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Application Scorecards are tools that allow organisations to predict the probability that an applicant will behave in a particular way, helping businesses to make effective automated decisions. The most commonly used application scorecard for credit, predicts the risk of a customer paying or not.
Lenders measure your credit application against a set of criteria they have for their ideal customer. The application score is the result of that process, and helps the lender make a decision.
The application score helps you gauge the general performance of each application. Scores are based on how much of the application has been exercised, as well as the amount and severity of vulnerabilities found for that application.
Application scoring is used to evaluate the risk of default when a customer applies for credit, using data like demographic information and credit bureau records. Behavioural scoring, on the other hand, assesses the risk associated with existing customers.
Application scoring takes two snapshots of the customer at different points in time: (i) beginning of the loan and (ii) the default observation point. Behavioural scoring considers the behaviour of the customer during the observation period.
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Scoring Models provide a framework for how applicants are scored based on institutional rating policies. Some Scoring Models also use Point Tables that allow you to assign points based on customized point scales.
Based on the analysis, the behavioral scoring model assigns a credit score or risk rating to the individual, indicating their likelihood of defaulting on loans or missing payments. This score influences lending decisions, debt recovery strategies and interest rates.

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