credit-risk

Open solution to the Home Credit Default Risk challenge 🏡

ESC Team's credit scorecard tools.

Credit Risk analysis by using Python and ML

Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics

Monotonic Optimal Binning in Consumer Credit Risk Scorecard Development

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.

Weight of Evidence，基于iv值最大思想求最优分箱

[Project repo] Improving business with a credit risk model

A short course on survival analysis applied to the financial industry

Credit scoring modeling toolbox based on R

A predictive model that uses several machine learning algorithms to predict the eligibility of loan applicants based on several factors

Curriculum for Finance

Final work report of Google Summer of Code 2021 with Hydra Ecosystem

Demonstrating technical elements in support of open source securitisation frameworks

This project commissions to examine the 100,000 credit card application data, detect abnormality and potential fraud in the dataset. All data manipulation and analysis are conducted in R. Featured analysis methods include Principal Component Analysis (PCA), Heuristic Algorithm and Autoencoder.

A public repository to facilitate the discussion / development of OpenCPM

MSc Dissertation on Credit Risk Modeling

Using various machine learning models to predict whether a company will go bankrupt

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.

A python package for credit risk card.

A python framework for credit risk modelling

Financial risks of bonds

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.

A mirror of the open risk white paper collection

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.