Fraud teams in Indonesia are under pressure to make accurate decisions in milliseconds while dealing with account takeover, scam activity, promo abuse, mule accounts, and transaction fraud. The challenge is not only the model. It is whether the right context is available at scoring time.
This session is built for fraud engineering and risk platform teams who are struggling to assemble a fraud stack from five vendors and want to see what production-grade fraud infrastructure actually looks like. Presentation, a live demo, and a reference architecture you can take back to your team are just some of the things you should expect from this session.
What you will learn:
Why the model is never the bottleneck and what the context layer failure actually costs you
How to stream live transaction data into your fraud agents at runtime so they score on what is happening now, not last night's batch
How ML teams and fraud agents can operate on the same live, consistent data without maintaining separate pipelines
How to retain cross-session fraud signals so coordinated attacks that look clean in isolation get caught before losses compound
How leading financial institutions are hitting the 300ms payment network decisioning window at petabyte scale
Speakers
Redis
Yoseph Nandana
Solution Architect
Register to attend
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