Professionals holding procurement jobs in the UK must become more vigilant about rampant procurement fraud, and CPOs and CFOs should consider investing in advanced machine learning fraud prevention tech to combat the problem, software analytics company, SAS, has concluded in a new study.

The study, which polled 850 British business leaders, warns that the UK has become a procurement fraud ‘capital’ with almost a third (31%) of British firms falling prey to contract bid rigging and 43% to duplicate invoices. Other common forms of procurement fraud include fake sellers – ‘ghost vendors’ –  and payroll scams. The ensuing damage can be enormous. 40% of the companies lose between €150,000 and €400,000 a year when they are struck by procurement fraud.

While procurement practitioners, from permanent employees to procurement and supply chain interims, are trying to thwart the fraudsters, the report finds that the reasons why UK companies are failing to stamp out the problem more effectively are a combination of lax attitudes to auditing and a failure to harness new fraud prevention technologies. UK businesses are well behind their EMA counterparts in regular auditing of procurement fraud (29% to 46%). Just 12% of UK firms are using advanced analytics technologies to tackle procurement fraud, while a mere 9% have adopted AI technologies, the study found. More commonly, professionals in UK procurement and supply chain jobs are left trying to detect fraud through manual controls (43%), rudimentary rules-based software detection solutions (38%) and anomaly detection tools (32%).

The report recommends a widespread softening of attitudes toward new software tools for detecting fraud. It states: “Machine learning models also have the added advantage that they learn over time, meaning they can detect new threats and techniques as they emerge. This is distinct from manual controls and rules-based detection, which take a rear-view mirror approach — analysing old data and patterns retrospectively as opposed to real-time reviews.”

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