The Financial Crimes Enforcement Network (FinCEN) in the United States just completed its request for information, gathering ideas from across the industry on how to better combat organized crime with innovations in artificial intelligence (AI) and machine learning as it seeks to modernize the Bank Secrecy Act and Anti-Money Laundering Regulations. 1. Explainability Dispel confusion and create confidence in innovation programs through a clear, risk-based framework. Financial institutions (FIs) need to know what an acceptable level of explainability is as it relates to more advanced machine learning models. This would include defining explainability versus interpretability and guidelines on measuring performance and minimum effectiveness standards. 2. Model Governance Update frameworks to be specific for financial crime management. Current guidelines were designed for a broader set of models, which makes it challenging for FIs to be confident that their innovation will be compliant. Regulation needs to ensure financial institutions can action the framework into practical solutions. 3. Open Data Create APIs and collaboration groups to enable secure data sharing. The biggest challenge in AML/CTF and combatting organized crime is operating on minimal data. A more efficient, timely, and automated flow of information to FIs would provide richer data to machine learning models for additional accuracy in financial crime prevention. Read More