amneh992/Loan-Default-Prediction

A machine learning project to predict loan default risk using financial and credit history data. Built as part of a team capstone project in master degree at Deakin University.

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JensBender/loan-default-prediction

Leverage machine learning to predict loan defaults from customer application data of financial institutions.

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princenzmw/Loan_Default_Prediction

Predicting Loan Default (Banking) is a Model to predict whether a customer will default on their loan based on their financial history and loan type.

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imrun10/Loan-Default-Prediction

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

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diarray-hub/predicting-loans-defaults

Binary classification to predict defaults on loans

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GeniDT/loan-default-prediction

Predicting the likelihood of a loan application resulting in a default based on various variables in the application.

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hq969/Loan-Eligibility-Prediction

The Loan Eligibility Prediction Module is a machine learning-based system designed to assess whether an applicant qualifies for a loan based on financial history, credit score, income, and other key factors. The project involves data preprocessing, feature selection, model training, and evaluation to ensure accurate predictions.

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nickhuo/Loan_Prediction

Developed a loan prediction model using logistic regression to evaluate loan applications based on credit factors. It is adapted from a Kaggle competition.

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art-test-stack/credit_risk_eval_model

Replication of the paper "Credit risk evaluation model with textual features from loan descriptions for P2P lending", Zhang et al. (2020), published in Electric Commerce Research and Applications.

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RelentlessDiscipline/Predicting-Loan-Default-with-a-Machine-Learning-Credit-Model

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rohit180497/NBFI-Loan-Repayment

This project aims to build an end-to-end loan default prediction system for a Non-Banking Financial Institution (NBFI). The system is designed to ingest, clean, process, and predict loan default probabilities while ensuring model deployment, monitoring, and automated CI/CD.

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brendancsmith/credit-risk-modeling

Credit Risk Modeling using XGBoost in Python

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Ujjwal-Jaiswal-UJ/Loan-Risk-Assessment

I successfully developed and evaluated machine learning models, specifically Logistic Regression and Random Forest, to predict credit defaults. Furthermore, I leveraged the power of Power BI to visualize model performance, analyze feature importance, and explore the relationships between key variables and default probability.

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sachnaror/mortgage_calc

Crunch numbers, not your dreams! This Advanced Mortgage Calculator is your financial GPS, adjusting for credit scores, taxes, and property quirks. Fast, accurate, and fun to use—because who said adulting can’t come with a sleek UI and a touch of financial wizardry? 🏠✨

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himanshkr03/Loan_Default_Prediction_Using_Machine_Learning

This repository contains a Python-based project that uses machine learning to predict loan defaults. It explores data preprocessing, feature engineering, and model training techniques to build a predictive model for assessing loan risk.

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smreynolds92/Great-Learning

MIT - Applied Data Science Program: Leveraging AI for Effective Decision-Making Certification

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faizpuad/DataScienceProject-LoanDefaultAssessmentUsingClassificationAlgorithm

Loan default risk prediction for NotALoanShark using Logistic Regression. Focused on data exploration, cleaning, and feature selection to identify high-risk borrowers and reduce financial risk

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MunjPatel/Bayesian-Networks-A-Practical-Guide

This repository demonstrates the application of Bayesian Networks for modeling relationships between variables, enabling data-driven predictions and decision-making. It includes real-world use cases such as disease prediction, loan default classification, weather forecasting, and stock price forecasting.

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sollua/Payment_Model

delinquency calculation for retail loans

Language: Java - Size: 39.1 KB - Last synced at: 5 months ago - Pushed at: over 8 years ago - Stars: 0 - Forks: 1

EC4308/loan-default

Created a loan default classification model at the point of granting a loan

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mriusero/loan-default-prediction-mlops 📦

This project builds a predictive model to evaluate the default risk of personal loans within retail banking. Leveraging an MLOps pipeline, it ensures efficient, scalable, and reliable model deployment on AWS, with a user interface created in Streamlit. The project incorporates experiment tracking, model tuning, and containerization.

