Credit Risk Prediction

Organization: Loan Tap

Location: India

Project Type: Academic (Scaler)

Duration: Jan 2025 – Feb 2025

Role: Data Scientist / Data Analyst

Project Description

Developed a regression model in Python, to predict credit risk and loan repayment outcomes using customer employment and financial behavior, optimizing feature engineering and trade-offs between precision and recall.

Screenshots

Predictors and Target
Predictors and Target
Predictors and Target
Predictors and Target
Predictors and Target
Predictors and Target
Titles
Titles
Home Ownership and Loan Amount
Home Ownership and Loan Amount
Loan Paid Status
Loan Paid Status
City trends in loan repayment performance
City trends in loan repayment performance
State trends in repayment behaviour
State trends in repayment behaviour
Feature Importance
Which features are most important for predicting loan repayment?

Detailed Tasks

  • Data collection and integration from multiple sources
  • Data cleaning and preprocessing for analysis
  • Exploratory data analysis to identify trends and patterns
  • Feature engineering for model improvement
  • Development of classification models for risk prediction
  • Model evaluation and validation
  • Visualization of key metrics for stakeholders

Core Skills

Machine Learning
Feature Engineering
Data Preprocessing
Risk Assessment
Logistic Regression
Model Evaluation
Data Analysis
Python
Statistical Analysis
Classification Models
Model Validation
Business Intelligence

Tech Stack

Programming & Tools

  • Python
  • SQL
  • Excel

Data Analysis

  • Exploratory Data Analysis
  • Data Preprocessing
  • Statistical Analysis
  • Feature Engineering

Machine Learning

  • Classification Models

Business Impact

  • Achieved 92% accuracy in credit risk prediction