Machine Learning Credit Risk Prediction Model

Construct an advanced machine learning model for predicting credit default probability using ensemble learning techniques. The model must combine gradient boosting, neural networks, and probabilistic graphical models to achieve >92% prediction accuracy. Implement robust feature engineering that handles non-linear relationships, manages sparse financial datasets, and dynamically adapts to emerging economic indicators.