Fraud is a growing problem in every industry, but can be much more impactful within financial services and enterprise businesses. When an organization is the victim of fraud, the company not only has to deal with what amounts to stolen financial resources, but what may also be damage to its reputation.

According to the 2015/16 Global Fraud Report from Kroll, more organizations inside and outside of financial services are dealing with fraud. Researchers discovered that, overall, 75 percent of businesses have experienced fraudulent activity within a 12-month period, representing a 14 percent increased compared to 2013.

Why fraud is such a pressing issue

"Analytics can help identify the hallmarks of fraudulent activity."

One of the most important issues at play here is that there are so many challenges involved when organizations seek to root out and address fraud. As McKinsey authors Jacomo Corbo, Carlo Giovine and Chris Wigley pointed out, it is difficult to pinpoint and deal with fraud due to the significant number of daily transactions, the speedy actions of fraudsters and a potential lack of data and visibility.

"All too often, banks lack the technology and capabilities to implement the necessary safeguards, responding to a primarily digital problem in an analog way – for example, phone calls attempting to piece together the path of a rapid series of money transfers," the authors wrote.

Modernizing fraud preventing with data analytics

The best solution to address these challenges head on is to leverage data analytics. This type of approach, when utilized in an expert manner, can not only help update fraud prevention strategies, but also enable organizations to take a more proactive, monitoring-based stance against fraudulent activity.

As noted by the Association of Certified Fraud Examiners, data analytics can be leveraged to glean more in-depth insights from transactional information, including to identify specific trends or patterns as well as anomalies that could point to suspicious activity. By analyzing sources like sales records, payment and expense reports, payroll information, inventory records, corporate documents and other details, applied analytic models can help identify the hallmarks of fraudulent activity.

Best of all, as ACFE noted, analytics is particularly beneficial when applied to the considerably large volumes of transactional and other financial information businesses and banks work with, and is significantly more successful than checking this data manually.

Why apply analytics: Specific benefits

In addition to improving efficiency through the elimination of manual processes, analytics can bring a wealth of other advantages to fraud investigations, including:

  • A wider scope: As EY noted, analytics can help expand visibility for fraud investigators as analytics models take into account a wider scope of pertinent data. In this way, fraud can be detected on a much larger scale and investigators can move away from less successful and more time-consuming spot checks of single, suspicious transactions.
  • Repeatable testing models: Investigators can also work with analysts to create repeatable testing models that can be run on an organization's data at any time. In this way, specific patterns or abnormalities can be more easily identified, and there is a reduced chance that fraud will fly under the radar undetected.
  • A proactive approach: Overall, using analytics can help businesses and financial service providers shift to a more proactive approach and pinpoint fraud before it becomes material, as opposed to chasing down fraudsters after the suspicious transactions have already gone through.

Tools and expertise required

In order to reap these benefits, organizations need specific technological tools. And, as ACFE noted, these advanced systems are best utilized alongside human judgment that can bring added, expert context to analytics results.

In this way, the best systems are Data as a Service tool suites that can easily be integrated within the organization's current infrastructure. These provide analysts with the capabilities needed to discover and catalog important data sources, prepare the information, and analyze it for the specific insights they are looking for.

To find out more, contact the experts at Unifi Software today.