An ensemble of GPT-4 and Gemini prompts, fitted to 300 hand-labeled CFPB complaints, labels scam vs. non-scam fraud with reported precision .95/recall .84 on the same training set and precision .97 on a 133-complaint sample.
As nationwide fraud losses top $10 billion in 2023, ftc steps up efforts to protect the public
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Distinguishing Scams and Fraud with Ensemble Learning
An ensemble of GPT-4 and Gemini prompts, fitted to 300 hand-labeled CFPB complaints, labels scam vs. non-scam fraud with reported precision .95/recall .84 on the same training set and precision .97 on a 133-complaint sample.