1. Data Integration: Combining diverse datasets to provide a comprehensive risk profile. 2. Pattern Recognition: Identifying subtle patterns that traditional statistical methods might miss. 3. Predictive Accuracy: Improving the accuracy of predictions through iterative training and validation of models. 4. Dynamic Updates: Allowing for continuous updates to risk models as new data becomes available.
