Retail Credit Scorecard
Contents
Definition
A Retail Credit Scorecard is a type of Credit Scorecard used in the classification (scoring) of Credit Risk for Consumer Credit. The scorecard output is an assessment of the relative likelihood of a certain Credit Event occurring, given a number of observable inputs
Retail Scorecard Types
By usage
Retail Credit scorecards may be used for a number of distinct activities
- Approval of new credit (acceptance scorecards)
- Assessment of ongoing credit risk profile ( behavioural scorecards, internal Credit Rating System)
- Input for the calculation of regulatory capital (Basel II scorecards) for regulated financial institutions
- Input for the calculation of IFRS9 / CECL Expected Credit Loss and Loss Allowance for institutions reporting under these standards
By type of output
A scorecard might produce as output a Credit Score or an actual estimated Probability of Default
By nature of development
Generally speaking, retail credit scorecards are quantitative (statistical) scorecards (Credit Scoring Models) that use exclusively or primarily quantitative inputs and algorithmic processing (Machine Learning) to achieve the risk classification. This is enabled by the generally large size of retail credit portfolios and the relative simplicity of retail credit products
By algorithm
Quantitative scorecards employ one of several possible algorithmic classes (For complete list see Credit Scoring Models), e.g. linear discriminant analysis, logistic regression, decision trees etc.
Retail Scorecard Development
Development of credit scorecards is highly dependent on context. An overview is given in the How to Build a Credit Scorecard entry.
Issues and Challenges
- Like with any statistical model, the predictive performance of scoring models exhibits Model Decay, as both the borrower's own characteristics may change and the external business and economic conditions evolve
- The data eligible for use in the development of credit scorecards are generally regulated under Fair Lending laws
