This chapter provides an overview of Oracle Credit Management.
This chapter covers the following topics:
Oracle Credit Management provides a global, standardized system that lets you make and implement credit decisions based on the collected credit data of your business-to-business customers and prospects. Credit reviews are automated by the Credit Management workflow process.
Automated periodic credit assessments include all activities from the initial credit review request and creation of the credit application, to credit scoring and analysis, to the final implementation of credit decisions.
Why is this useful? First, an automated credit review process employs standard guidelines that you define, for a consistent approach to credit decisions across your entire credit department.
Additionally, an automated process that continuously evaluates and manages less risky credit decisions leaves your credit personnel free to concentrate their efforts on higher risk credit assessments. For example, your skilled credit analysts can focus on selected customer portfolios, such as those customers driving revenue or licenses above a threshold of $250,000, as well as on credit reviews that fail the automation process.
Credit Management facilitates these manual credit reviews through features such as online case folders, easily generated what-if scenarios, and integration with Dun & Bradstreet.
As a result, you can increase the scope of your customers' portfolios without increasing your credit personnel overhead. And, because all credit reviews are administered according to your own established credit policies, your business can continue to grow without compromising your own overall portfolio risk and financial stability.
Oracle Credit Management integrates with other Oracle applications, so that business events across the E-Business Suite can initiate a request for a credit review. For example:
An order entry clerk places an order in Oracle Order Management that causes a customer to exceed its current credit limit.
A sales representative or leasing agent enters a new lease application in Oracle Lease and Finance Management for a customer.
Six months have passed since a customer's last credit review date, automatically initiating a periodic credit review.
A credit analyst manually enters a new credit application for a prospect.
Once initiated, a credit review can either be completely automated, or managed by a skilled credit analyst. You control how credit reviews happen when defining your credit policies.
Oracle Credit Management's business solution is comprised of these main process flows:
Credit policy management
Completion of the credit application
Credit analysis and implementation of decisions
Risk and revenue management
Before credit analysis can begin, you must define your credit policies. In Credit Management, you model your credit policies around the intersection of two user-defined dimensions: the credit review type and the customer credit classification:
The credit review type refers to the type of credit reviews that you perform at your enterprise, such as Credit Checking, Periodic Credit Review, or Lease Application.
The customer credit classification refers to the credit relationships that you have with your customers and prospects, such as High Risk or Low Risk.
For each credit review type and credit classification combination, you assign a set of credit review tools that will vary according to your requirements. Credit review tools include:
Credit checklists
Credit checklists specify which data points are required or optional during a credit review. Examples of data points are Days Sales Outstanding and Percentages Of Invoices Paid Late. When defining checklists, choose from a universe of almost 200 data points, or define your own.
See: Defining Checklists.
Scoring models
Scoring models include the data points and scoring method that are appropriate for a particular credit review. When defining scoring models, for each data point, (1) indicate a score for each range of values and (2) optionally assign a relative weighting factor.
For example, will you use this scoring model to determine a credit limit increase for an existing customer who has years of credit history with your enterprise? In that case, you might assign a higher weighting factor to the Percentages Of Invoices Paid Late data point, and a lower weighting factor to the Credit Agency Score data point.
See: Defining Scoring Models.
Automation rules
Automation rules guide the implementation of credit recommendations without user intervention. Optionally define automation rules and assign them to a scoring model. If a score is above a certain threshold, for example, you might want Credit Management to automatically approve and implement a higher credit limit, or release an order hold.
During setup, you model your credit policies by assigning the appropriate credit review tool to each combination of credit review type and credit classification.
For example, for the combination of Increase Credit Limit credit review type and High Risk customer credit classification, your credit policies might dictate a conservative approach. In this scenario, you would use a conservative policy (scoring model) to determine whether to grant additional credit and what the credit limit should be.
Credit Management provides a modular, online credit application, which can either be manually completed by a credit analyst or automatically populated by business events.
See: Using Credit Applications to Collect Credit Data.
In Credit Management, credit analysis can proceed with the partial or full participation of credit personnel. Using an online case folder, the credit analyst has all the information needed to make informed credit decisions.
More typically, credit analysis will proceed automatically. Credit recommendations can be implemented without user intervention through the use of automation rules, Oracle Workflow, and Oracle Approvals Management.
For example, at the conclusion of a credit review, Credit Management can automatically implement these recommendations:
Establish a new credit limit
Revise an existing credit limit
Remove an order hold
Put a customer account on hold
Put a customer party on hold
If an automated credit review fails at any point during the process, the workflow will stop and the credit review will be routed for assignment to a credit analyst for manual processing. See: How Automation Works.
Are your current enterprise credit policies effective? Credit Management provides the tools to help you analyze the results of past credit reviews, so that you can manage your assumed credit risk on an ongoing basis. Such analysis can help you to decide if existing credit policies require adjustment, or if you are right on track. See: Reviewing Credit Management Performance.
You can also manage risk from a receivables perspective, in terms of revenue recognition timing. Credit Management integrates with another E-Business Suite application, Oracle Receivables, to provide automation around revenue management.
Depending on your Receivables setup, you can manage revenue recognition based upon the customer credit classification assigned by a Credit Management credit review. For example, if a customer has a High Risk credit classification, you can defer revenue recognition on that customer's orders until payment is received. This helps you to comply with stringent revenue management requirements.
Note: Setup around revenue management is completed in Receivables, not in Credit Management.
See: Defining Your Revenue Policy, Oracle Receivables Implementation Guide.
Credit Management uses automation rules, Oracle Workflow, and Oracle Approvals Management to automate the credit review process.
If the automated review process fails, then the credit review is routed to the Credit Scheduler role. A manager logs into the Credit Scheduler responsibility to review and re-route credit reviews to the appropriate credit analyst for manual processing.