How data analytics make a credit union’s internal audits more efficient

Credit unions and financial institutions continue to evolve out of necessity, responding to year-round disruption, emerging competitors, changing business models, and new technology. This fast-paced change affects business operations at all levels, with members demanding real-time interactions, regulators across the country applying increasing levels of scrutiny, and boards of directors requiring increased assurance in this dynamic risk environment.

Consequently, internal audit functions with the strongest impact in their organizations are those that are adapting to change, promoting cross-functional collaboration, and making investments in digital assets, analytics, and automation.

New technologies have enabled a variety of techniques to improve efficiency and insight from audit activities, including 100 percent assurance coverage (rather than sampling), automation of tasks, and real-time insight into emerging risks via data-led, continuous monitoring. This creates an opportunity for internal audit to continuously evolve its future role.

How internal auditors in the credit union space are using data analytics

An internal audit is typically initiated for one of the following reasons:

• It is mandated by compliance regulations.
• It is part of a credit union's standard operating procedure.
• A business problem or risk has been discovered that requires a solution.
• There is a business opportunity that requires a strategy.
• A new technology has been recommended that requires system optimization.

Leveraging the power of data analytics can reduce the effort required to perform internal audits and yield more robust information to make better-informed decisions. More than that, a well-planned data analytics strategy for internal auditing purposes can save valuable time by allowing you to find anomalies quicker, change direction earlier, and get back on track sooner.

Analyze more information in less time

Before data analytics, internal auditors had to manually review samples and from those, extrapolate hypotheses. This method, although effective, limited the conclusions that could be drawn from the audits performed. The use of sampling was a necessary compromise, to save time and money—until now.

Credit unions with data analytic capabilities can now review relevant information in seconds and generate on-demand reports that highlight any aspect of the data in an order that makes sense. This saves time and reduces the efforts required to prepare for and perform an audit.

Find anomalies before they become major difficulties

With a complete picture from all the data, internal auditors at credit unions can identify questionable transactions that may not have otherwise been analyzed or may not have been considered part of a pattern or trend because similar/related transactions were not assessed.

With the ability to instantly interpret data, credit unions supported by data analytics can use what they collect to get answers more quickly, even if the question was not the one originally asked.

Make more confident recommendations

The results of a quality internal audit almost always include at least one recommendation that needs management buy-in and could also require audit committee or even business unit buy-in. But there will be no consensus if the parties that need to approve the improvements don't have complete confidence in the suggestions being offered.

Data analytics goes a long way to solidifying confidence.

First, the internal audit function can say, with certainty, that all the applicable data has been reviewed and can produce documentation to support their assertions.

Second, the internal audit function does not need to rely solely on intuition and experience. The recommendations put forth are more informed and backed by solid, irrefutable data.

Third, and possibly most important, the internal audit function can also look for positives within the data, which can balance the tough realities that an internal audit might yield. This can make hard news easier to accept and make its receivers more inclined and motivated to address issues head on—which would be the most desirable outcome of an investment in an internal audit.

Clear a wider path towards ROI

Credit unions using data analytics are spending less money on the deep data dives required to perform a comprehensive internal audit. They are using fewer human resources to complete an internal audit, freeing team members up to contribute to other growth-related and solutions-driven conversations. They are also providing enhanced recommendations because they have all the essential data needed to make informed decisions. This can help place the credit union in a better financial, operational, technological, and strategic position than it was before.

How can data analytics benefit your credit union's internal audit?

Credit unions are at a crucial juncture after COVID-19. It's more important than ever to find new strategies for growth and innovation in order to stay competitive. Applying data analytics to internal audits can offer the following benefits:

• Brings previously invisible trends and patterns into plain sight.
• Dives deep into results and provides insights on credit risk and lending activity trends, liquidity management, branch performance, and other factors analyzed.
• Compares questionable transactions to similar transactions so they can be considered with all relevant context. Human errors can be spotted and corrected faster.
• Completes internal audits in less time spent, for less money and with more accurate recommendations.

BDO can help

At BDO, we understand the responsibilities you have to your members, as well as the regulatory requirements mandated by the industry. While implementing a data analytics strategy may seem like a daunting task, our team can provide an end-to-end solution that includes:

• Developing and implementing a customized data analytics strategy.
• Enhancing your credit union's existing internal audit capabilities or establishing a robust internal audit function that is complemented by data analytics.
• Helping you to improve your credit union's internal capabilities, tools, and overall operational efficiency.