Ryan Drapeau: Battling Fraud with ML at Stripe

Ryan Drapeau: Battling Fraud with ML at Stripe

Author: Daniel Bashir July 20, 2023 Duration: 1:06:31

In episode 82 of The Gradient Podcast, Daniel Bashir speaks to Ryan Drapeau.

Ryan is a Staff Software Engineer at Stripe and technical lead for Stripe’s Payment Fraud organization, which uses machine learning to help prevent billions of dollars of credit card and payments fraud for business every year.

Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub

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Outline:

* (00:00) Intro

* (02:15) Ryan’s background

* (05:28) Differences between adversarial problems (fraud, content moderation, etc.)

* (08:50) How fraud manifests for businesses

* (11:07) Types of fraud

* (15:49) Fraud as an industry

* (19:05) Information asymmetries between fraudsters and defenders

* (22:40) Fraud as an ML problem and Stripe Radar

* (25:45) Evolution of Stripe Radar

* (31:38) Architectural evolution

* (41:38) Why ResNets for Stripe Radar?

* (44:15) Future architectures for Stripe Radar and the explainability/performance tradeoff

* (48:58) War stories

* (52:55) Federated learning opportunities for Stripe Radar

* (55:50) Vectors for improvement in Stripe’s fraud detection systems

* (59:22) More ways of thinking about the fraud problem, multiclass models

* (1:03:30) Lessons Ryan has picked up from working on fraud

* (1:05:44) Outro

Links:

* How We Built It: Stripe Radar

* Stripe 2022 Update



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Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
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