Credit recommendations are made at the end of a credit review in one of either two ways:
A credit analyst enters one or more recommendations in the case folder, on the Recommendations page.
See: Making a Recommendation.
The automation rules associated with the case folder's assigned scoring model use the calculated credit score to select one or more recommendations.
Oracle Credit Management provides you with a seeded inventory of credit recommendations, but you can define your own.
Credit Management distinguishes between trade credit and term credit.
Seeded trade credit recommendations include:
Change Periodic Review Cycle
Assign Credit Classification
Assign Overall Credit Limit
Place Customer on Credit Hold
No Change
Change Overall Credit Limit by Percentage
Change Transaction Credit Limit by Percentage
Remove Customer from Credit Hold
Remove Order from Hold
Send Credit Reference
Assign Transaction Credit Limit
Seeded term credit recommendations include:
Approve
Authorize Appeal
Extend
Increase
Reject
Terminate
You define recommendations using user-extensible lookup codes. Define your recommendations for both trade and term credit using these lookup codes:
AR_CMGT_RECOMMENDATIONS (credit recommendations for trade credit)
AR_CMGT_TERM_RECOMMENDATIONS (credit recommendations for term credit)
See: Defining Lookups.
Note: User-defined recommendations are available for business event subscription.
If you are using Oracle Lease Management or Oracle Loans and want to define application-specific recommendations, see: Defining Recommendations for Integrated Applications.
You can add a condition as an attribute of a user-defined recommendation. A condition will launch a new page where the user can document a large set of data points.
To add a condition to a recommendation, you must build a custom page first where condition fulfillment details can be recorded. You then add the new page's OA function to the recommendation's lookup type, in the Tag field.
Suggestion: Use the ability to add an OA function to recommendations to further extend the implementation of credit policies that require more complex information than a set of single data points.
See: Approving a Credit Review with Conditions.
How many values can I associate with a recommendation?
When you define automation rules for a scoring model, you assign one or more recommendations to a credit score range. See: Assigning Automation Rules.
Recommendations can have up to two associated values. For example, for a recommendation of increase credit limit to CAD $800,000, value 1 is currency = CAD and value 2 is 800,000.