For banks, profitability has been under pressure for some time now, due to the lasting negative interest rate environment, an increase in non-performing loans, fintech competition, regulatory compliance costs, geopolitical issues, and other factors. None of these is new, but the risk linked to low profitably used to be mitigated by a positive macroeconomic outlook, and most importantly the monopolistic position of banks in the financial sector—assumptions that cannot be made anymore.
In this context, profitability has become one of the ECB’s key concerns, since indeed solid profits converted into retained earnings contribute to greater capital strength. A more capitalized banking sector is more resilient, able to absorb economic shocks, and therefore contributes to a more stable financial system, ensuring economic growth and welfare. To highlight this importance for the sector, the ECB has put reviewing the sustainability and viability of the business model, as well as assessing profitability, as key pillars in the SREP process.
In managing their profitability, banks are struggling mainly in two areas: first, knowing their bottom line income and profitability drivers, which is an important issue because high quality and sufficiently granular data is needed to build a comprehensive cost allocation approach; and second, using the same terminology of data across the whole bank with a common approach. Take the example of the ECB short-term exercise: banks need to provide a three-year forecast based on FINREP in an accounting view, while the budget must be prepared in a management reporting view. As these views usually differ in definition and granularity, a completely new forecast is required—and it is a struggle. Then, on top of financial and operational perspectives, banks must also analyse the risks and compliance costs associated with their business activities and integrate them into the margin calculation. Segregating the risk appetite by product, client, region, and division level is still, for many banks, a high-level rather than a precise exercise.
Assessing the degree to which a business yields profit requires a review of the business model and the identification of the bank’s core activities. A few useful questions to ask would be:
When exploring how to slim down, senior bank managers mainly cut or reduce ongoing investment projects so as to reduce their fixed costs. However, highly detailed information bases, which would enable better decision-making processes, don’t really exist—banks don’t even know their true profitability drivers except by knowing which products or clients are “cash cows”. Cost income ratios do reflect profitability, but this KPI is insufficient for taking concrete actions in reaction to granular-level insights.
Thus, to analyse, understand, and confidently report the company performance, and to take informed decisions, management needs a holistic view of the relevant information. This information should come from every department and, most importantly, be highly detailed, resulting in a unified executive function. This, in turn, enables an agile approach to processes such as reporting and disclosure, consolidation, analytics, budgeting, and planning. In the end, trustworthy and reconciled performance information should be available in an easy, rapid way.
From a larger perspective, performance management then becomes more risk-based. This reflects the SREP and turns a regulatory exercise into a value-adding business exercise, helping banks towards an ongoing management style rather than a periodic or ad-hoc one.
First of all, banks should fix their data quality and availability issues by ensuring that their data model and definitions are properly organised and governed. In this, internal silos should be abolished in favour of a holistic approach—after all, profitability is an issue shared by CFO, CEO, CRO, and COO alike. In fact, it concerns every department, and facing it should be seen as a collective effort to implement an adequate, granular cost allocation methodology.
Secondly, banks must get their technology right by taking advantage of software that already exists, getting a consolidated view of meaningful operational, capital, and risk information and measuring performance and profitability drivers. Such products are also designed to help remove existing silos when it comes to data management, harmonize differing data sources, and calculate KPIs in different ways.
Thirdly, implementing tools to measure performance in an integrated way often results, initially, in a decrease in that performance. This underlines the conceptual work that needs to be done: the right data model, a common taxonomy, and sound cost allocation methodology must all be in place.
The current banking environment requires banks to take strategic decisions now in order to preserve profitability. However, informed decisions need to be based on sound, useful, and integrated information about the business performance of the whole organization, which is often not available. The name of the game, currently, is bridging that information gap in order to get or keep a competitive edge. This would imply that banks must invest in their future, and accept that their costs may rise before they fall.