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. This supports you as a business to make automated, accurate and consistent decisions on whether to approve, review or decline applicants.
Application scorecards can also help you predict many other different metrics such as:
- An applicant’s affordability (ability to pay)
- Potential future profitability
- The likelihood to churn (attrition) etc.
- In the case of a credit risk application scorecard the output is usually a numeric score provided for eachapplicant, with higher scores corresponding to lower levels of estimated risk.
Our application scorecards can enable you to:
- Automate the application decision processes, reducing the cost of manually underwriting applications.
- Facilitate the ability of businesses to make accurate, consistent, fact-based decisions.
Flexibly optimise and manage credit risk strategies including:
- Portfolio approval and bad debt management
- Risk based pricing – offering preferential terms (e.g. credit limits, interest rates)
- Cross-selling – appropriately identified customers can be pre-approved for other products that may be of interest to them
How it works
- Application scorecards are statistical models typically developed using an institution’s historical data for the relevant product, if sufficient such data is available.
- If relevant historic data is not available, for example if the scorecard is required for a new product, then Experian can provide representative generic data from their extensive data sources.
- After the data has been extracted and verified it is critical to design a modelling data sample that is representative of the target portfolio and allows the resultant scorecard to meet the business objectives. This is achieved through detailed analysis of the available criteria, portfolio stability and behaviour. The model can then be developed using several methodologies, with linear and logistic regression proving to be the most common. Experian has more than 30 years of experience in successfully developing credit risk models for financial institutions.
- In addition to your data, captured at the point of application, the most predictive application scorecard developments include credit bureau data which provides a detailed view of credit history. In addition to scorecards, Experian can provide extensive retrospective credit bureau data to support application scorecard developments.