The growing complexity and capacity of business’ systems are making it difficult for investigators to understand, follow, and detect fraud. As data grows exponentially and spreads outside the organization, it is becoming increasingly difficult to make connections and identify anomalies or patterns across these disparate data sets. To add fuel to the fire, this explosion of data is resulting in the spread of cybercrime – as more data means more opportunities to commit fraud.

To keep pace in today’s increasingly complicated risk management landscape, investigators must move beyond traditional methods and begin leveraging the latest technology to more quickly and accurately detect and prevent fraud.

The Emergence of Fraud Analytics

While the idea of leveraging data analytics to improve decision-making and operational efficiencies is a relatively mainstream idea, it is only in the past few years that we have seen this type of advanced technology really become mainstream in practice, especially for smaller to midsize businesses who don’t have the bottomless budget and resources of larger corporations.

Thanks to the advent of cloud computing, companies of all sizes now have access to a vast amount of data which, if analyzed correctly, can offer insights that were previously inaccessible. However, this data is only meaningful if it can be mined and explored further for meaningful information.

This is where fraud analytics comes into play. By utilizing advanced analytics technologies, including artificial intelligence (AI), machine learning, and predictive modeling, investigators can gather and analyze trillions of data points across the globe. Through automation, teams can quickly and efficiently understand and respond to critical inquiries or allegations – greatly reducing or even preventing the economic and reputational repercussions of fraud.

Let’s take a deeper look at some of the ways fraud analytics is transforming how investigations are performed.

Spend more time consuming the data; less time gathering it

The use of automation is one of the most significant ways fraud analytics is enhancing investigations. Through artificial intelligence and machine learning, systems can automatically transfer and compile a company’s financial information, allowing investigators to move beyond sample testing and instead explore the large majority of a company’s transactions. This not only decreases the likelihood of overlooking a critical issue, but it also opens up more space for investigators to focus their efforts on more value-added tasks.

To demonstrate the value of fraud analytics, let's take a closer look at an example of how fraud analytics helped one particular franchisor of pizza chains gain visibility into the full data sets (not just samples) to identify high-risk items. This particular franchisor suspected manipulation of Point of Sale (POS) systems aimed to decrease revenue and royalty payments, thereby increasing franchisee’s individual profits. After completing an investigation, the team was able to determine the total number of deleted sales transactions, which exceeded 100,000, and calculate the value of the missing orders. In addition, the team discovered how the culpable franchisees were committing the fraud: an unauthorized back door had been coded into the POS system, enabling the franchisees to access the system and delete orders. As a result of this analysis, the franchisor was able to recover over $1 million in unpaid royalties and address the vulnerability in the POS system to prevent any fraudulent behavior in the future.

Identify and improve data inefficiencies

In today’s data-driven world, embracing analytics is crucial to keeping your organization nimble, competitive, and profitable. With greater awareness and deeper insights through fraud analytics, it’s not uncommon to surface other issues and operational inefficiencies that would have otherwise gone unchecked for months, years, or even indefinitely.

For example, when conducting a fraud analytics review, you may come across an instance where your organization has been making duplicate payments to a vendor. While this oversight may not be absolute fraud, it brings other operational inefficiencies to the surface that, when corrected, can have a significant impact on your organization’s profits.

The Bottom Line

The increased use of automation and artificial intelligence in investigations is enabling us to securely analyze massive amounts of data with unprecedented speed and accuracy. With advancements in cloud technology, these types of fraud analytics techniques are now within reach of organizations of all sizes. So, while most internal audit departments are too overwhelmed to develop fraud analytics in-house, service providers have emerged who understand the needs of midsize companies and can help fill the gap and guide organizations through their fraud analytics journey.

Learn more about how BDO applies extensive forensic expertise, adaptive cloud architectures, and highly advance analytics dashboards to deliver proactive protection that greatly reduces and even prevents the economic and reputational repercussions of fraud.

Kirstie Tiernan is a managing director in BDO’s Technology & Business Transformation Services practice with more than 15 years of experience providing data analysis, information technology (IT) advisory, digital forensics, and e-discovery services.