Reconciliation Of Bank Statement with SAP

A lot of businesses use SAP to record all the transactions done to and from the business. A single source of information is made available for many business operations by SAP software, which centralizes data management. This enables businesses to quickly manage complicated business processes, provide employees from many departments with easy access, and receive real-time insights throughout the entire organization. As the entries are done by various users sometimes there can be issues or errors in the records. At times there are discrepancies between the data records in SAP and the data that is in the bank statements. Sometimes there are missing payments or receivables and sometimes errors. This can lead to a lot of disputes and losses for a business. Thus, verification of this data is necessary. This important process is very time-consuming and difficult to do as the quantity of the data is very vast. This process is made easy by Cointab. Cointab has made an automated reconciliation system which makes Bank Reconciliation Statement for SAP easy. In the system, the data can be uploaded automatically, which greatly reduces the time consumption. After this, the system provides systematic results which are easy to read and analyze. All the business needs to do is read this output and take necessary actions.

This Reconciliation process is explained as follows:
The Reports needed for Reconciliation are:
  • SAP Ledger Report
  • Bank Statement
Data Loading:
  • Data can be loaded via email attachments, SFTP, and APIs.
  • Bank statements in CSV/Excel formats are sent by banks to the Client. They in turn automatically forward the emails to the Cointab reconciliation system.
  • SAP data in CSV/Excel format is sent by email to the Cointab reconciliation system for processing.
Reconciliation Process:
  • For reconciliation, the system extracts Transaction ids such as UTR, App ID, Dealer Code, etc. from the raw bank and SAP data.
  • A pivot is made on both Bank and SAP data based on the extracted Transaction ID.
  • Amount is then summarized at Transaction ID level (for bank & SAP separately).
  • The Mapping is made between bank & SAP data based on the Transaction ID.
  • Once the mapping is established, bank & SAP amounts are compared.
  • The comparison is executed in both forward and backward ways – Bank to SAP and SAP to Bank.
  • Based on the output, the system summarizes the result and shows it on the Cointab dashboard, and sends it by email in an Excel file.
Output – Bank to SAP reconciliation result
The result displays:

Total Transactions:

The total number of transactions in the Bank Statement.

Reconciled with SAP:

This shows the transactions where the Transaction amount matches the amount in SAP.

Less Amount Recorded in SAP:

When the bank amount is higher than the SAP amount in the bank transactions.

More Amount Recorded in SAP:

All bank transactions where the bank amount is less than the SAP amount.

Not Found in SAP:

This line item records the bank transactions that are not recorded in SAP.

Output – SAP to Bank reconciliation result
The Result Displays:

Total Transactions:

All the transactions in the SAP Report

Reconciled with Bank

The SAP transactions are recorded here, where the transaction amount matches the amount in the bank.

Less Amount Recorded in SAP

This shows SAP transactions where the bank amount is higher than the SAP amount.

More Amount Recorded in SAP

SAP transactions where the bank amount is less than the SAP amount are recorded here.

Not Found in Bank

This line-item records SAP transactions that are not recorded in the bank.

Cointab’s system does Bank Reconciliation Statement with SAP easily. As seen in the above results, the process is done in a precise manner which makes the results appear very easy to read and accurate. The system automates the data upload which saves a great amount of time in gathering the data. Cleaning and extracting the data are also made simpler and a merchant can save a lot of time on these. Use Cointab now and easily analyze data and save money and time.

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