This project demonstrates the implementation of a loan approval system that utilizes MongoDB for distributed data storage and management, and PyMongo for database operations. The project aims to automate the assessment of loan eligibility using customer details from online applications.

Data Science Challenge from Coursera Project : Loan Default Prediction

A model for predicting loan default based on historical data.

The project aims to develop a predictive model for loan default using the dataset given by Imperial College London. The goal is to analyse the data, understand the factors that contribute to loan defaults, and create a machine learning model that can forecast the likelihood of loan default for future borrowers.

In this project, I analyzed the prosper load data, studied the trends and concluded that monthly income, loan amount and borrower's rate significantly affect the prosper rating and a good predictors of delinquency.

Credit Risk Analysis - PD Modelling

Data science workflow development to solve credit load default problem, as part of the interview assignment

Final project for my IM1002-232422M - Machine learning class

The project predicts the probability of loan default using various financial features of customer. I applied SMOTENN by combining SMOTE cand Edited Nearest Neighbor (ENN) to handle class imbalance. Logistic Regression, Random Forest and CATBOOST models have been apllied and evaluated based on accuray, F1 score, ROC-AUC score.

A project to compare machine learning algorithms for a loan default dataset using MATLAB.

Goal is to determine whether client (Lending Club) should invest in P2P loans.

Predictive model for loan defaulters using LightGBM, HyperOpt and SHAP model interpretation.

A project aim to predict default rate of Commercial Real Estate(CRE) Loans

Provided two datasets of a finance company trying to figure out the attributes of customers who don't have a sufficient credit history take advantage of this and default on their loans. Task is to use EDA to analyze patterns in the data, ensuring that capable applicants are not rejected with the help of a Machine Learning model.

Predict loan default in a peer-to-peer lending settings

Supervised Machine Learning model predicting loan default using Logistic Regression.

Loan Default Prediction Dataset from Kaggle and default prediction using machine learning techniques

Omega is a loan prediction software, developed with the aim of assisting financial service providers to better vet their loan applicants with ease, efficiency and accuracy

Loan-Default-Prediction

Predict the Home Credit loan default risk based on the applicant's data