Large Language Models in Risk and Compliance

This technical report discusses the application of Large Language Models (LLMs) in the context of risk and compliance, particularly in combating financial crimes. It outlines the potential of LLMs to automate processes such as Anti-Money Laundering (AML) and Know Your Customer (KYC) efforts, which are increasingly necessary due to rising transaction volumes and regulatory demands. The report details how LLMs can enhance decision-making by reducing false positives in alerting systems and improving transaction monitoring. It also emphasizes the importance of integrating LLMs into comprehensive systems rather than using them in isolation. The document further explains key concepts such as word embeddings and attention mechanisms, which are crucial for understanding how LLMs function and their relevance in identifying risks. Additionally, it highlights the need for domain-specific training of LLMs to ensure accuracy in financial crime detection, illustrating the advantages of tailored embeddings over generic models.