Introduction to Online Payments Risk Management

Table of contents

1. Introduction to Online Payments Risk Management
2. Preface
   1. Why Was This Book Written, and Who Is It For?
   2. Acknowledgements
3. I. Background and Theory
   1. 1. What Is Risk Management in Payments?
   2. 2. What Problem(s) Are We Trying to Solve?
      1. Optimizing Risk with a Solution-Based Approach
      2. Why Talk About Loss and Not Fraud?
   3. 3. The Two Leading Approaches to the Analysis and Optimization of Losses
      1. The Portfolio Approach
      2. The Behavioral Approach
      3. Which of These Methods Works Better?
   4. 4. How Should We Describe and Understand Behavior?
      1. Remember: People Make Mistakes
      2. Putting the Framework to Use
4. II. Organization and People
   1. 5. The Goals and Functions of a Payments Risk Management Team
      1. What Does a Payments Risk Management Organization Do?
      2. Payment Risk Operations: Making Sure You Run Smoothly
      3. Decision Automation: Allowing You to Scale
      4. Analytics: Making Sure You Know What’s Going On
      5. Product Management: Bridging a Rather Narrow Gap
   2. 6. Hiring for Your RMP Team
      1. Some Important Comparison Points
      2. What If I Don’t Have Anyone?
      3. Hiring Your First Operator
5. III. Tools and Methods
   1. 7. Detection: Figuring Out that Something Is Wrong
      1. Measuring Performance
         1. Measuring Offset Performance: Time-Based Cohorts
         2. What Should You Measure?
            1. Measure Your Defaults
            2. Measure Your Recovery
            3. Measure Your Rejections
            4. Measure Ops Performance
         3. What’s “Normal” Performance?
            1. Defaults
            2. Rejections
            3. Operations Performance
      2. Detecting that “Something” Is Happening
         1. Incoming Complaints
         2. Inflow
         3. Linking
            1. Some Linking Terminology
            2. How Complex Should Your Linking Be?
         4. Velocity
            1. Some Velocity Terminology
            2. Baselining
            3. Iterative Analysis
            4. Individual Merchant/Consumer Velocity Models
            5. General Outlier Detection Models
   2. 8. Analysis: Understanding What’s Going On
      1. Designing for Analysis
         1. Instrumentation and Data Retention
         2. Data Latency and Transformation
         3. Control Groups
      2. Best Practices for Ongoing Analysis
         1. Automated Segmentation and Tagging
         2. Root Cause Analysis
   3. 9. Action: Dealing with Your Findings
      1. Manual Review
      2. The Variable Library
      3. The Review GUI
         1. Main Consideration in GUI Design
            1. Decision Fatigue
            2. System Responsiveness
            3. Data Assimilation
      4. The Rules Engine
         1. Basic Functionality Requirements
         2. Performance Simulation
         3. Performance Monitoring
      5. Automated Decision Models
         1. What Are You Predicting?
         2. Which Algorithms Should You Use?
         3. Model Time to Market (TTM)
         4. The Feedback Loop
      6. Product and Experience Modifications
         1. In-Flow Challenges
         2. User Experience Changes
         3. Proactive Risk Management
      7. When Things Go Wrong: Dispute Resolution
         1. User Experience Design
         2. Back Office Efficiency
      8. Setting Up Your Team and Tools
         1. Buy vs. Build
         2. Which Vendors Should You Look For?
            1. Should You Buy an Off-the-Shelf Risk System?
            2. Detection Vendors and Social Data
            3. Must-Have Tools and Data Sources
         3. Don’t Forget Domain Expertise
   4. Epilogue
6. About the Author
7. Copyright