Advanced Fraud Analyst

Example Use Cases

• 1

  Detect fraudulent transactions using AI-powered anomaly detection.

• 2

  Aggregate and utilize threat intelligence data in fraud investigations.

• 3

  Clear explanations of risk scores to support decision making.

Description

This project provides an advanced fraud analysis assistant that inspects transactions for anomalies, aggregates threat intelligence, and explains risk scores to investigators. It leverages large language models integrated with external tools such as threat intelligence APIs and validation modules. The system is designed to handle sensitive information securely and includes safety measures against prompt injection and jailbreak attacks. It aims to improve fraud detection accuracy and provide transparent risk explanations for better investigation outcomes.