A credit score is a numerical value based on statistical analysis that represents the creditworthiness of a person or company. With credit scoring, companies try to determine the creditworthiness of customers or partner companies more or less automatically according to a predefined procedure. In a more general sense, scoring refers to the use of a probability value relating to a particular future conduct of a natural person for the purpose of deciding whether to establish, perform or terminate a contractual relationship with that person.
On the basis of borrower characteristics such as “customer since”, “place of residence”, “profession”, “collateral”, points are awarded, these are weighted and then combined into a single credit rating in order to facilitate the granting of loans with this overall score. If the creditworthiness is sufficient, a loan can be granted. However, scores can not only be used to make a credit decision per se, but also to determine interest rates and credit lines.
The motivation is to avoid risks and to obtain objective decisions based on a statistically underpinned method. The better the underlying scoring model reflects reality, the fewer loan defaults there will be. Scoring models and the characteristics that flow into them must be constantly maintained.
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The specific rules and algorithms for awarding and weighting points are called “scorecards”, after the term of the same name from sports. There are various techniques to develop suitable scorecards, such as logistic regression, discriminant analysis, artificial neural networks and other data mining methods. Credit scores can be based on a company’s own data (e.g. personal master data, loan application data) or take into account external data, such as from credit agencies.
Internally determined credit scores do not have to match external ratings, so there may be different probabilities of default. This can be due to a variety of reasons:
- Various inputs
- Various information aggregation methods
- Different rating scales
- Banks produce internal “point-in-time” ratings, i.e. a default forecast for one year after the assessment date, while external ratings are based on a “through the cycle” approach, i.e. a default forecast over the economic cycle.
Credit scoring is used as a statistical procedure by credit institutions to carry out a risk classification for private standardized installment loans and small loans. Such loans are usually granted unsecured and are based solely on the personal creditworthiness of the borrower(s).
When processing installment loans, a quick credit decision is sought, whereby the detailed financial situation of the borrower can only be clarified to a limited extent.
