How I Uncovered Hidden Structuring Patterns in bKash Transactions with Python
Last quarter, while reviewing a batch of 80,000 MFS transactions for a leading fintech in Bangladesh, I noticed something odd. About 2% of the transactions were exactly BDT 99,000, just below the BDT 100,000 MFS threshold. I was intrigued. The core problem most practitioners miss When I was new to AML analysis, I focused on detecting obvious suspicious transactions. But I was wrong about this until I realized that structuring patterns, like the one I mentioned, can be a significant red flag. In my experience, most AML analysts miss these patterns because they are not looking for them. I recall a case where a customer was structuring transactions to avoid the BDT 100,000 threshold, and it took us months to detect. Background / why this matters in BD fintech context In Bangladesh, the BFIU guidelines require fintechs to report suspicious transactions, including those that involve structuring. The STR/SAR process is critical in preventing money laundering and terrorist financing. As an AM...