/vkkm:ml-pd — ML-Powered Probability of Default

What problem does it solve?

This Skill automates the calculation of a company's 1-year Probability of Default (PD) using a machine learning model, providing a more nuanced risk assessment than traditional methods like the Altman Z-Score.

Core Features & Use Cases

• ML-Powered PD Calculation: Utilizes a calibrated logistic regression model to predict PD with a 95% confidence interval.
• Feature Importance: Identifies key financial ratios driving the PD prediction.
• Comparison to Altman Z-Score: Contrasts the ML-derived PD with the traditional Altman Z-score zone and its associated PD range.
• Use Case: A credit analyst can input a company's financial ratios and additional metrics to quickly assess its default risk, understand the contributing factors, and compare it against a baseline model.

Quick Start

Run the ML PD model for a private company using the provided financial ratios and additional metrics.