credit-risk
There are 330 repositories under credit-risk topic.
Home-Credit-Default-Risk
In this project we try to predict home credit default risk for clients. We try to predict, if the client will have payment difficulties or not.
OpenCPM-Architecture
A public repository to facilitate the discussion / development of OpenCPM
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.
Google-Summer-of-Code-2021
Final work report of Google Summer of Code 2021 with Hydra Ecosystem
credit-eda-case-study
Should you get a loan? Will you pay on time?
migrate
An R package for building state transition matrices
msc-dissertation-credit-risk-model
MSc Dissertation on Credit Risk Modeling
IBRD-credit-scorecard-predictive-engine
Innovative solution for credit scoring leveraging machine learning to predict credit risk using The International Bank for Reconstruction and Development (IBRD) Loans dataset.
Credit-Scoring-and-BASEL-IRB-Model
The objective of this project is to predict credit score of the borrowers using logistic regression and provide threshold cut-off recommendation
bonds-risk
Financial risks of bonds
Banking-Risk-Assessment-ML
A comprehensive machine learning solution for assessing credit risk in the banking sector. This project leverages advanced algorithms to evaluate and classify the creditworthiness of customers, aiming to enhance decision-making in loan approvals and risk management.
credit-risk-analysis-using-ML
Credit Risk Analysis using Machine Learning models
Underwriting-Module
Our underwriting python module for underwriting credit card accounts. For enterprise partners wanting to do their own underwriting in-house.
tool-credit-risk-modelling
Tool demonstrating building credit risk models
Credit_Risk_Analysis
Evaluate the performance of multiple machine learning models using sampling and ensemble techniques and making a recommendation on whether they should be used to predict credit risk.
2nd_Project
This is our second project at neuefische DS Bootcamp. Silas Mederer (https://github.com/sls-mdr) and me applied different ML models and for credit default prediction of the P2P platform Lending Club.
CreditMetrics.jl
Efficient simulation in the CreditMetrics model with Julia
Home-Credit-Default-Risk
Objective of this competition is to use historical loan application data to predict whether or not an applicant will be able to repay a loan.
roll_rate_analysis
Roll Rate Analysis python package. Both month over month and snapshot roll rate functionalities are supported. It utilizes Polars library for optimization and speed.
Credit_Score_Classification_System
A credit score classification is a system used by lenders and financial institutions to assess an individual's creditworthiness. A credit score is a numerical representation of a borrower's credit history, ranging from 300 to 850. The higher the score, the better the borrower's creditworthiness.
credit-risk-classification
This is a program to predict the possible risk of default on credit card use.
Credit-Scoring-Home-Credit
The objective of this project is to predict credit score of the borrowers using logistic regression and provide threshold cut-off recommendation
Credit_Risk_Classification
Classification Modeling: Probability of Default
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.
discrust
Supervised discretization in Rust
Academy-Course-PYT13013
Supporting material for the Open Risk Academy course: "Concentration Measurement Using Python"
CreditRiskAndClimateChange
This project aims at jointly modeling physical and transition risk within a Merton-like credit risk model, building up on [Bouchet and Le Guenedal, 2020]
credit-model-tree
By the data set from 'Give Me Some Credit' (2012), this work is to use it to illustrate some useful techniques in Credit Scoring Modelling, namely: GLM, SMOTE, CARET, CHAID, and MOB.
rosaceae
A python package for credit risk card.
CreditRisk
CreditRisk predicts bank credit risk using machine learning model to classify safe and risky credit applicants, offering insights through data ingestion, transformation, model training, and prediction.
Credit-Card-Approval-Prediction
Ipynb file of an Ensemble model used to train for credit card approvals using UCI machine learning dataset
Credit_Risk_Machine_Learning_Model
Predictive model to classify prospective customers based on their likelihood of getting approved for credit.
DataBrokerOptOut
Data Broker Opt Out is a Python script that provides a convenient way to access opt-out pages of various data brokers on the web. Data brokers are companies that collect, analyze, and sell personal information, and opting out from their services can enhance your privacy.
Risk_analysis
Repository represents python usability of measuring and managing risks (practice tasks and real cases)