A high-performance binning library specifically designed for Credit Risk Modeling and Scorecard Development.
Project description
A high-performance binning library specifically designed for Credit Risk Modeling and Scorecard Development.
In financial risk modeling, Weight of Evidence (WoE) and Information Value (IV) are gold standards for feature engineering. fastbinning ensures mathematical rigor with extreme speed.
Why fastbinning for Credit Scoring?
- Monotonicity Guaranteed: In credit scoring, features like 'Utilization Rate' or 'Age' must have a monotonic relationship with default risk to be explainable and compliant.
- Built for Big Data: While traditional tools struggle with millions of rows,
fastbinninghandles 10M+ records in milliseconds. - Robustness: Prevents overfitting by enforcing minimum sample constraints (
min_bin_pct), ensuring each bin is statistically significant.
Installation
Install using pip:
pip install fastbinning
Example
Please refer to the Examples provided for further clarification.
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