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mahnoorsheikh16/Loan-Default-Prediction

Credit risk is the borrower’s inability to repay a loan. Machine Learning models can predict risky customers and reduce lender losses. By analyzing behavior and demographics of past customers, these insights can apply to future customers for better loan decisions. This study aims to find the most suitable model for predicting loan defaults.

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johnsonhk88/Data-Science-Challenge-Coursera-Project-Loan-Default-Prediction

Data Science Challenge from Coursera Project : Loan Default Prediction

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rosaaestrada/Loan-Default-Feature-Analysis

Logistic Regression, Random Forest, and Decision Tree to predict what factors influence loan default in the U.S.

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Trueprince/Loan-default-Predictor--Capstone-Project

Loan default predictor using Various Machine Learning Algorithms

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Vatshayan/Btech-Loan-Predication-Project

Minimization of risk and maximization of profit on behalf of the bank

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Medkallel/Loan-Default-Prediction

This project aims to predict loan defaults in retail banking using an end-to-end MLOps pipeline. It includes data preprocessing, model engineering, CI/CD, model tracking and cloud deployment of the best model via a Flask app

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ibrahimgb/ML-Ops

Prévision de prêts, solution et déploiement

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Abhinav330/Loan-Repayment-Analysis

This repository implements a machine learning workflow for predicting loan defaults using Python libraries: pandas, seaborn, matplotlib, and scikit-learn. It analyzes the loan_data.csv dataset to classify applicants as likely to default (binary classification).

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sowmyamanojna/Loan-Default-Prediction

This repository contains all material related to the project done as a part of the course Introduction to Data Analytics (MS4610) in the Fall 2020 semester.

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zachtheyek/Loan-Default-Prediction

EDA on loans & payments datasets for modeling risk of loan default.

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Toluwaa-o/Loan-Default-Classification

Develop a robust machine learning model to accurately classify whether a new loan borrower is likely to default, thereby aiding ABC Bank in minimizing financial risks associated with loan defaults.

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cheshtadhingra/LendingClub

This project builds a model to predict if Lending Club loans will be fully paid or charged off. Using completed loan data, it includes credit history and loan grades but excludes FICO scores and rejected loans due to limited data. Methodologies and results are documented for accuracy and fairness.

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MeghanPokorski/Loan-Default-Prediction

[Project Repo] Bank loan default prediction with machine learning models

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Owadd/Credit-Risk-Assessment

This project aims to predict credit risk for individuals applying for loans, classifying whether they will default based on features such as age, income, employment length, loan amount, interest rate, percentage of income, credit length, home ownership, and loan intent.

Language: Python - Size: 1.35 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

leongrammy03/dApp-Micro-Loans

Decentralised Loan App Running On Local Ehtereum Blockchain

Language: Python - Size: 101 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

abhishekdbihani/Home-Credit-Default-Risk-Recognition

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

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NdAbdulsalaam/Prosper_loan_eda

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.

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abiodunarabaa/Loan-Default-Prediction-with-Python

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.

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AaronXxx1024/Empirical-Comparision-of-Classification-Methods-on-2018-FICO-xML-data

Supervised Learning Practice on Borrowers Behaviour

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kkpro18/PredictingLoanDefaults

Predicting Loan Defaults using 15+ Features and over 250,000 records

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Geo-y20/Loan-Approval-Automation-Using-MongoDB-and-PyMongo

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.

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rishikksh20/Loan-Prediction-Challenge

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george-mitchell/Predicting-Loan-Default

A model for predicting loan default based on historical data.

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rbhatia46/LendingClub-Loan-Analysis

Lending Club Loan Default Analysis using historic loan applications data.

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SannketNikam/Credit-Risk-Analysis

Credito - Credit Risk Analysis using XGBoost Classifier with RandomizedSearchCV for loan approval decisions.

