Question
A financial organization implements a new AI-based fraud detection system to flag suspicious transactions. A security analyst discovers that it occasionally blocks legitimate transactions. Which of the following is the best recommendation?
- A. Retraining the model with more data and recent transaction patterns Correct
- B. Implementing AI token usage and rate limits
- C. Encrypting all the data processed by AI and applying further access controls
- D. Rolling back the model and using a traditional fraud detection system
Explanation
Occasional false positives mean the model is not representing current legitimate behaviour well, so retraining it with more data and recent transaction patterns improves its accuracy. Token usage and rate limits control consumption and abuse, not classification quality. Encryption and access controls protect the data but do not change the model's decisions, and rolling back to a traditional system discards the AI benefits instead of fixing the cause.
