Higher education institutions have an enormous amount of data, which, if left unanalyzed, could result in a missed opportunity to catch errors or fraud.
Higher education institutions have vast amounts of data; however, it isn’t all being used to its full potential. From endowment data and donor databases to journal entries and tuition and fee revenue, there is plenty of data to work with.
Data analytics could help you harness this information to identify trends and anomalies. So instead of looking at a balance in a point-in-time or in a sum, you can view figures in a new, more targeted context.
- Your auditor might use it to identify trends in revenue fluctuation or tuition and fee variances.
- Your investment committee could use it to track how returns on your endowment compare to the market, and make adjustments to investment allocations accordingly.
- And your internal finance department could use it to uncover patterns and irregularities due to error or potential fraud.
Ultimately, data analytics help you gain a more holistic understanding of your institution’s operations.
Data analytics, audits, and the general ledger
When choosing an auditor for your institution, consider how data analytics could enhance the quality of the audit. By moving away from the traditional method of sampling sets of data, the auditor can instead analyze whole sets. This gives you a better understanding of your institution’s overall picture, and opens the door for much deeper conversations.
For example, if the auditor examined your institution’s monthly revenue for a fiscal year and discovered that the highest amount of tuition and fee revenues were recorded in September, January, and February, you will want to probe further. The higher revenue in September and January makes sense since fall and spring semesters begin during those months, but what about February? Conversations founded in these kinds of discoveries provide meaningful insight that can help both parties uncover anomalies and non-routine transactions.
General Ledger
Moreover, your auditor could use data analytics during a review of all general ledger transactions within a fiscal year. This process allows the auditor to identify which accounts receive the most transactions, which accounts have a significant balance but receive a relatively low number of transactions, and if there are any transactions to new accounts. Once the general ledger activity has been identified, the auditor can explore results that aren’t congruent with expectations.
For example, your institution would expect to have a large volume of transactions in cash and accounts payable accounts and a lower volume in investment and fixed asset accounts. Any unusual activity in accounts that are often inactive should become apparent during the audit process. This added insight helps you to make corrections and plan for future audits.
Unearth fraud and discover trends
Data analytics could also be used by your institution’s internal finance department. While there are several different ways to transform the way your finance department operates, incorporating data analytics could help the department review the following data sets in a new light.
Cash and payroll disbursement listing
Review full cash disbursement listings to see which vendors you used, and what payments were made during that fiscal year. You could also summarize the cash disbursement listing by vendor to identify the amount paid and the volume of transactions — you’re more likely to uncover unusual activity during this review. For example, 13 monthly payments to a landlord within one year could reveal an unexpected top vendor, calling for additional research.
Payroll transactions
During the process of reviewing all payroll transactions within a fiscal year, use data analytics to identify any non-standard payroll payments, such as bonuses, loans, draws, or reimbursements.
Donor database
Your institution most likely relies on the generosity of your donors for the viability of its future. Although there is often some uncertainty about how many donations you’ll receive from year-to-year, you can rely on the data in your donor database to help you understand what you’ve received historically. Your advancement office and finance department should review and analyze donor data annually, including how many donors you’ve had in the past five years, how often they donate, and how much they give. This ensures you have the right expectations each year.
How we can help
CLA has made it a priority to harness the power of data analytics. As a part of our holistic approach to serving the higher education industry, we use data analytics in every one of our audits. We believe that by doing this, we are setting our clients up for success.
Our seasoned professionals can help you understand how data analytics can be used as part of your financial modeling to provide you with insight into your institution’s operations.