whkung0903/kenya-loan-credit-prediction

# Kenya Loan Default Prediction A course project (BA810 Supervised Machine Learning, Fall25 Instructor: Nachiketa Sahoo) Boston University, Master of Business Analytics Team leader: Grace Kung Team Members: Bruce Liu, Emily Su, Allen Chiu ## Project Overview ### Problem Definition Using loan information & macro-economic indicators to predict Default / Paid, we identify high-risk applicants, minimize defaults & costs, and ensure balanced lending practice. ### Business Value * For financial institutions: Risk Mitigation, Optimized Lending Decisions, Revenue Growth * For borrowers: Fairer Loan Terms, Financial Inclusion * For government: Economic Stability, Trust in Financial Systems ### Data Sources * Kenya Loan Dataset * Kenya Monthly Economic Indicators ### Data Dictionary ##**2.3 Data Dictionary** Data Size: 66854 rows x 26 columns | Column Name | Data Type | Description | |----------------------------------|------------------|-------------| | ID | int64 | A unique identifier for each entry in the dataset. | | customer_id | int64 | Unique identifier for each customer in the dataset. | | country_id | object | Identifier or code representing the country where the customer resides or where the loan was issued. | | tbl_loan_id | int64 | Unique identifier for each loan associated with the customer. | | lender_id | int64 | Unique identifier for the lender or institution that issued the loan. | | loan_type | object | The category or type of loan. | | Total_Amount | float64 | The total loan amount initially disbursed to the customer. | | Total_Amount_to_Repay | float64 | The total amount the customer is expected to repay, including principal, interest, and fees. | | disbursement_date …