ML in Financial Fraud

Modern ML systems analyze transaction patterns and user behavior to flag potential fraud with greater accuracy than traditional rule-based approaches. While deep learning detects complex schemes, challenges like model interpretability and adversarial attacks drive innovation in explainable AI techniques. The field continues to evolve with hybrid models that strike a balance between detection speed and adaptability.