Implementing a loan decision policy

Scenario: This demonstration knowledge base implements a hypothetical bank's loan policy to illustrate the application of expert systems as performance support tools. It embellishes a knowledge decomposition example used in the IBM Building Expert Systems Workshop presented during the late 1980's.

The recommended minimum confidence factor (CF) used to accept an input or derived value as a fact is shown below. Setting the CF to a lower value may produce more results (with less confidence in these results):
Minimum CF:50% 60% 70% 80% 90% 100%

If you allow "cookies" to be accepted by your Web browser, you may use the Save all button on the Why ask? screen at any time during a session to store all of the answers you have submitted up to that point. To reload the answers most recently saved (if there are any), start your interview with the following button:

When you restart an interview, the minimum confidence factor will be reset to the value it had when you saved your input.

Technical note: This is an eXpertise2Go demonstration expert system using XML output produced by e2gDotNet, the port to Microsoft's .Net and C# technology of the original Java-based eXpertise2Go inference engine.

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