Predictive Credit Default Probability Model

Design an advanced credit risk assessment model using machine learning regression techniques integrated directly into spreadsheet environment. The model should incorporate multiple data sources including financial ratios, market sentiment indicators, macroeconomic variables, and historical default patterns. Develop custom scoring algorithms that generate probabilistic default predictions with confidence intervals, including visual representations of risk stratification and potential loss scenarios.