AI for Fintech

Transaction risk model for a major online payment platform

Transaction risk model for a major online payment platform

A team from Modulai trained a model to predict risk in direct banking transactions. The project included a full specification of the decision engine infrastructure as well as the deployment plan.

This client is a large Fintech company in the payments space, providing an alternative to credit card payments. They process many millions of transactions yearly for thousands of e-commerce sites and online service providers. Each transaction might expose the different parties to various risks, and containing these risks is crucial.

The data was largely structured and tabular but of various types. The team focused on careful feature engineering with implementability in mind. A gradient boosting model architecture was chosen for maximum prediction accuracy.

The preprocessing and modeling flows were built with Python open-source libraries, and the proposed implementation is based on various managed cloud services.

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