Intermediate

Understanding Transaction Monitoring Systems in Banks

A concept course for compliance officers at banks and NBFCs, aspiring forensic auditors and risk professionals who want to understand the machine at the centre of every bank's AML programme. It explains why Indian banks must monitor transactions under the PMLA and the RBI KYC Master Direction, where monitoring sits between KYC, screening and reporting to FIU-IND, and how real-time payment monitoring differs from overnight batch scans. You then open up the engine: the data it consumes from core banking and channel systems, how customer risk rating and segmentation shape what it looks for, and why poor data quality quietly breaks most systems. The course decodes detection scenarios, from structuring and rapid movement of funds to dormant account reactivation and UPI mule networks, and follows an alert through triage, investigation and case management to a filed STR. It closes with the hard problems: false positives, threshold tuning, performance metrics and model validation, the shift to machine learning and network analytics, and what regulators in India and abroad have done to banks whose monitoring failed.

Transaction MonitoringAML SystemsDetection ScenariosAlert InvestigationFalse PositivesThreshold TuningMule AccountsFIU-IND Reporting
MODULES
6
DURATION
4 Hours
TRACK
Forensic Accounting & Compliance

What You'll Master

Explain what a transaction monitoring system does and the legal obligations under the PMLA and RBI rules that require Indian banks to run one
Place monitoring correctly alongside KYC, sanctions screening and FIU-IND reporting, and distinguish real-time from post-event monitoring
Describe the data a monitoring system needs and how customer risk rating and segmentation drive what it detects
Read and design a detection scenario, including its rule logic, thresholds and lookback window, for common laundering and fraud typologies
Follow an alert from generation through L1 and L2 review and case management to a decision to file or close
Diagnose the false positive problem and explain threshold tuning, performance metrics and independent model validation
Evaluate machine learning and network analytics approaches and learn from real monitoring failures and regulatory penalties
Access Level
LEARNER
Everything included
Full Text Playbooks
Actionable Exercises
Mobile Reading Mode
Lifetime Updates

Curriculum Breakdown