Loan approval prediction is a popular machine learning project, especially in the banking and finance industry. The goal of this project is to build a predictive model that can determine whether a loan application will be approved or not based on the applicant's information such as income, credit history, and loan amount.

Loan Approval using Random Forest Algorithm

FoxTrend uses advanced machine learning to provide insightful stock price forecasts and comprehensive company information. The platform also offers additional features, such as car price prediction, loan approval assessment, and housing price estimation.

A Django-based Credit Approval System that intelligently determines loan eligibility and offers real-time insights based on past loan data and customer profiles using PostgreSQL.

Predicting personal loan approval using machine learning techniques

Proof of concept unbiased loan calculator.

Loan Approval Business Process and Web Services parent project

Credit Score Modelling: Perform a Weight of Evidence Logistic Regression Modelling (WoELR) to generate credit scorecard for loan approval.

This project focuses on building a machine learning model to predict the approval status of loan applications based on applicant information. It explores data preprocessing, visualization, feature engineering, and classification modeling.

A web app built with React and Flask to predict loan approval using machine learning. Evaluates user inputs (income, loan amount, CIBIL score) and provides predictions, probability scores, and feature importance.

Loan Approval Dashboard using SQL, Python, and Power BI

Loan approval prediction means using credit history data of the loan applicants and algorithms to build an intelligent system that can determine loan approvals.

Predicts loan approval using demographic and financial data. Includes data cleaning, EDA, feature engineering, and ML models (Logistic Regression, Random Forest). Achieved ~79% accuracy. Full notebook, predictions, and insights documented.

A Cryptocurrency based on Cryptonote Technology that can easily run on your WordPress website, and designed to give you financial freedom

Loan Approval Prediction using Machine Learning | EDA + Decision Tree, Random Forest & Logistic Regression | Automating loan eligibility for Dream Housing Finance by analyzing customer data and predicting loan approvals.