Anti-Money Laundering Transaction Monitoring Systems Implementation : Finding Anomalies

Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Acknowledgments -- Preface -- 1 An Introduction to Anti-Money Laundering -- The Emergence of AML -- AML as a Compliance Domain -- The Objectives of AML -- Regulatory Reporting -- Corporate Citizenship versus Profitability -- About True and False Positives and Negatives -- The Evolution of Automated Transaction Monitoring -- From Rule-Based to Risk-Based -- From Static to More Dynamic Transaction Monitoring -- Latest Trends: Machine Learning and Artificial Intelligence -- Latest Trends: Blockchain -- Risk-Based Granularity and Statistical Relevance -- Summary -- Chapter 2 Transaction Monitoring in Different Businesses -- Banking -- Correspondent Banking -- Banking - Trade Finance -- Banking - Credit Card -- Insurance -- Securities -- Stored Value Facilities (SVFs) -- Casinos and Online Gambling -- Lottery and Jockey Club -- Other Businesses -- Summary -- Chapter 3 The Importance of Data -- ETL: Extract, Transform, and Load -- Extract: Data Availability and Sourcing -- Transform: Data Quality, Conversion, and Repair -- Data Load and Further Processing -- Loading of the Data -- Data Lineage -- Multiple ETLs -- Summary -- Chapter 4 Typical Scenario Elements -- Transaction Types -- Actionable Entity -- Scenario Parameters -- Use of Maximum Instead of Minimum Value Threshold -- Threshold per Customer -- Pre-Computing Data -- Timeliness of Alerts -- Use of Ratios -- Ratio as Degree of Change/Similarity -- Ratio as Proportion -- Other Common Issues -- Chapter 5 Scenarios in Detail -- Large Aggregate Value -- Unexpected Transaction -- High Velocity/Turnover -- Turnaround/Round-Tripping -- Structuring -- Early Termination/Quick Reciprocal Action -- Watchlist -- Common Specifications across Unrelated Entities -- Involving Unrelated Third Party -- One-to-Many.