Summarizing the SAP Cash Reconciliation Functionality​

In accounts receivable accounting, financial apps automatically match most incoming bank statements with open receivables based on defined rules and leave unmatched bank statements for manual post-processing. With machine learning, a model is trained with data from past manual actions to learn from it and applies this information to new data to achieve a higher rate of automatic clearing.

Essentially, SAP Cash Application is a cloud-based software solution that leverages machine learning and automation to streamline the accounts receivable process. It automatically captures and extracts payment information from various sources, like emails and scanned documents, eliminating manual data entry and reducing errors.

To perform these tasks, SAP Cash Application passes incoming payment and open invoice information from SAP S/4HANA Cloud to a matching engine, based on SAP Business Technology Platform. This integration helps to ensure lower total cost of ownership with improved efficiencies, reduced days sales outstanding and a single, integrated environment with SAP S/4HANA Cloud.

Additionally, SAP Cash Application includes Payables Line-Item Matching, which matches outgoing payments to supplier invoices. These payments are often manual due to insufficient information on bank statements. Machine learning proposes matching supplier invoices for these payments, allowing for automatic clearing based on configured thresholds. The workflow for Payables Line-Item Matching is similar to that of Receivables Line-Item Matching.

The Receivables Line-Item Matching machine learning service of SAP Cash Application provides proposals for matching receivables with incoming bank statement items and according to the confidence level and clearing-threshold automatically clears them.

The Receivables Line-Item Matching machine learning service consists of two tasks:

1. Schedule Jobs
2. Reprocess Bank Statement Items

Let's start with the Schedule Jobs task. There are some technical prerequisites that you must consider when scheduling jobs for the Receivables Line-Item Matching machine learning service. Check the details here:

The Scheduling Jobs task has two sub-steps. To successfully complete the Receivables Line-Item Matching machine learning service, you must schedule the following templates within the SAP Fiori app Schedule Accounts Receivable Jobs:

• Cash Application: Open Item Upload
• Automatic Bank Statement Processing

This Accounts Receivable job is required to provide the current open items in your system for SAP Cash Application so that a possible match can be generated. When you select SAP Cash Application: Open Item Upload template, you can schedule accounts receivable jobs to receive machine learning proposals to match open receivables to incoming bank statement items, and to automatically clear them.

For the template itself, you must specify the scheduling information either to be performed immediately or you define a recurrence pattern. Patterns could be set up, for example, on an hourly basis. Several different options are available.

In the last step of the Scheduling Template, you define parameters, like document numbers or company codes to refine your job. Once you schedule your new SAP Cash Application: Open Item Upload job, it will be executed in the background as per the definition.

The second item to be taken care of in the Schedule Accounts Receivable Jobs app is based on the Cash Application: Automatic Bank Statement Reprocessing job template.

The latter job selects bank statement items that could not be processed with posting or processing rules before and tries to analyze them. After the job analyzed them, the resulting proposals of open items and accounts are displayed for each item in the Reprocess Bank Statement Items app. Depending on how you've defined the target accuracy in your configuration settings and if you've selected the Automatic Posting / Clearing checkbox, the resulting proposals can also be used to automatically process the remaining bank statement items.

The Target Auto-Clear Accuracy defines the threshold confidence level that allows the SAP Cash Application to automatically post items. In the example above the target is set to 100% which means the system is only allowed to automatically post items if it is absolutely sure that the two items are a match.

The Target Accuracy for Proposal describes the confidence level above which the SAP Cash Application shows a proposal of two items in the Bank Statement Reprocessing app.

Watch this video to learn more about scheduling options and parameters, and also how the results are displayed in the Reprocess Bank Statement Items SAP Fiori app.

As shown in the video, you can check the processing status of the bank statements in the SAP Fiori App Reprocess Bank Statement Items. You can filter or sort according to the SAP Cash Application status. From here, you can decide and process the items further until clearing is performed.