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InfoQ Homepage Presentations Solving Payment Fraud and User Security with ML

Solving Payment Fraud and User Security with ML

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Summary

Soups Ranjan talks about Coinbase’s risk program that relies on machine learning (supervised and unsupervised), rules-based systems as well as highly-skilled human fraud fighters. He presents attack trends and techniques they've seen throughout the past years and how the entire system has worked in cohesion allowing them to stay a step ahead of the bad actors.

Bio

Soups Ranjan is the Director of Data Science at Coinbase, one the largest bitcoin exchanges in the world. He manages the Risk & Data Science team that is chartered with preventing avoidable losses to the company due to payment fraud or account takeovers. He has previously led the development of Machine Learning pipelines to improve performance advertising at Yelp and Flurry.

About the conference

Software is changing the world. QCon empowers software development by facilitating the spread of knowledge and innovation in the developer community. A practitioner-driven conference, QCon is designed for technical team leads, architects, engineering directors, and project managers who influence innovation in their teams.

Recorded at:

Oct 05, 2017

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