Real-Time Fraud Detection Agent
How we stopped $2.4M in fraud in Q1 with an AI agent that thinks in milliseconds.
CreditPulse (YC W24) · Digital Lending · India + Singapore
Fraud Prevented (Q1)
Detection Accuracy
Decision Latency
Idea → Production
The Challenge
CreditPulse, a YC-backed digital lending startup, was processing 8,000+ loan applications per month across India and Singapore. A 12-analyst manual review team was overwhelmed, and sophisticated fraud rings had learned to exploit the 4–6 hour review window.
By Q4 2024, they were losing approximately $400,000/month to fraudulent applications that passed initial screening. The CEO's brief to Palpx was specific: build an AI system that could decide fraud-or-approve in real time — with accuracy matching or exceeding their best human analysts.
Our Solution
We built an autonomous AI agent — not just a model, but an intelligent decision system — that evaluates 240+ signals simultaneously: behavioral biometrics, device fingerprinting, GST-cross-referenced income, social-graph analysis, and historical fraud pattern matching.
- Instant approve — high-confidence legitimate apps, <200ms.
- Human review — borderline cases flagged with an AI risk brief.
- Instant decline — high-confidence fraud, with reason codes for audit.
Architecture
Application Submit ↓ Behavioral Biometrics Layer ↓ 240-Signal Extraction ↓ XGBoost + Neural Ensemble ↓ LLM Risk Reasoning Layer ↓ 3-Way Decision Router → Loan Origination System
Process Timeline
Month 1
Data Archaeology & Model Design
Analyzed 18 months of historical applications. Identified 47 fraud pattern signatures. Designed signal extraction pipeline.
Month 2
Build, Train & Red Team
Built and trained the ensemble model. Ran adversarial red-team sessions with CreditPulse's fraud team to stress-test the system.
Month 3
Production Integration & Monitoring
Integrated with live loan origination. A/B tested vs. human reviewers for 3 weeks (AI outperformed precision by 12%). Cutover. Real-time dashboard launched.
Results
“We went from hemorrhaging $400K/month to fraud to having the lowest fraud rate in our cohort — in one quarter. The ROI was obvious from week 4.”
— Karthik Iyer, CEO, CreditPulse
Gallery
Decision dashboard
Real-time approve / review / decline rates.
AI risk brief
Auto-generated for every human-review case.
Fraud trend chart
$400K → near-zero in one quarter.
UI design by Palpx — details obscured for client privacy.
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