Callum Court - Multi-tasking fraud detection From Trees to MLPs | PyData London 25

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Multi-Task Learning for Fraud detection: From Trees to MLPs

This talk will present Monzo's exploration of multi-task deep learning to enhance our real-time fraud detection systems. I will outline the challenges of card fraud detection, and explain the limitations of traditional gradient boosted decision tree models in terms of generalisation to rare fraud subtypes. This will motivate the use of multi-task learning, which leverages shared dense representations across fraud sub-tasks. By consolidating multiple specialist learners into a single model, we observe improved performance on less prevalent fraud types, leading to better generalisability, scalability, and robustness. I will also share results from testing multi-task models within our fraud detection infrastructure.

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