Credit-Risk-Model

Credit scorecards are basically used to assess credit worthiness of customers. Credit scorecards are heavily used in the industry for taking decisions on granting credit, monitoring portfolio, calculating expected loss. German Loan data-set (publicly available credit data) is used to build credit scorecard for customers. The data set has historical data on default status of 1000 customers and the different factors that are possibly correlated with the customer's chances of defaulting such as salary age, marital status etc. and attributes of the loan contract such as term, APR rate etc. A classification model (using algorithms like Logistic Regression, XgBoost) is built to classify good and bad customers. Using this model to score new customers in future and lend loans to customers that have a minimum score.