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Counterfactual Methods for Detecting Unfairness in Anti-Money Laundering Algorithms
The application of machine learning-based predictive algorithms to Anti-Money Laundering (AML) has grown rapidly, driven by the vast volume of financial transaction data available to banks. These algorithms are typically trained not only on transactional data but also on sensitive client information
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