Credit scorecards

Credit scorecards are mathematical models which attempt to provide a quantitative measurement of the likelihood that a customer will display a defined behavior (e.g. loan default, bankruptcy or a lower level of delinquency) with respect to their current or proposed credit position with a lender. Scorecards are built and optimized to evaluate the credit file of a homogeneous population (e.g. files with delinquencies, files that are very young, files that have very little information). Most empirically derived credit scoring systems have between 10 and 20 variables for UK scorecards. Indeed there has been an increasing trend to minimize applicant or non-verifiable variables from scorecards which has increased the contribution of the credit bureau data.

Credit scoring typically uses observations or data from clients who defaulted on their loans plus observations on a large number of clients who have not defaulted. Statistically, estimation techniques such as logistic regression or probit are used to create estimates of the probability of default for observations based on this...
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