5+ years building payment infrastructure that powers real transactions. Now at SKEMA Paris, bridging technical depth with AI-driven risk innovation.
I validate systems that move money. Not test cases. Payment infrastructure. $1B+ monthly GPV. 1M+ merchants across Asia, Middle East and Africa. Zero critical defects at go-live.
I led a cross-functional team of 7 to deliver an AI/ML fraud detection system from scratch: rule engine, ML model inference, and geography-based blocking. Signed off by VP and CTO.
Now at SKEMA Paris, I am completing an MSc in Sustainable Finance and Fintech, writing a dissertation on Explainable AI-Driven Adaptive Fraud Detection. Not a career change. An altitude upgrade.
"Technical depth. Strategic ambition. Paris-ready."
Zero critical defects. Signed off by VP & CTO.
Built and validated a real-time fraud detection system screening high-volume transactions across UPI, POS, AEPS, and Payment Gateway channels, with accuracy, speed, and full regulatory compliance.
99.9% financial accuracy. $1B+ monthly volume. Zero discrepancies at go-live.
Validated a multi-model settlement engine processing $1B+ monthly GPV across 1M+ merchants in Asia, the Middle East, and Africa.
"10 systems built, validated, and shipped to production."
End-to-end merchant onboarding & KYC — 500+ test scenarios, zero bugs at go-live.
Full wallet lifecycle. 1M+ merchants, 1000+ test cases, zero production issues.
Terminal lifecycle with geo-tracking and auto-deactivation. Zero reconciliation gaps.
Multi-channel payment testing across UPI, POS, AEPS, MATM, and PG with full load and stress validation.
Full chargeback lifecycle across Mastercard 48xx and Visa dispute codes, from initiation through to arbitration and resolution.
PHP to Node.js, version 2 to 3, and database migration. Zero data loss, 99.9% uptime maintained throughout.
Selenium and Java framework delivering a 40% regression efficiency gain across ERP and UPI systems.
1,200+ automated scenarios with 35% regression time reduction and full CI/CD pipeline integration.
Requirements, system flows, risk areas
Test strategy, scenario design, traceability matrix
Manual testing, API validation, automation build
Regression tuning, pipeline integration, coverage refinement
Performance metrics, defect triage, root cause analysis
Deployment validation, post-release sanity, stability confirmation
"Explainable AI-Driven Adaptive Fraud Detection: A Machine Learning System for Digital Banking"
Completing MSc at SKEMA Paris. Finalising dissertation on Explainable AI fraud detection. Targeting fintech product and payment systems roles across Europe, building on 5+ years of technical depth in payment infrastructure and AI-driven risk.
Engineering foundation → analytical thinking → QA in fintech
Sharing perspectives on fintech, payment systems, and AI-driven risk. Follow along on LinkedIn.
Real-time fraud detection is not just a technical problem. It is a trust problem. Validating ISO 20022 messaging formats and financial settlement rails requires rigorous end-to-end reconciliation testing to prevent multi-million dollar ledger discrepancies before deployment.
Machine learning models in fraud detection are powerful, but black-box decisions face strict European regulatory hurdles. Explainable AI (XAI) bridges the gap between high accuracy models and compliance auditability in digital banking.
From validating $1B+ payment infrastructure in India to studying Sustainable Finance and Fintech at SKEMA Paris. The transition was not a pivot. It was a vertical move.
Fintech Product. Payment Systems. AI-Driven Risk. Europe.
SKEMA Business School · Paris, France