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Uncovering Patterns of Corporate Risk Behavior in the Financial Industry
Thu, September 4, 4:00 to 5:15pm, Communications Building (CN), CN 3111Abstract
Financial institutions are expected to act as gatekeepers of the financial system, ensuring compliance with integrity regulations to prevent money laundering and financial crimes. In the Netherlands, financial supervision follows a twin-peaks model, with both the Dutch Central Bank (DNB) and the Dutch Authority for the Financial Markets (AFM) overseeing compliance through a risk-based and data-driven approach. Institutions self-report on key risk indicators, which inform enforcement interventions ranging from norm-enforcing conversations to formal enforcement measures.
This research explores longitudinal patterns of corporate risk-taking and risk mitigation with respect to integrity risks within the banking and investment sectors in the Netherlands. Using regulatory enforcement data from Dutch financial authorities (DNB and AFM), a data-driven corporate risk score is constructed based on integrity risk self-reports spanning from 2019 to 2023 for approximately 80 banks, 3,000 investment firms, and 7,000 investment funds. The score captures two key dimensions: risk behavior – how financial institutions expose themselves to integrity risks – and risk mitigation – how these risks are managed. Multi-group, Multi-trajectory Modeling is applied to identify distinct risk trajectories and assess potential compensatory mechanisms between risk-taking and mitigation strategies. Internal consistency tests, cross-year sensitivity analyses, and correlations with regulator-assigned risk classifications are conducted to validate the risk score. The findings provide insights into corporate risk dynamics, regulatory oversight, and the effectiveness of data-driven approaches in identifying entities with higher risks on facilitating financial crime.