# Data Scientists Are Using Graph Neural Networks for Fraud Detection Page: https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/data-scientists-are-using-graph-neural-networks-for-fraud-detection Text version: https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/data-scientists-are-using-graph-neural-networks-for-fraud-detection.md Podcast: [The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831) Published: 2026-06-12T10:53:56+00:00 Episode link: https://audio.fexingo.com/business/the-data-science-podcast/episode-0046.mp3 Audio file: https://audio.fexingo.com/business/the-data-science-podcast/episode-0046.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/episodes/data-scientists-are-using-graph-neural-networks-for-fraud-detection Duration seconds: 505 ## Resource Episode 46 of The Data Science Podcast with Fexingo explores how graph neural networks (GNNs) are transforming fraud detection in financial services. Lucas and Luna break down a real case: how a major European bank used GNNs to catch a money-laundering ring that rule-based systems missed. They discuss why traditional fraud models fail with relational data, how GNNs represent transactions as a graph of accounts and connections, and what it means for data scientists building production pipelines. Topics include message-passing layers, inductive vs transductive learning, and the challenge of class imbalance in fraud datasets. The hosts also touch on explainability trade-offs and whether GNNs are ready for real-time scoring. If you're a data scientist curious about graph-based machine learning beyond social network recommendations, this episode gives you a concrete, business-driven example to learn from. #GraphNeuralNetworks #FraudDetection #MachineLearning #DataScience #FinancialServices #AntiMoneyLaundering #GNN #GraphML #MessagePassing #InductiveLearning #ClassImbalance #Explainability #ProductionML #Technology #DataSciencePodcast #FexingoBusiness #BusinessPodcast #ModelDeployment Keep every episode free: buymeacoffee.com/fexingo ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/episodes/data-scientists-are-using-graph-neural-networks-for-fraud-detection/transcription-requests` — Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/data-scientists-are-using-graph-neural-networks-for-fraud-detection.md` — Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.