AI Agents for Advanced Fraud Detection
Evaluated supervised/unsupervised learning, RL, CNNs/LSTMs, GAN‑based augmentation, and NLP phishing detection, plus MAS/cognitive agents for adaptive fraud detection in production‑like settings. Addressed class imbalance, interpretability, ethics/GDPR, and compute constraints; reviewed XAI, federated learning, blockchain integrity, and adaptive models as future enablers.