Researchers at the intersection of symbolic AI and fraud detection have demonstrated that neural networks can monitor their own learned rules to catch concept drift before model performance degrades. In controlled experiments using the Kaggle Credit Card Fraud dataset, a hybrid system that combines neural networks with symbolic rule learning detected concept drift in all 5 test runs, sometimes triggering alerts even when traditional metrics like RWSS showed perfect scores of 1.000. The system works by monitoring symbolic rules the neural network discovered on its own—like "IF V14