AI Powered Fraud Detection for Payments & Transactions
summary
Claims that AI detects fraud in real time using anomaly detection (autoencoders, clustering), supervised predictive modeling (logistic regression, gradient boosting, neural nets) and pattern recognition (RNNs, graph neural networks). Tools named include TensorFlow, PyTorch, H2O.ai, spaCy, GPT models, AWS Comprehend, Google NLP, DataRobot, Amazon Fraud Detector and FICO Falcon. Cited numbers: $48B annual payment fraud, 85% of attacks use AI, Visa scores transactions on 500+ attributes (1–99), 6M transactions processed in two minutes; a Visa initiative blocks ~$350M and 12,000 scam merchants, saving $27M for victims.
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chapters (12)
- 0:00AI fraud detection intro
- 1:25Fraud detection critical now
- 3:31Cost of payment fraud
- 7:27Traditional fraud limits
- 9:38AI transforms fraud systems
- 11:48AI vs traditional methods
- 16:48Core AI techniques
- 21:46AI tools for text fraud
- 23:10Visa’s AI success story
- 29:52How Visa’s AI learns
- 30:15AI necessity in fraud fighting
- 30:57Q&A explainability & future
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