LunCH Lecture –

Graph Theory for Fraud Detection at

Conventional fraud detection has historically been centered around linear relationships between user indicators. The weak point of this setup is that we miss out on transitive relationships, which becomes an increasingly interesting factor when fraudsters reuse few overlapping indicators in new fraud attempts.

In this presentation we will show how we developed an in-house technological ecosystem that stores fraud attempts in graph format and leveraged state of the art algorithms to compute innovative graph features that enriches our existing fraud controls (ML models and static rules).

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