Fraud Detection and Reporting

Project Summary

The project focused on identifying potentially fraudulent subscription activity and reducing payment related risks.

Reporting Examples

Spike in Fraudulent Subscription Attempts

Fraud Report Overview

Objective

Interactive reports and dashboards enabled business stakeholders and the fraud team to investigate high risk users, monitor fraud trends, and identify emerging attack patterns. Risk scoring and segmentation allowed teams to prioritize investigations and take preventive actions before chargebacks or financial losses occurred.

Solution

A monitoring solution was developed to analyze user subscription behavior, payment information, and account characteristics to detect uspicious patterns and support fraud prevention efforts. The platform consolidated subscription, payment, and user activity data to create fraud risk profiles for individual customers. Multiple fraud indicators were implemented, including payment card BIN analysis (first six digits of the card number), geographic mismatches between user IP addresses and card issuing countries, suspicious email address patterns, and excessive trial subscription attempts.

Results

The reporting framework provided flexible analysis across multiple dimensions, including affiliate partners, websites, countries, subscription pricing tiers, and customer segments. Managers and data analysts could analyze performance through daily, weekly, monthly, and yearly views, enabling both operational monitoring and long-term trend analysis. The final solution enabled stakeholders to identify the most profitable acquisition channels, affiliate partners, and customer segments, optimize marketing investments, improve retention strategies, and make decisions that maximized revenue and overall ROI. The solution improved fraud visibility, supported proactive risk management, reduced chargeback exposure, and enabled faster investigation of suspicious subscription activity.

Key Fraud Indicators and Analysis Included:

• Card BIN (Bank Identification Number) analysis.
• IP address versus card issuing country comparison.
• Geographic risk assessment and country level fraud trends.
• Detection of suspicious email patterns and disposable email domains.
• Multiple trial subscription attempts and abuse detection.
• Payment decline and retry behavior analysis.
• High risk user identification and segmentation.