Mini Model - Fraud Diagnostics Platform
Automates the complete fraud diagnostics workflow: validates transaction datasets, enriches data with 25,000+ features, calculates Information Value (IV) using distributed processing, and generates comprehensive performance reports with actionable insights.
Tech Stack
Problem
Traditional fraud root cause analysis required days of manual investigation, processing large datasets with thousands of features to identify model degradation and fraud trend shifts.
Solution
Built an automated pipeline that validates datasets, enriches with 25,000+ features via QPull, calculates IV using distributed Shifu processing, and generates professional HTML reports with visualizations.
Impact
Reduced analysis time from 3 days to hours, with 50% cost reduction through dynamic cluster sizing and 82-87% performance improvement via parallel processing.
Key Features
- •Automated quality control: validates datasets (10k+ records, 5-60% bad rate)
- •Intelligent chunking for large datasets (>26k rows) with parallel processing
- •Dynamic Dataproc cluster sizing for cost optimization
- •Information Value (IV) calculation via distributed Shifu
- •Comprehensive metrics: AUC, ROC, KS, precision/recall for all features
- •Professional HTML email reports with visualizations and ZIP archives
- •Mock testing framework for offline development