Oluwakemi-moyin/Loan-Prediction-Model---Africa-Agility-
Domain:
socioeconomicRecord type:
model
Creator:
Olu
Host:
# Loan-Prediction-Model---Africa-Agility
Tools used: Python
## Introduction
The purpose of a loan prediction model is to assess the likelihood of a loan applicant repaying a loan, thereby aiding in risk assessment and loan approval decisions.
## Objective
The goal of a loan prediction data analysis is to:
- Develop a model that accurately predicts the likelihood of loan repayment (or default).
- Identify key factors (features) that influence loan approval and repayment.
- Provide insights to improve loan risk assessment and decision-making processes.
- Minimize financial risk for lenders by reducing loan defaults.
- Potentially streamline the loan approval process.
### The data source used: LOAN PREDICTION DATASET
2. Data Summary & Insights
2.1 Data Overview:
- The dataset consisted of 614 Loan records and 13 columns.
- Key attributes including Loan_ID, Gender, ApplicantIncome, CoapplicantIncome, LoanAmount, Credit_History, Property_Area, and Loan_Status.
- The data showed a wide distribution of Loan applicants across different distinct Property areas, income ranges and genders (male and female).
2.2 Key Observations:
### Findings:
- The analysis revealed that credit history, applicant income, and loan amount are the strongest predictors of loan approval.
- Random Forest Algorithm result: The model achieved an accuracy of 78% on the test dataset
- Logistic Regression Algorithm result: The model achieved an accuracy of 79% on the test dataset
- Support Vector Machines (SVMs) result: The model achieved an accuracy of 79% on the test dataset
### Patterns observed in loan data:
- Credit_History is the most important feature. A credit history indicates how reliably a person has repaid debts in the past.
- LoanAmount :The amount of the loan is also a very strong predictor. Larger loans may be riskier and are thus more closely scrutinized.
- ApplicantIncome :The applicant's income is a crucial factor in determining their ability to repay a loan. Higher i …