PurposeThis book is designed to provide practical and professional guidance on Anti-Money Laundering (AML) analytics, fraud detection scenarios, and compliance strategies using SAS and Gephi tools. It is tailored for professionals working in UAE banks, regulators, and analytics teams involved in AML monitoring and fraud risk management.Key Features- Covers 20+ AML detection scenarios implemented using SAS- Includes entity network mapping using Gephi- Provides full alert-to-SAR case studies- Explains key UAE compliance frameworks like goAML, FATF, and CBUAE regulations- SAS code and logic published on GitHub for practical useTarget AudienceAML investigators, compliance officers, risk analysts, SAS programmers, regulators, and financial crime teams in UAE-based institutions. Sameer Shaikh is a Senior Data Architect with over 14 years' experience in Banking, fraud detection, and credit-risk modeling for leading banks in India and United Arab Emirates. A recognized thought-leader, Sameer has:Architected enterprise AML/Credit Risk platforms in SAS Viya and SAS AML Manager, delivering real-time solutionsBuilt advanced machine-learning models (logistic regression, gradient boosting, random forests) in SAS Enterprise Miner and SAS Studio, achieving up to 95% detection rates on synthetic fraud scenarios.Pioneered network analytics by integrating Gephi visualizations with SAS data flows-uncovering hidden rings of mule accounts and circular money-movement patterns.Automated regulatory reporting in private banks in India, Singapore and MalaysiaMentored dozens of junior analysts through internal "SAS training programs, fostering a new generation of Tech specialists.
