Big data can be a powerful tool for deterring, detecting and investigating fraud throughout organizations, yet few companies are effectively leveraging forensic data analytics, according to an EY report.
The survey finds that 42% of companies with revenues between US$100 million and US$1 billion are reviewing less than 10,000 records. And 71% companies with more than US$1 billion in sales report examining just one million records or fewer.
“Consider how many cheque payments a company makes every year, and for each there is a cashbook entry describing the reason for payment — 10,000 doesn’t come close to reflecting the number of records produced by mid-sized and larger companies,” says David Meadows, associate partner in EY’s Fraud Investigation & Dispute Services practice. “That’s a huge missed opportunity. Reviewing as much data as possible can provide a clearer picture of what’s happening within an organization and where potential fraud may be occurring.”
That means considering both numbers and text from across various systems.
“Terms like gift, facilitate, as instructed, cash withdrawal, customary fee or consultant payments can be red flags of questionable or high risk payments. But only 47% of respondents said they evaluated both numbers and text when searching for traces of fraud,” says Meadows.
“Companies know there are high risk numbers in book entries, such as round thousands or duplicates, but they’re only just starting to analyze descriptions for those book entries. Looking at both the numbers and words can mean the difference between uncovering fraud, and falling victim to it.”
Companies can’t afford a lack of oversight, especially given the ever increasing attention to ethical behavior by both shareholders and regulators.
“The stakes are much higher now for Canadian companies,” says Meadows. “Companies can avoid challenges down the road by utilizing forensic data analytics. Key success factors include incorporating best practices and the experiences of others and implementing appropriate technologies to improve fraud detection and enhance risk assessment. The opportunities to mitigate these risks are significant with forensic data analytics.”