Jaap Stefels & Itzel Belderbos Share How to Tackle Card Testing Fraud at PyData Amsterdam 2025 π
Discover innovative strategies to combat the rising threat of card testing fraud in payments. Join Jaap Stefels and Itzel Belderbos at PyData Amsterdam 2025 for insights on handling fraud without relying on labels.

PyData
333 views β’ Oct 29, 2025

About this video
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Card testing is one of the largest growing fraud problems within the payments landscape, with fraudsters launching millions of attempts globally each month. These attacks can cost companies thousands of euros in lost revenue and lead to the distribution of private card details. Detecting this type of fraud is extremely difficult without confirmed labels to train standard supervised ML classifiers. In this talk, weβll describe how we built a production-ready ML model that now processes hundreds of transactions per second and share the key take-aways from our journey.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
Card testing is one of the largest growing fraud problems within the payments landscape, with fraudsters launching millions of attempts globally each month. These attacks can cost companies thousands of euros in lost revenue and lead to the distribution of private card details. Detecting this type of fraud is extremely difficult without confirmed labels to train standard supervised ML classifiers. In this talk, weβll describe how we built a production-ready ML model that now processes hundreds of transactions per second and share the key take-aways from our journey.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
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Video Information
Views
333
Likes
8
Duration
35:27
Published
Oct 29, 2025
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