Algorithmic Lending & Model Governance

Jul 31, 2026 · 1 min read
projects

Jun 2026 – Jul 2026

  • Built credit-scoring models using Logistic Regression and Random Forest on the German Credit (Statlog) dataset.
  • Conducted SHAP-based explainability and fairness/bias analysis to understand how the model predicts.
  • Identified biases shown by the model based on demographic data and mapped the behaviour to Indian digital governance frameworks.
Machine Learning Credit Scoring Explainability Fairness
Porush Yadav
Authors
Porush Yadav

Hi! I am Porush Yadav. I have graduated from IIT Kanpur with a BS-MS Dual Degree in Mathematics and Scientific Computing. I have Worked at Axis Bank on an image recognition system that leverages neural networks to automate document classification and enhance data extraction. Before that, I interned at Samsung R&D Institute India, eJET systems, and EZ Technologies, where I worked on machine learning applications in signal data compression, recommendation systems, classification systems, and image recognition.

I look forward to leveraging AI and ML expertise to develop impactful solutions that can solve real-life problems.