How we re-architected a Payment Fraud Detection Engine with 300% performance increase

July, 2018 - March, 2020

PythonFlaskGunicornDockerRedisAWSMySQLSQSData PipelineNewRelicMicroservices

This service was built for Xapo, one of the biggest Bitcoin Wallet and Vault services at that time. We redesigned and developed the core engine for their entire transactional fraud detection system that helped Xapo to identify/block fraudulent transactions/account takeover situations in real-time. We were able to improve the performance of their system by 100% along with massive improvement in scalability, extensibility, resilience, and reliability

We built the entire pipeline as a composable system of different plugins and rule engines. Each plugin was responsible to collect/aggregate some piece of data needed for analysis. Similarly, each rule was responsible to analyze one aspect of the transaction and make a local decision. We also designed an ML engine that uses the rules, as well as plugin data to come up with a risk score.

We also integrated a new relic for monitoring and built instrumentation that helped us to evaluate custom metrics at each sub-stage of our system as well for individual plugins and rules across different kinds of transactional events that we supported.

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