The aim in credit scoring is to distinguish good clients from bad clients. This is done at the stage of the application (application scoring - AS) based on demographic and similar data. AS is used to decide whether the application is accepted or rejected.

When the credit is being repayed the bahavior of the obligor (did s/he need any reminders, ...) is used to calculate a behavior scoring (BS). The BS can be used to estimate needed reserves for the credit given and for further credit descisions

It is known (and clear) that the discriminatory power of AS deteriorates in the months after the application. Thus it is good practice to combine AS and BS.

What are best practices about when to combine AS and BS and how to do this? I am looking for references and opinions in the context of banking credit risk.

Machine learning like aspects are very important and interesting but I would be happy to have the banking context too. Thanks a lot !

  • $\begingroup$ I am curious why you would want to combine both scores. AS is used to assess thru-the-door customers, on whom the firm has no internal data. Once the customers are booked, the firm will have rich data on the customers and that data is the basis of BS. Any decisions on the existing customers can be just based on BS. $\endgroup$ – nyk Oct 23 '20 at 1:59
  • $\begingroup$ @nyk Yes, after a while the information of AS is too old. In the first couple of months it can be useful to combine them (for a risk class for RWA calculation). $\endgroup$ – Ric Oct 23 '20 at 11:08

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