing in complexity. While it is not impossible for an organisation to have in-house appropriately skilled resource available at the time required, having such resources on the payroll is an expensive approach. This internal approach also limits access to best practice from the wider financial services industry and indeed applicable best practices from other sectors.
Value beyond compliance
There is significant potential value to be obtained from effective risk data aggregation, storage and analysis, beyond simple regulatory compliance. The ability to consolidate and synchronise all relevant risk data can lay the foundation for a more overarching and consistent analysis, enabling better business management, better risk management and optimised operating models.
Data management success will bring significant strategic benefits, including:
- The ability to aggregate risk, counter-party risk, etc. in a timely manner
- The necessary integration of finance and risk data
- The ability to make better strategic decisions around products and markets
- Rationalisation of reporting and dashboards
If lenders fail to get this right, they will fail to satisfy the regulators and their shareholders. More importantly, they will continue to lack the information they need to run their businesses properly - and lose market share to the digital and customer-centric challengers.
High-quality risk data should lead to improved decision-making, greater confidence and a more stable strategy.