Director of the Centre for Counter Fraud Studies at the University of Portsmouth, Mark Button recently released work predicting that the global economic downturn being caused by the Coronavirus will cause an increase in online and eCommerce fraud attacks.
He bases his prediction on historical trends, citing statistics from previous recessions providing strong proof of a correlation between recessions and fraud. Fraud rose 5.6% in during the 1980 downturn, 9.9% in the 1990’s, and 7.3% during the ‘Great Recession’ of 2008.
In a guidance paper released for businesses and organizations, Button states that the impact of Coronavirus on fraud has already begun–with a 400% increase being observed since mid-February. He draws the conclusion that this recession will be no different, and in fact could see the problem grow to be worse than before.
“Past recessions have led to an increase in fraud and the University of Portsmouth has just completed research which shows that, if this happens at a similar rate as the previous three recessions, the increase in fraud could be as high as 60%+,” he says in the paper.
To backup this claim of a 60% increase over previous recessions, Button cites the severity of the potential downturn compared to previous ones. It’s accepted that the global economy is in recession. However, while full extent of the damage remains unknown. Citing data from the National Institute for Economic and Social Research, he warns that if predictions of a contraction of as much as a quarter of global GDP are realized, the fraud rate could increase to the point of actually doubling.
“Predictions of GDP shrinkage in Q2 vary from 15% (Centre for Economics and Business Research) to 25% (National Institute for Economic and Social Research),” he writes. “A 15% shrinkage could result in an increase in fraud of over 60%; a 25% shrinkage could mean this figure was 100% – a doubling of fraud.”
To mitigate the potential consequences of such a drastic spike in fraud, Button makes a number of suggestions including updating organizational understanding of high-risk areas/behaviors, having access to up-to-date ‘thread intelligence’, and quickly investigating if attacks do occur.