Consilient examines the de-risking trend, which involves financial institutions exiting markets and cutting ties with client categories to mitigate financial crime risks.
This strategy, while reducing exposure, often leads to economic exclusion and hampers growth, especially in developing regions.
A critical component of global finance is the correspondent banking system, where large banks provide international banking services to smaller banks. This system is increasingly under pressure as large banks pull back from these roles due to de-risking, leaving smaller banks without the necessary support. This not only affects the banks but also impacts individuals and businesses globally that depend on these services.
De-risking is just one part of a broader spectrum of risk management strategies, which includes risk acceptance, avoidance, reduction, and transference. In the banking sector, these strategies are foundational to managing risks effectively.
Risk Transference: This involves shifting risk to a third party. In the context of financial crime, banks face inherent risks that cannot be transferred and must be managed internally. FML supports this by improving control mechanisms that aid in risk reduction.
Risk Acceptance: Banks decide to accept certain risks when the cost of mitigation is higher than potential losses or the opportunities presented justify the risks. The level of risk acceptance is typically a fixed parameter within the bank’s overall strategy and risk appetite.
Risk Avoidance: This strategy involves altogether avoiding risk by staying away from high-risk markets or clients. Overemphasis on risk avoidance can lead to missed opportunities and is often the default strategy when other risk strategies are not viable.
Risk Reduction: Banks may reduce risk by engaging selectively within a market based on detailed risk assessments of individual customers. This selective engagement promotes financial inclusion while managing exposure to acceptable levels of risk.
FML offers a promising approach to enhance risk management capabilities, especially in correspondent banking. In correspondent banking transactions, the bank does not have a full view of the total activity from the respondent bank’s customer, making it particularly hard to understand the risk associated with a transaction. Federated Learning is designed to train the machine learning models across multiple data repositories, integrate these learnings to understand behavioral patterns of all high-risk transactions, and distribute the ability to identify these via a central model. This technology enables banks to use a trusted, robust model for evaluating customers, which is particularly advantageous in new or unfamiliar markets.
FML helps accurately assess risk and distinguish between risk and uncertainty—a vital capability in today’s financial landscape. By sharing technology and insights, FML allows respondent banks to gain a deeper understanding of the controls and risks managed by correspondent banks, thus enhancing the overall quality of risk management.
FML stands out as a strategic asset within banks’ risk management framework. It allows them to accurately measure risk and make informed decisions about engaging in new markets. By facilitating technology sharing among banks, FML improves the visibility of risk controls and supports a safer, more inclusive financial environment.
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