credit-risk-analysis
There are 5 repositories under credit-risk-analysis topic.
semasuka / Credit-card-approval-prediction-classification
Credit risk analysis for credit card applicants
Language:Jupyter Notebook 213- credit-risk-analysis
Amatofrancesco99 / credit-risk-analysis
The aim is to understand which are the key factors for a certain level of credit risk to occur. In addition, some ML models capable to predict the credit risk level for a company in an year - given past years data - have been built and compared.
Language:Jupyter Notebook 13 arunp77 / MonteCarlo-simulation
Application to finance
Language:Jupyter Notebook 12Predicting how much loan will be approved
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- Credit-Risk-Analysis
ankit-kothari / Credit-Risk-Analysis
Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods
Language:Jupyter Notebook 7 Mun-Min / Credit_Risk_Classification
Credit risk poses a classification problem that’s inherently imbalanced. Using a dataset of historical lending activity from a peer-to-peer lending services company, build a model that can identify the creditworthiness of borrowers.
Language:Jupyter Notebook 5chetandudhane / finance-analytics-credit-risk-default
The project involved developing a credit risk default model on Indian companies using the performance data of several companies to predict whether a company is going to default on upcoming loan payments.
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janitbidhan / data-mining
This repository contains projects related to data mining. Data mining finds valuable information hidden in large volumes of data and it is the analysis of data and the use of software techniques for finding patterns and regularities in sets of data.
Language:Jupyter Notebook 2michaelxie1 / Credit_Risk_Analysis
In 2019, more than 19 million Americans had at least one unsecured personal loan. Personal lending is growing at an extremely fast rate, and FinTech firms need to go through an organize large amounts of data in order to optimize lending. Python will be used to evaluate several machine learning models to predict credit risk. Algorithms such as RandomOverSampler, SMOTE, and RandomForest will be used to analyze credit card datasets from a company (LendingClub) and use linear regression to both sample and predict data. This data can be used to determine the number of people who are predicted to be at high/low risk for credit risk.
Language:Jupyter Notebook 2ArtTucker / Credit_Risk_Analysis
Credit risk analysis using scikit-learn and imbalanced-learn.
Language:Jupyter Notebook 1barkamoljon / Barkamol_Portfolio
All Main Projects
ltayara1 / The-Young-and-the-Credit-less
Our group chose this question to bring attention to the little knowledge that young loan applicants have. Based on our findings in our models we explore: Which age group is the least likely to apply for loans? Which group is most likely to default on loans?
Language:Jupyter Notebook 1omveersinghiitdelhi / Credit_Risk_Analytics
This repository contains python code from scratch to develop the credit risk model for loan portfolio
Language:Python 1WideSu / CreditRiskDetection
A data analysis project to classify whether an applicant is capable of paying a home loan by using 4 machine learning models (Logistic Regression, SVM, Random Forest and LGBM) and 1 deep learning model (DeepFM). We also drew some insights from the best model that can be useful for analysts in bank.
Language:Jupyter Notebook 1- Abhijyot-Das
AbhijyotDas / Abhijyot-Das
Portfolio of projects
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Arslan-Mehmood1 / Credit-Risk-Analysis-for-european-peer-to-peer-lending-firm-Bandora
Machine Learning pipelines are deployed to accomplish the objective of credit risk analysis.
Language:Python 0Crossed-finger / Credit-risk-analysis
CSCI316 Group assignment 1
Language:Jupyter Notebook 0dshreesr / credit-loan-analysis
Credit Risk Analysis using Python
Language:Jupyter Notebook 0ramkumarpj / credit-risk-classification
Machine Learning Model for Credit Risk Classification using Scikit Learn Logistic Regression
Language:Jupyter Notebook 0Robyn2024 / Credit_Risk_Classification
I'll use various techniques to train and evaluate a model based on loan risk. I will use a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.
Language:Jupyter Notebook 0Senan25 / Credit_Risk_Modelling-Loan_Default_Prediction
This work is about "Loan Default Prediction" which is one of the most important and critical problems faced by banks and other financial institutions as it has a huge effect on profit
Language:Jupyter Notebook 0yatshunlee / lending-club-credit-risk-analysis
Credit Risk Analysis - PD Modelling
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nirmit27 / credit-risk-modelling
ML Model for predicting the level of risk associated with extending credit to a borrower
Language:CSSnovrizalrnd / credit_risk_analytics
Credit risk analysis determines a borrower's ability to meet debt obligations and the lender's aim when advancing credit. The goal is to identify patterns that indicate if a person is unlikely to repay the loan or labeled as a bad risk through automated machine learning algorithms.
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