In this talk at the IMC Summit Europe on June 20, David Maitland
VP Sales, EMEA at Redis Labs, explains why a real-time fraud intelligence platform requires machine learning capabilities as well as customizability by industry, to be effective.

For example, in an online travel business, understanding where a flight ticket is purchased and where a user is going has an impact on determining fraud. But for a gaming company, the metrics for understanding fraud are somewhat different, as it's important to understand how a user buys an in-game credit and how soon thereafter that credit used.

Simility implemented a sophisticated platform, both as a service as well as on-premises software, delivering rapid fire fraud analytics across millions and billions of data points.

To handle millions of transactions per hour, and to accomplish transaction and analytic processing in milliseconds, for in-line systems such as financial services and travel customers, in-memory computing becomes a requirement. Simility’s complex scale out microservices based architecture incorporates Redis and Cassandra. Join this session to learn about their experience incorporating machine learning algorithms in real time to detect fraudulent behavior and the technology stack that maximized scale and availability.

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