There is no denying that the regulatory burden placed on the banking industry has dominated projects and resource deployment for the last few years. CECL, CCAR, DFAST, Stress Testing have all placed enormous demands on banks focus, money, and talent deployment. At the core of this overwhelming burden is the capture and management of quality customer account level data for analytics to satisfy regulatory requirements.
For over 20 years, I have faced the same data challenges in developing and implementing Customer Profitability Analytic solutions for banks of all sizes. Over the years, data marts, lakes, warehouse and hub strategies have come and gone, but the core challenge in implementing these analytics remains the same: DATA. These analytic models to understand the lowest level drivers of profitability and performance of banks require a tremendous amount of data. Data management barriers restrict many banks from even embarking on the initiatives, or programs were stalled or abandoned from lack of quality data.
More recently, I have found that the regulatory burdens placed on banks regarding stress testing compliance have yielded most of the data necessary for providing robust customer account level profitability analytic models. What used to be the biggest obstacle for profitability initiatives, is now lying in wait for a strategic purpose. The initiatives that previously would take years to accomplish, now can be provided in weeks. Previously long development cycles of defining methodology and technology implementation are accelerated through iterative modeling, driving more accurate methodology refinements and actionable insights along the journey.
Concurrently, the strategic value of customer profitability analytics has increased beyond financial performance measurement and reporting. Front line access to these analytics can now prioritize financial needs analysis, provide relationship pricing applications to accelerate deals, and increase customer to banker ratios. Merger and acquisition analysis can leverage the same models for evaluation of combined business and regulatory impacts of proposed deals. Incentive compensation plans can shift from top line revenue generation to bottom line risk adjusted return on capital. Advancing profitability analytics is no longer a ‘big bank’ luxury, but quickly becoming table stakes in this extremely competitive and challenging industry.
A confluence of events in the industry has provided both the motivation and the capabilities to simplify what was once a daunting initiative. There has never been a more advantageous time to evaluate and consider advancing customer profitability analytics for banks. The only challenge now is getting started before the next economic event or industry disruption.