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ERP Glossary

Bank Reconciliation

Bank reconciliation is the process of comparing a company's internal financial records against the bank statement to identify and resolve discrepancies. It ensures that the cash balance in the accounting system matches the actual cash held at the bank.

Understanding Bank Reconciliation

Bank reconciliation is one of those tasks that sounds straightforward but can become surprisingly complex. The core concept is simple: compare what your books say your bank balance should be with what the bank actually reports, and explain every difference. Differences arise for legitimate reasons. Checks you have written may not have cleared yet (outstanding checks). Deposits you made on the last day of the month may not appear on the statement until the next day (deposits in transit). The bank may have charged fees or earned interest that you have not recorded yet. And sometimes there are genuine errors on either side. The reconciliation process typically starts with the ending balance on the bank statement and adjusts it for outstanding items to arrive at the "adjusted bank balance." Separately, you take your book balance and adjust it for items on the bank statement that you have not recorded. If both adjusted balances match, the reconciliation is complete. For businesses with high transaction volumes, manual reconciliation is impractical. A company processing thousands of transactions per month needs automated matching that compares bank transactions against recorded entries by amount, date, and reference number. Machine learning improves this over time by learning patterns: if a certain bank description always corresponds to a certain vendor payment, the system can match them automatically. Regular bank reconciliation is not just good practice; it is a critical internal control that catches fraud, prevents overdrafts, and ensures financial statements are accurate.

How Yukti Handles This

Yukti connects directly to banks via secure feeds and uses AI-powered matching to automatically reconcile transactions. The system learns your patterns over time, reducing manual matching to only the truly ambiguous items and completing most reconciliations in minutes rather than hours.

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