A Reversed Early Warning Methodology for Optimal Bank Profit Retention Recommendations

This study introduces a calibration method for the newest policy instrument in prudential supervision by endogenising profit retention targets via a reversed early warning system, depending on the supervisors' risk tolerance, the exposure to the economy, and the level of financial pressure. We model the likelihood of banking crises in EU jurisdictions within a medium‐term horizon using monthly frequency data to account for the increasing speed of financial shock developments amid the digital revolution, as the March 2023 distress episode indicated. Toward this target, we employ economic, monetary, and financial stress variables, banking size indicators, and leverage ratio. The early warning system is then run to calculate the capital buffer against a presumptive probability standard of the supervisory authority, given the financial stress level and the banking intermediation size. This approach would inform supervisors whether a profit retention recommendation is needed to enhance the shock absorption capacity of credit institutions to preserve banking stability given the existing economic, monetary, and financial conditions. Moreover, it can guide central bankers on their policy mix calibration, avoid frictions in the monetary transmission mechanism, and simultaneously accommodate price stability and financial stability goals. Furthermore, despite its macroprudential input, the regulators could replicate the methodology with microprudential data to derive an alternative but direct measure of capital buffers, complementing the current prudential regulatory approach.