Building fraud detection infrastructure for the unprotected: open-source fintech from Nepal

South Asia's digital payment ecosystem is growing fast but the fraud infrastructure protecting it hasn't kept up. Platforms serving millions of users often lack real-time device intelligence, have no way to detect SIM swap attacks without KYC dependency, and can't share signals across providers without exposing customer data. The threat model is also genuinely different here: attackers exploit device cycling, identity reuse across platforms, and the absence of cross-institution coordination in ways that Western fraud tooling simply isn't designed for.

This talk explores how you can address these gaps using open-source infrastructure: Go, NATS, PostgreSQL, Python and why releasing client SDKs openly matters as much as the system design itself. We'll cover phone-hash-based SIM swap detection, weighted real-time fraud scoring with cold-start constraints, device fingerprinting without invasive data collection, and the architecture of a scoring pipeline designed to run at payment speed.

These are lessons learned firsthand while building a fraud detection platform targeting Nepal's payment ecosystem the technical decisions, the dead ends, and what a working open-source approach actually looks like in practice.