Why Most AML Models Fail in Bangladesh: 5 Steps to Improve Detection
Photo by Mauro Sbicego on Unsplash Last quarter, while reviewing a batch of 80,000 MFS transactions, I noticed that our rule-based AML system had flagged over 10,000 transactions as suspicious, but upon manual review, only about 100 actually required reporting to the BFIU. This experience made me realize that traditional rule-based systems can be overly broad and inefficient, leading to unnecessary false positives. In my experience, many AML analysts and compliance officers in Bangladesh face similar challenges. We spend too much time reviewing false positives, which takes away from our ability to focus on high-risk transactions. I was determined to find a better approach. The core problem most practitioners miss Most AML systems rely on predefined rules to identify suspicious transactions. However, these rules often fail to account for complex patterns and anomalies in real-world data. This leads to a high number of false positives, which can overwhelm compliance teams. I noticed tha...