The original pattern-recognition problem in banking.
4 AI translations · Banking & Financial Services
Your transaction monitoring system (Actimize, Verafin, SAS, Mantas/Oracle, or legacy rules-based) generates alerts based on predefined scenarios: structuring detection (transactions just below CTR thresholds), rapid movement of funds, unusual wire activity, cash-intensive business patterns, and peer group deviation. The problem: rules-based systems generate massive false positive rates (often 90–98%), burying your investigators in alerts that are almost never suspicious. You tune thresholds, manage alert queues, and your BSA analysts clear the vast majority of alerts as non-suspicious after manual review.
You perform CDD at account opening and periodically thereafter: verifying identity (CIP requirements), assessing risk (customer risk rating based on product, geography, entity type, industry), screening against OFAC/sanctions lists, determining beneficial ownership (for legal entities per the CDD Final Rule), and performing EDD for high-risk customers (PEPs, MSBs, foreign correspondents, cash-intensive businesses). You maintain customer risk profiles and update them based on transactional behavior and KYC refresh cycles.
When investigation determines activity is suspicious, you file Suspicious Activity Reports (SARs) with FinCEN. SAR narratives must clearly describe the suspicious activity, the subjects involved, and why the activity is suspicious. You manage filing timelines (30-day initial filing deadline from determination of suspicion, 90-day continuing activity SARs), track SAR subjects, and respond to law enforcement requests (314(a) and 314(b) information sharing). Quality SAR narratives are critical — they're what law enforcement actually reads.
You detect and prevent fraud across channels: check fraud (counterfeit, altered, kiting), wire fraud (BEC/business email compromise, authorized push payment fraud), deposit fraud (account takeover, new account fraud, check deposit fraud), and card fraud (counterfeit, CNP, account takeover). Each channel has different detection logic, different risk tolerances, and different response workflows. The fraud landscape shifts constantly as bad actors adapt to new controls.