Train GPT on historical fraud data and use RPA to collect data from various sources. GPT can then analyze the data and identify potential fraud, flagging suspicious transactions for review.
Ensure that the GPT model is transparent and explainable, and that the flagged transactions are reviewed by human experts before any action is taken.
A risk of using GPT for fraud detection is that the model may not capture all types of fraud or may flag legitimate transactions as suspicious.
Benefits include faster identification of fraud, improved accuracy, and reduced false positives.
