A Bank Trained Its Own Foundation Model to Catch Fraud — Freddy Lecue, Wells Fargo
Wells Fargo pre-trained a transformer from scratch on billions of customer transactions rather than words, then fine-tuned it for fraud detection, credit decisions, anti-money laundering and marketing. The talk covers how tabular transaction data was tokenized, the model's size and training setup, and results that beat the production XGBoost fraud model on both detection and false positives while meeting real-time latency requirements.
