Banking is no longer just about money. It used to be, but the demand for information is rising. Regulatory pressure has continuously increased. Data management is key in order to keep profitability up and costs down. Looking at recent developments in fines and regulations, we see regulators pushing for data and analytics. Looking at ECB (TRIM) reviews, stress testing, EBA requirements, and BCBS requirements (Basel III update, consisting of BCBS 279, 309, 352, 374, 400, and 424), we can easily assume that data-driven regulation is now at the heart of the supervisory system. Therefore, banks should continually invest in their data management and be aware of shifting demands in the data ecosystem, becoming agile, data-driven enterprises.
The updated Basel requirements for market risk
Basel IV, officially named the updated Basel III, must be implemented by all banks. With the last update in December 2017, BCBS introduced more data complexity and additional data requirements for the banking sector. One reason is that the Basel committee wishes to increase comparability between the banking books of different banks and to be able to benchmark risk-related transparency and comparability. With BCBS 239 at the heart of their supervisory quest, banks are obliged to deliver more and better data every next review.
Looking at market risk, a standardized approach is introduced with sensitivities-based method to incorporate more risk sensitivity into the pillar 1 standards. These models will be driven by desk-specific models and required documentation which (again) requires significant regulatory data management efforts. Banks need to identify the trading desks with high levels of unclarified P&L because of lack of data granularity. Therefore, high-quality and highly granular data combined with better analysis are required to meet these new standards.
The new standardized approach will impact the RWA calculations. Capital floors will now limit the RWA reduction which can be achieved with the internal models, IMA, IMM, and IRB, by using the standardized approach.
Within the market risk-standardized approach, the sensitivities-based method requires banks to include the correlations of each risk class. The correlation corresponding to three different scenarios of high, medium, and low correlation between risk factors within a bucket and across buckets is to be computed for each risk class. On top of this, the sensitivities-based method requires that all risk weight determinations are computed using the same aggregation formula across the delta and vega risk factors. Despite the common computations, the delta and vega risks are to be computed separately. This means that there is no more diversification benefit between the delta and vega risk factors. In short, the sensitivities-based method entails an expanding use of sensitivities across the standardized approach, to require a consistent and risk sensitive framework. This requires additional emphasis on both data gathering and data analytics.
New requirements do allow for a new competitive edge
Basel IV doesn’t only bring an increase of the restrictions, minimal capital requirements, and standardized risk methods. To balance the challenges faced by the new Basel requirements, there are a few positive updates which include the removal of the conservative IRB scaling factor, maintaining IRB approaches for specialized lending, and the F-IRB approach. Each of these will have some positive effects for global large corporate portfolios and low default portfolios, such as banks.
Banks should take the opportunity to use their data to test the regulator’s assumptions about defaults and loss. High quality granular data will allow banks to make proper forecasts of accurate measurements. This will then help banks to undo the mark-ups they get for uncertainty and provide the evidence on being compliant with the capital floors. If less capital is stuck in the floor, more is available for new investments.
If you neglect your data you are wasting money
BCBS is continuously urging banks to report with consistency and with such levels of granularity that manual generation of these reports will be impossible. Banks need to be able to instantly produce regulatory insights. The full automation of the generation of these reports is, therefore, a must.
Accurate and granular data from banks will support the regulator and the bank to produce insights in what capital is to be reserved as a buffer. There is now a mutual interest here to organize the data, and the quality aspects of it are key. So banks, please manage your critical data elements in a way that they are able to manage once and use multiple times. That will increase compliance and profitability. Banking is no longer only about the money but as much about data. Don’t waste it!
Your team Data, Finance, Risk, and Regulation
Elena Paniagua Avila