Xendit Built a Counter-Fraud Watchlist for the Fintech Industry

Summary

Payment processor Xendit needed a fast, cost-effective counter-fraud watchlist system to screen transactions against international sanctions lists in real time without relying on expensive providers like Worldcheck or Refinitiv. Leveraging their existing familiarity with Postgres, the team loaded parsed sanctions lists from the United Nations and the Indonesian government into Supabase. They implemented full-text search using the Postgres Trigram extension, enabling relevance scoring across queried records. A dedicated database function handles the search queries directly via Xendit's Python clients, allowing the entire solution to reach production in under one week. The deployment has operated reliably in production for nine months without issues, with potential future iterations planned around machine learning techniques.

Context

As a payment processor, Xendit must perform real-time anti-money-laundering checks by verifying suspicious transactions against international sanctions lists to prevent delays on legitimate payments. They required a fast, scalable solution that was more cost-effective than using commercial vendors such as Worldcheck or Refinitiv.

Approach / What changed

Xendit parsed sanctions lists from the UN and the Indonesian government and loaded them into Supabase. Using the Postgres Trigram extension, they enabled full-text search with relevance scoring and exposed the capability through a database function called directly by Python clients.

Takeaways

• Xendit parsed international sanctions lists from the United Nations and the Indonesian government into Supabase to power real-time anti-money-laundering checks.
• The Postgres Trigram extension was used to provide full-text search capabilities with relevance scoring over the sanctions data.
• A custom database function allows direct search execution from Python clients, enabling the team to build and deploy the production system in under a week.

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