But as the massive volumes of data collected by companies balloon, this task has become increasingly arduous, time-consuming and humanly impossible.
Instead of investigators manually reviewing spreadsheet rows and columns, looking for three or four data elements that together indicate a suspicious transaction, ML can peruse thousands of data elements — instantly. “We let the data tell us where to look, as opposed to us having to look everywhere,” says Tim Bryan, one such investigator and a partner in the Crowe forensic accounting and technology services group.Since the solution is capable of continuous learning, its ability to detect fraud improves by the day, Bryan notes. “Each time the tool is right about an actual anomalous transaction, the information automatically goes into the system, making it smarter.
To test the tool’s ability to identify suspicious and possibly fraudulent activity, Crowe recently used the solution to analyze more than 16,000 contracts from a large telecommunications company. “With human analysts, the project took five professionals four months to complete,” says Bryan.