Fraud detection, G2N risk management, and AI-powered analytics across Bangladesh, Pakistan, Sri Lanka, and Nepal. Turning platform leakage into strategic clarity.
I lead the G2N Risk function at Daraz (Alibaba Group), the leading e-commerce platform across South Asia. My work sits at the intersection of fraud detection, logistics analytics, and AI deployment across Bangladesh, Pakistan, Sri Lanka, and Nepal.
I operate across two domains with dual reporting: Risk Analytics (Head of Risk) and AI Initiatives (Head of AI). This dual structure means I build analytical frameworks that feed directly into both rule-engine deployment and AI agent development.
My core focus is the gross-to-net (G2N) metric: how much platform revenue actually reaches the bottom line after failed deliveries, cancellations, returns, and subsidy abuse are accounted for. Every workstream I run is anchored to that number.
Three analytically validated workstreams addressing structural gaps in how buyer risk is measured and acted on across South Asian e-commerce markets.
Six years building risk frameworks at the intersection of analytics, fraud detection, and AI deployment across South Asian e-commerce markets.
Writing about fraud detection, COD risk frameworks, delivery analytics, and AI in e-commerce operations from the field.
COD block rules work as designed but solve the wrong problem for a significant segment of buyers. The platform pays twice: once in the failed delivery cost and again when it permanently suppresses a buyer who could have become loyal.
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The best intervention is not always the broadest one. A practitioner perspective on precision over aggression in cash on delivery risk framework design.
Read article →Open to conversations about risk strategy, analytical frameworks, AI in e-commerce operations, and senior analytics roles across Southeast Asia, the Middle East, and globally remote.