Cliff857/My_first_project

A machine learning model to predict Loan defaulters in Ghana. # INTRODUCTION AND PROBLEM STATEMENT GhanaLoanConnect is currently facing a growing challenge with non-performing loans. To improve the accuracy of credit decisions and reduce default risk, this project applies supervised machine learning to build a predictive model. Using a dataset of borrower profiles—including financial, demographic, and transactional information—we aim to: 1. Explore and clean the data 2. Engineer and transform useful features 3. Train and compare several classification models 4. Evaluate performance using relevant metrics 5. Interpret the results and provide actionable recommendations The ultimate objective is to equip GhanaLoanConnect with a model that flags high-risk borrowers early and supports smarter loan approvals.