Fraud Data Analysis

The Fraud Data Analysis page provides insights into fraud detection accuracy, trends, and patterns. It helps administrators track fraudulent activities and optimize fraud prevention measures.

Features#

🔹 Fraud Detection Accuracy Trend#

• Displays a graphical trend of fraud detection accuracy over the last 30 days.
• Helps in evaluating the efficiency of fraud detection algorithms.

🔹 Onboard Risk Correlation Matrix#

• Analyzes the correlation between different risk levels (high, medium, low) over the past 7 days.
• Helps in understanding the distribution of fraudulent, suspicious, and legitimate onboarded users.

🔹 Fraud Patterns Over Last 7 Days#

• Highlights key fraud indicators such as:
  • IP Reuse
  • Device Fingerprint
  • Email Pattern
  • Multiple Accounts
  • High-Risk Country
• Displays occurrences of these fraud patterns to help in risk mitigation.

🔹 Onboard Correlation Matrix#

• Displays the correlation of different onboarding cases categorized into Fraud, Suspicious, and Legit over the last 7 days.
• Allows tracking of fraud trends based on historical data.

This section provides valuable insights for fraud monitoring, improving accuracy, and identifying patterns in onboarding activity.