Reconciliation is a complex banking aspect that can benefit immensely from automation and software-based solutions.
FREMONT, CA: Reconciliation is an important step in banking that ensures the accuracy of a bank’s financial data. While reconciling bank statements, it is essential to carefully match transactions in the accounting records to the transactions on the bank statement. Conventionally, reconciliation tasks were carried out by human auditors. The process was both tedious and involved the possibility of human errors. However, with the advancement of technology, reconciliation is being automated.
While hundreds of transactions can be good for business, it can be difficult for humans to match the balance in the accounting ledger with that in the bank account. Fortunately, accounting software has come to the rescue of the banking sector. Accounting software can fetch bank transactions, organize them as per the custom rules, and reconcile them in groups. Thus, accounting software can save significant time and effort for the banks.
Data aggregators can help the banks by pulling a list of transactions eliminating duplicate entries and adding them to the accounting software. The transactions can be seen with the amount, date description, and the information of the payee and the payer. Transaction filters can be used to filter and categorize transactions automatically based on desired transaction categorizations or groups.
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Cloud accounting software offers an even better alternative to reconciliation efforts than the desktop accounting application. Artificial intelligence (AI)-powered cloud accounting software is much more intuitive than the system accounting applications. AI can track an uncategorized transaction from the bank repositories and recommend an existing category within a bank’s accounting application. Such suggestions enable identifying and reconciling transactions simple and less expensive for the banks. Reconciliation software promotes automation in banking. Software-driven consolidation and categorization of mass data set significantly reduce efforts as well as the possibility of errors.
With growing complexities and a significant rise in the number of online transactions, a software-based solution will certainly help the banking sector to record and categorize transaction history accurately.
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