Three reconciliations with its own rules
Every month, Singapore Management University's (SMU) Accounts Receivable team needed to ensure that the transactions recorded by its bank, payment platforms and internal financial systems were consistent.
This involved collecting reports from different systems, bringing them together in Excel, checking whether amounts matched, identifying refunds and investigating discrepancies. The team had to reconcile three different sets of financial records, each with its own checks and procedures.
The work was repetitive and required considerable attention to detail. The most complex reconciliation alone took approximately two hours, while the other two took around 30 minutes each. In total, staff spent approximately three hours processing the records before completing their review.
For a finance team, finding discrepancies is only part of the responsibility. Staff also need to understand why those differences exist and determine whether further action is required. Yet much of their time was being spent preparing spreadsheets and carrying out the same comparisons month after month.
Translating those rules into an automated process
To reduce this manual workload, an automation was developed internally at SMU to handle the repetitive parts of the reconciliation process.
Using the team's existing financial reports and Excel workbooks, the automation compared transaction amounts, identified refund entries, applied the required matching rules and highlighted discrepancies for staff to review.
The solution was designed around the university's existing procedures, allowing staff to continue working with familiar reports and retain responsibility for reviewing the results. The automation handled the routine comparisons while the finance team remained responsible for investigating exceptions and making vital decisions.
175 minutes saved each month
The improvement was substantial. Processing time fell from 180 minutes to approximately 3 minutes, with each of the three reconciliations taking around a minute to complete.
Including staff review, the total time required decreased from 200 minutes to 25 minutes, saving approximately 175 minutes per month, an 87.5% reduction in overall effort.
For the finance team, this meant spending far less time working through spreadsheets to identify differences between financial records. With the routine comparisons handled automatically, staff could direct more of their attention towards understanding discrepancies, reviewing unusual transactions and resolving issues that required their judgment.
The records still needed to be accurate, refunds still needed to be accounted for, and discrepancies still needed to be explained. The automation made it possible for the team to get to that work much sooner.
