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Credit Scoring via Logistic RegressionI

Credit Scoring via Logistic RegressionIAli Al-AradiDepartment of Statistical Sciences, University of Toronto, Toronto, CanadaAbstractThe goal of Credit Scoring models is to predict the creditworthiness of a customer and deter-mine whether they will be able to meet a given financial obligation or default on it. Suchmodels allow a financial institution to minimize the risk of loss by setting decision rules regard-ing which customers receive loan and Credit card approvals. Logistic regression can be usedto predict default events and model the influence of different variables on a consumer s Credit -worthiness.

Logistic regression is used in a wide variety of applications including biomedical studies, social science research, marketing as well as nancial applications. One example of the latter is the use of binary logistic regression models for credit-scoring, that is: modeling the probability that a …

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utstat.toronto.edu

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