Home Credit Default Risk (Individual)

Case synopsis

Home Credit cares deeply about the population without sufficient credit history and aims to improve inclusion for this underrepresented group by designing prediction models for loan repayment, such that capable borrowers are not denied solely due to absence of credit while protecting against defaults.

Refer to group project notebooks for additional detail.

Model: Support Vector Machine

Exploring the performace of a support vector machine model on predicting "default".

model svm quarto r

Model: Penalized Regression

Exploring the performace of an elastic net, penalized logistic regression model on predicting "default".

model elastic net quarto r
Vector Graphic of Data Analysis

Exploratory Data Analysis

Exploring Home Credit current and historical applications with third-party data, mining for insights that would help the future predictive models.

eda quarto duckdb python