When AI Transforms Banking Risk Management

In recent years, banks have invested heavily in regulatory compliance. Artificial intelligence now represents a genuine opportunity for them to optimize their ratios and improve overall performance.

Text: Olivier Clinckart

As Morgan Serfiotis, Partner at Avantage Reply Belgium (a consulting firm specializing in financial risk management services for financial institutions), explains: “Regulations such as BCBS 239 and, more recently, expectations surrounding RDARR have reinforced a fundamental reality: the quality of risk-related decisions depends directly on the quality of the underlying data.”

This is precisely where AI can play a highly practical role: “It can help detect data anomalies more quickly and facilitate root-cause analysis when issues arise. In doing so, it enables a more proactive approach to data governance.” However, AI does not replace governance, controls, or business expertise: “On the contrary, it makes them even more important. Any AI used in risk management must be explainable, controlled, and integrated within a robust framework.”

The Challenge of Regulatory Capital

With the implementation of Basel IV, many financial institutions are facing an increase in their Risk-Weighted Assets (RWA). Here again, AI can serve as a significant accelerator: “It can help analyze large volumes of data, identify the key drivers of RWA, simulate different scenarios, and highlight optimization opportunities that would be difficult to detect manually.”

Avantage Reply supports financial institutions at the intersection of regulation, risk, data, and technology: “This positioning is essential because the market needs organizations capable of translating regulatory requirements into operational processes, data models, reporting capabilities, and concrete optimization levers. AI can become a major driver of risk management transformation, provided it is built on reliable data and supported by a strong governance framework,” concludes Morgan Serfiotis.