Fraud Monitoring Table of Contents


Table of Content
 


Module 1: Foundations of Fraud

  • What is Fraud? What Constitutes Fraud?
  • Categories and Types of Fraud
  • Occupational Fraud and Profile of the Typical Fraudster
  • The Fraud Triangle: Pressure, Opportunity, Rationalization
  • The Fraud Diamond: adding Capability
  • Characteristics and Common Behavioral Red Flags of Fraud Perpetrators

Module 2: Fraud Schemes and Typologies 

  • First-, Second-, and Third-Party Fraud
  • Billing, Skimming, Payroll, Expense, and Procurement/Vendor Fraud Schemes
  • Identity Theft and Synthetic Identity Fraud
  • Account Takeover (ATO) Fraud
  • Insider and Employee Fraud
  • Detecting Single, Second, or Third-Party Fraud

Module 3: Digital & Payments Fraud

  • Card-Not-Present (CNP) and Card-Present Fraud
  • UPI, Mobile Wallet, and Real-Time Payments Fraud
  • E-commerce and Marketplace Fraud (chargeback fraud, triangulation fraud, refund abuse)
  • Business Email Compromise (BEC) and Vendor Impersonation Fraud
  • Phishing, Vishing, Smishing, and Social Engineering Fraud
  • Deepfake, Voice-Cloning, and GenAI-Enabled Fraud
  • Telecom and SIM-Swap Fraud

Module 4: Red Flags and Fraud Indicators 

  • Behavioral Red Flags (individual conduct, lifestyle indicators)
  • Transactional Red Flags (structuring, velocity, round amounts, off-hours activity)
  • Documentary and Accounting Red Flags
  • Identifying Opportunities for Fraud

Module 5: Regulatory Framework, AML and Compliance

  • Overview of Relevant Laws and Regulations (global)
  • Anti-Money Laundering (AML) Fundamentals and the Fraud–AML Overlap
  • KYC, CDD, and Enhanced Due Diligence (EDD)
  • India Regulatory Context: RBI Guidelines, PMLA, FIU-IND Reporting
  • Suspicious Activity/Transaction Reports (SAR/STR) — When and How to File
  • Sanctions and PEP Screening Basics
  • Global Standards: FATF Recommendations
  • Forensic Accounting and Investigation Standards (FAIS)
  • Consequences of Non-Compliance

Module 6: Fraud Risk Management 

  • Risk Basics and Sources of Risk
  • Risk Identification, Analysis, and Assessment
  • Risk Measurement and Handling Methods
  • Risk Management and Financial Ratios

Module 7: Fraud Detection Techniques 

  • Recognizing the Symptoms of Fraud; Tips and Complaints
  • Anomaly Detection Fundamentals
  • Data Analysis Techniques for Fraud Detection
  • Applying Benford's Law, Z-Score, and Correlation Analysis
  • Industry-Specific Fraud Detection
  • Network and Link Analysis for Fraud Rings and Mule Accounts
  • Introduction to Predictive and Behavioral Analytics

Module 8: Fraud Monitoring Operations

  • Fraud Monitoring Fundamentals and Monitoring Tools
  • Risk-Based Monitoring
  • Alert Generation and Rule-Based Monitoring Systems
  • Alert Triage, Disposition, and Escalation Workflow
  • False Positive Reduction and Rule Tuning
  • Case Management Systems: An Overview
  • Key Performance Indicators (KPIs) for Fraud Monitoring
  • Feedback Loops and Continuous Improvement Strategies

Module 9: MS-Excel for Fraud Analytics 

  • Excel for Fraud Analysis: Sort, Filter, Pivot Tables
  • Key Formulas and Functions for Transaction Analysis
  • Logical, Date/Time, Lookup, and Reference Functions
  • Building a Simple Fraud Dashboard in Excel

Module 10: SQL for Fraud Investigators

  • SQL Basics: SELECT, WHERE, JOIN, GROUP BY
  • Writing Queries to Identify Duplicate, Structured, or Outlier Transactions
  • Aggregation and Pattern Queries for Fraud Analysis

Module 11: Tableau for Fraud Monitoring 

  • Tableau Basics, Working, and Data Terminology
  • Data Types and Data Cleaning in Tableau
  • Tableau Calculations, Functions, and Filters
  • Building Fraud Monitoring Dashboards
  • Case Study: Detecting Anomalies in Credit Card Transactions

Module 12: Fraud Investigation

  • The Fraud Investigation Process, End to End
  • Evidence Collection and Chain of Custody
  • Interviewing Techniques and the Cognitive Interview
  • Digital Forensics Basics for Fraud Investigators
  • Writing the Fraud Investigation Report
  • Working with Law Enforcement and Legal Teams
  • Successfully Investigating and Closing a Fraud Case

Module 13: Internal Controls 

  • Internal Control Basics, Types, and Common Procedures
  • COSO Framework
  • Internal Controls Policy and Procedures

Module 14: Ethics and Privacy in Fraud Monitoring 

  • Professional Ethics in Fraud Detection
  • Balancing Privacy and Security
  • Data Privacy Considerations
  • Ethical Dilemmas in Fraud Monitoring

Module 15: New-Age Technology in Fraud

  • Artificial Intelligence and Machine Learning in Fraud Prevention
  • Generative AI as a Fraud Risk: Deepfakes and Synthetic Content
  • Blockchain and Fraud Prevention
  • Blockchain Forensics and Cryptocurrency Forensics
  • Biometric Authentication and Its Limits

Module 16: Emerging Trends in Fraud Monitoring 

  • Cybersecurity Threats Relevant to Fraud
  • Social Engineering Techniques
  • Technological Advancements and Associated Risks

Module 17: Case Studies and Real-World Fraud

  • Banking Industry Fraud Monitoring Case Study
  • Insurance Industry Fraud Monitoring Case Study
  • Healthcare Industry Fraud Monitoring Case Study
  • Retail and E-commerce Fraud Monitoring Case Study
  • Fintech and Digital Payments Fraud Case Study
  • Cross-Border and Trade-Based Fraud Case Study



Apply for Certification

https://www.vskills.in/certification/fraud-monitoring-certification-course


 For Support