Antifraud Architecture with Josh Yudaken
Online marketplaces and social networks often have a trust and safety team. The trust and safety team helps protect the platform from scams, fraud, and malicious actors. To detect these bad actors at scale requires building a system that classifies every transaction on the platform as safe or potentially malicious.
Since every social platform has to build something like this, Smyte decided to engineer trust and safety as a service. Josh Yudaken joins the show today to discuss how Smyte engineered its platform to provide machine learning models for any organization that wants to take advantage of Smyte for its trust and safety.
The tools we discuss include Kubernetes, RocksDB, and Kafka, and Smyte is solving some problems that have not been solved before, so this is a great episode for anyone interested in data engineering or fraud detection–or how to use cloud services and open source tools in unique ways.