Open solution to the Home Credit Default Risk challenge 🏡

ESC Team's 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

Python scripts for generating analytic tests for credit portfolio loss distributions

Weight of Evidence，基于iv值最大思想求最优分箱

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

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.

Demonstrating technical elements in support of open source securitisation frameworks

A short course on survival analysis applied to the financial industry

A python package for credit risk card.

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 mirror of the open risk white paper collection

[Project repo] Improving business with a credit risk model

MSc Dissertation on Credit Risk Modeling

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 python framework for credit risk modelling

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

Financial risks of bonds

Course draft - bank corporate lending

A framework for analysing the performance of credit networks

Efficient simulation in the CreditMetrics model with Julia

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.

Home Credit Default Risk in Python

Identifying the creditworthiness of loan applicant and the risk associated with them using exploratory data analysis.

Creating an India credit risk(default) Logistic Regression model