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Manpreet1377/Loan-Delinquency-Prediction

Loan default prediction is one of the most critical and crucial problem faced by financial institutions and organizations as it has a noteworthy effect on the profitability of these institutions. In recent years, there is a tremendous increase in the volume of non – performing loans which results in a jeopardizing effect on the growth of these institutions. Therefore, to maintain a healthy portfolio, the banks put stringent monitoring and evaluation measures in place to ensure timely repayment of loans by borrowers. Despite these measures, a major proportion of loans become delinquent. Delinquency occurs when a borrower misses a payment against his/her loan. Given the information like mortgage details, borrowers related details and payment details, our objective is to identify the delinquency status of loans for the next month given the delinquency status for the previous 12 months (in number of months).

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pkiage/tool-credit-risk-modelling

Tool demonstrating building credit risk models

Language: Python - Size: 487 KB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 3

Nikita9779/Loan_Default_Prediction_

Business Objective : To classify if the borrower will default the loan using borrower’s finance history. That means, given a set of new predictor variables, we need to predict the target variable as 1 -> Defaulter or 0 -> Non-Defaulter.

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imrun10/ML-Loan-Default

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

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KunutBoon/interview-assignment

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

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RSAKIB78/Machine-Learning-Credit-Risk-Prediction-R

ML analysis to predict customer default

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lemoinef/Loan-Default-Prediction

Capstone Project: Predicting default in P2P lending

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yatshunlee/lending-club-credit-risk-analysis

Credit Risk Analysis - PD Modelling

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4rn3/loan_default_prediction

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

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pHequals7/Loan_Application_Prediction

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muhammadfhaider12/loan-default-prediction

The project predicts theprobability 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.

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AjNavneet/CreditRiskPrediction_LightGBM_Hyperopt_SHAP

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

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Akshay6045/Loan-Default-Prediction

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

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Luissalazarsalinas/Loan-Default-Prediction

Loan Default Detector App built with XGBoost, FastApi, Docker and Streamlit

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HaHaIamHarry/Commercial-Real-Estate-CRE-Loan-Credit-Risk-Model

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

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ROCeey/Credit-Default-Prediction

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

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avannaldas/Loan-Defaulter-Prediction-Machine-Learning

Prediction of loan defaulter based on more than 5L records using Python, Numpy, Pandas and XGBoost

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avijay24/PredictiveAnalysisforLendingClub

Predictive Analysis of Lending Clubs loans to predict whether a loan may default or not using R

Size: 18.3 MB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

harmonizerblinks/loanapi

Loan Management System and daily collection Api For Financial institutions.

Language: C# - Size: 231 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 16 - Forks: 25

nataberishvili/nataberishvili.github.io

Size: 255 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

Niranjankumar-c/IndiaML_Hiring_Hackathon_2019

India ML Hiring Hackathon by Analytics Vidya. Analytics Vidhya is proud to present the "India Machine Learning Hiring Hackathon- 2019" - India's Largest Hiring Hackathon where every data science aspirant and professional will get an opportunity to showcase their talent

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CuiyiLIU/Credit-Default-Risk-Evaluation-on-the-Unbanked-Population

In the present years, credit loan becomes one of the most important fundraising approaches for individuals or companies. And with this tendency, credit risk attracts more attention to the financial industry. How to make a reliable prediction of clients’ repayment abilities turn into a significant research project.

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Niranjankumar-c/CreditRiskAnalytics

Predicting the default customers

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vishnukanduri/Credit-Risk-Modeling-in-Python

Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discrete variables using various techniques depending on the feature. Checked for missing values and cleaned the data. Built the probability of default model using Logistic Regression. Visualized all the results. Computed Weight of Evidence and price elasticities.

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dudehacker/Bank-Loan-Default

Predict bank loan default

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botdotpy/ML-Loan-default-prediction

Supervised Machine Learning model predicting loan default using Logistic Regression.

