- SAP Managed Tags
Challenges with the Clearing of Incoming Payments
SAP Billing and Revenue Management (BRIM) is designed to efficiently handle high transactional volumes through process automation. While configuring business rules enables full automation in most areas, such as billing, invoicing, and collections, many companies still struggle with effective payment allocation. This challenge often arises when relying on arbitrary free text remittance information commonly used in bank transfer payments.
FI-CA Clearing Control is effective only to a certain extent and is highly depended on the discipline of customers in providing accurate remittance information. Although system allows for the configuration of complex and flexible allocation rules through standard configuration and custom code enhancements, predefined business rules cannot address scenarios where a customer does not follow the prescribed remittance format (e.g. omitting an account number or invoice number) or provides incomplete payment details. As a result, such incoming payments end up in the clarification worklist.
Manual clarification is often time consuming , requiring significant effort, as unresolved clarification cases continue to accumulate. This leads to large amounts of cash being booked in suspense accounts for extended periods, negatively impacting key financial metrics such as available cash flow.
SAP Cash Application
The AI capabilities embedded in the SAP Cash Application Add-on for Contract Accounting reduce the need for manual intervention and enable the assignment of incoming payments as quickly as possible. Running on the SAP Business Technology Platform, the SAP Cash Application leverages Machine Learning (ML) model to analyse data transferred from the S/4HANA system, identifying selection categories and selection values for FI-CA Clearing Control.
The ML model is trained before productive use, learning from historical clearing information. This learning process continues permanently in the production environment, automatically adapting to changing conditions to keep the model up to date. The key advantage of the ML model is its ability to automatically detect data patterns, while its dynamic learning process ensures long-term effectiveness without requiring additional maintenance effort.
Key Configuration in Contract Accounting (FI-CA)
- Activate Cash Application for the Company Code
SPRO -> Organizational Units → Set Up Company Codes for Contract Accounts Receivable and Payable
- Define Conditions for Using the ML Proposal Based on the Confidence Level Rating
SPRO -> Business Transactions → Payments → Processing Incoming and Outgoing Payments → Incoming Payment Clarification with Machine Learning → Make Settings for SAP Cash Application for Contract Accounting
The configuration determines how the clarification case will be processed in FI-CA based on the confidence rating returned to S/4HANA from the Cash Application. The configuration allows different follow-up processes to be set up:
- A clearing document will be generated for a matching proposal above the auto-clearing accuracy threshold.
- Matching proposals under the auto-clearing threshold are shown and displayed for validation.
- Proposals below the minimum threshold are skipped and not displayed at all.
In this instance (as per the configuration), the payment will be automatically cleared only if the confidence level is very high (greater than 95%). If the confidence level is between 80% and 95%, the system displays the proposal and requires manual post-processing. Below 80%, the system ignores the proposal completely.
Use Case – Payment Clarification with Cash Application
Let’s demonstrate the capabilities of Cash Application for Contract Accouting with a simple use case (note: the screenshots are taken from SAP S/4HANA Cloud Public Edition).
In this scenario, a payer has two ongoing service subscription contracts and is paying both invoices at once. The provided note to payee information is: “Payment for Feb 25 subscriptions West Corp” This presents the following challenges for payment allocation:
- No invoice reference number or account number is provided.
- The payer name (“West Corp”) may or may not match a Business Partner (BP) ID in the system.
Payment lots are created from the electronic bank statements, and the remittance information provided with the payment will be captured in the note to payee segment of the lot. However, the predefined interpretation rules and configured clearing rules will fail to translate the remittance information into selection categories and values, resulting in the creation of a clarification case.
In a system with the Cash Application Add-on activated, manual processing of clarification cases is blocked until the machine learning (ML) analysis is complete. The system will raise an error message if the user attempts to process the clarification case before the data are sent for analysis.
Next, the clarification case is sent to Cash Application for analysis. This is done through job scheduling using the job template “FI-CA: Transfer Clarification Cases”. In a productive environment, this job should be scheduled immediately after the creation and posting of payment lots to FI-CA.
The ML model applies the logic to find a suitable matching proposal, which is then returned to the S/4HANA system. This process is also done through job scheduling, using the job template “FI-CA: Process Returned and Reversed Clarification Cases”.
The ML model provides matching criteria with a confidence level for each clarification case. Proposals with a confidence level meeting the minimum auto-clearing threshold will trigger the posting of FI-CA document.
Availability
As of now, the Add-On is available for SAP S/4HANA BRIM, SAP S/4HANA Cloud Public Edition for Contract Accounting, and other industry-specific FI-CA variants, including PSCD for Public Services, FS-CD for Insurance Companies, and IS-U for the Utilities sector.
Further SAP Help references
Cash Application integration for Contract Accounting for Cloud
SAP Cash Application for Contract Accounting: Product information
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