Sergey Zelvenskiy

Project RADAR: Intelligent Early Fraud Detection System with Humans in the Loop

Payment fraud is a severe problem for marketplace platforms like Uber. It directly affects the financial stability of the platform as a whole. One of the key challenges to solving this problem is the continuous emergence of new patterns of fraud attacks. In this talk, we will show how the project RADAR brings together algorithms, technology, and experts to efficiently block the fraud early. RADAR uses time-series anomaly detection, feature selection, and pattern mining algorithms. It’s built on top of Uber’s technical infrastructure and data streams. This talk is for the technical and business audience interested in technological innovation behind fraud detection systems.

Sergey Zelvenskiy is a software engneer, algorithm designer, and entrepreneur. He solves complex real-world problems using the combination of software engineering, data pipelines, and machine learning. His current focus is financial fraud detection and mitigation at Uber. Previously he worked on e-commerce, search ranking, fintech, and security domains. Sergey’s algorithmic intestines include deep learning, anomaly detection, pattern mining, search ranking, and NLP. Sergey was a co-founder and founding CTO of ForUsAll - the provider of 401k and financial wellness services, where he built a no-code platform for building financial advice products.

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