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manjeet13/loan-default-prediction

Language: Jupyter Notebook - Size: 2.12 MB - Last synced at: over 1 year ago - Pushed at: almost 7 years ago - Stars: 1 - Forks: 4

harishpuvvada/LoanDefault-Prediction 📦

Lending Club Loan data analysis

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gneisscode/Client

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

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Soumalya-B/datascience

My projects and practices on various segments of machine learning and deep learning.

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yrnigam/UCI_Credit_Card_Default

This dataset contains information on default payments, demographic factors, credit data, history of payment, and bill statements of credit card clients in Taiwan from April 2005 to September 2005.

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yashkim77/AV_LTFS_Data_Science_FinHack_ML_Hackathon

LTFS Data Science FinHack ( ML Hackathon)

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MarcoZazzini1989/load-default-using-machine-learning

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

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YangLei2586/Loan_Classification_using_SQL_Server_R_services

Building a in database prediction model to leverage SQL Server 2016 as a Scoring Engine to predict "bad" loans

Language: PLpgSQL - Size: 4.88 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 1

YangLei2586/Build_the_best_Classifier_for_Loan_default_Prediction

Build Machine Learning Models for Loan Default Prediction using different algorithms including Decision Tree, K Nearest Neighbor,Support Vector Machine, Logistic Regression. And then evaluate the different model performances to choose the best one for production.

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zhousrhhh/Loan-Default-Prediction

Loan-Default-Prediction

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jarni66/loan_status_prediction

This project develops a machine learning model to predict loan status and assess credit risk, aiding banks in making informed lending decisions, reducing defaults, and enhancing financial stability.

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kelvinjuliusarmandoh/loan-approval-prediction

Implementing Machine Learning for predicting loan approval

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Jigisha-p/Home-Loan-Prediction

A model that predicts whether an applicant will be able to repay a loan using historical data

Language: Jupyter Notebook - Size: 32.3 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

jsutch/Decision_Trees_and_Random_Forests

Decision_Trees_and_Random_Forests

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naumanthunder22/business_analytics

Loan Defaulter's Prediction using Statistical Analysis

Size: 27 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

moggirain/Loan_default_analysis

American loan default analysis

Language: R - Size: 1 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0

dell-datascience/Prosper_Bank_Loan_Data_Exploration

The main interest of this project is to study the borrowers of prosper bank, especially their loan status along with other features to understand what factors affect a loan status of a borrower

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kr900910/lendingclub_loan_default

R exercise to predict probability of default of LendingClub personal loans

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saqib772/Loan-Status-Prediction

Loan Status Prediction Using Machine Learning | End To End Machine Learning Project

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riyasql/Problem-Statement-Exploratory-Data-Analysis

Uni-variate and Bi-variate analysis to understand the driving factor behind loan default

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sidharthamondal/datasets

python_datasets

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PiyushG0999/Bank-Loan-Case-Study

Risk Analytics using Python

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stankovix/Loan-Prediction

The project entails building a model that predicts if someone who seeks a loan might be a defaulter or a non-defaulter. We have several independent variables like, checking account balance, credit history, purpose, loan amount etc. Ensemble Models such as Bagging, AdaBoosting, GradientBoost, XGBoost, Random Forest etc will be used for the modelling

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rajneeshvsht/Loan-Default-Prediction-using-Artificial-Neural-Networks

The goal of this project is to build a Deep Learning model using ANN to predict if a person will default on the loan based on the loan and personal information provided.

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Promeos/Home-Credit-Default-Risk

Using data provided by Home Credit Group, this project aims to predict the probability of loan applicants defaulting on their payments using various machine learning techniques.

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FataiAzeez/svm_loan_prediction

The repo contains a loan prediction model implemented in python using the SVM algorithm. The model predicts loan approval based on historical loan application data

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lapuzshawn/zz-Underwriting-App

Underwriting Loan Doc Generator: Business and Real Estate Investment DL App

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shreshthvashisht/Bank-Loan-Case-Study

Risk Analytics using Python

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