A quick introduction to scorecards

Some may ask what the relationship of scorecards to Business rules is…

Well it turns out that IBM has created an add on to add support for scorecards in JRules and that before I go on and do my review I decided it was necessary to write a post on what a scorecard is so that I don’t have to do it as part of my upcoming review… 🙂

What is a scorecard?

For those of you who don’t know what a scorecard is, it is a Risk Management tool used mostly by banks and other institutions to calculate the risk they take by selling you one of their products.

  • How risky a customer are you?
  • What are the chances that you might default on payment?
  • etc.

Based on that information, they may adapt their specific offer. For example, a good customer might get a better interest rate, a higher credit limit, etc.

It works like this (more or less):

  1. The company performs a statistical analysis on historical data that they have on all their existing customers
    • They may break the data down into smaller groups that have something in common (called segmentation) so that the resulting analysis is more precise
  2. From this analysis, they will identify characteristics (attributes or pieces of information) that are “predictive”
    • That is, the characteristics show a statistically significant relationship to past results (positive or negative)
  3. Each characteristic is then broken down into ranges of possible values
    • For example, a characteristic based on family income may be broken down into ranges as follows:
      • 1-30000
      • 30001-60000
      • 60001-90000
      • 90001-120000
      • over 120000
  4. Each range is then given a score and the attribute is also usually assigned an expected score. For example
  5. Characteristic Expected Score Range Score
    Family income 50 1-30000 10
    30001-60000 25
    60001-90000 40
    90001-120000 65
    over 120000 75
  6. This is repeated for many characteristics and combined together into a single scorecard.
  7. In addition to a score for each range, a reason code may be attached to a specific range value to provide some indication as to which attribute may have scored low (i.e. lower than the expected score).

In the end, when executing a scorecard the result will be a score calculated based on all the indivdual scores of each attribute and a list of reason codes (usually the codes associated to the attributes that score the most negative, if applicable).

This score can then be used as part of another calculation to calculate a risk rating, credit limit, interest rate, etc.

That is about it! Now you have a basic understanding of what a scorecard is. In the near future, I will post my review of the Scorecard Modeler add on for JRules.

In the meantime, if you have questions about scorecards or the post needs clarifications, feel free to comment and drop me a line!

One thought on “A quick introduction to scorecards

  1. Hi Eric,
    Thanks for your fantastic intro to scorecards. Please do you have an idea of a modelling for calculating the historical characteristics? Would you suggest regression method can be used initially to identify significant variables? Can you pls send me samples of what you have done, if any.


Leave a Reply

Your email address will not be published. Required fields are marked *