Credit Risk Prediction
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
Titles
Home Ownership and Loan Amount
Loan Paid Status
City trends in loan repayment performance
State trends in repayment behaviour
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