The power of artificial intelligence (AI) and its potential is constantly up for discussion within the tech industry. The technology continues to weave itself into a variety of verticals, showing up in places we wouldn’t expect. 2019 in particular has seen verticals such as healthcare and automotive embracing AI to further innovation within the sector. In particular, the retail sector has on boarded many AI based products, such as supermarkets using AI to benefit goods delivery systems to help track the prices and locations of products around their stores and warehouses.
One development that we’re continuing to see is the increase of AI in fraud detection, assisting companies in spotting fraudulent activity in their spend management. Fraudulent activity and succumbing to phishing scams is not something organisations are usually open to discussing, however, scammers are getting smarter and more creative, and fraud can result in costing companies up to an estimated five per cent of annual revenue each year. Five per cent may seem like a small percentage of annual revenues, but it can add up to millions for global businesses, but from a qualitative perspective it also means damaged reputations and a reduction of trust.
What do we know about fraud?
Clearly, it seems some people are trying to do the right thing by reporting fraud. But, as is shown from the amount of revenue that’s disappearing, many are not.
The 2018 Report to the Nations Global Study on Occupational Fraud and Abuse found that weak internal controls were responsible for nearly 50 per cent of all instances of fraud.
SMEs are naturally impacted as they typically have fewer fraud controls and more prevalent funding issues, but of course bigger companies offer a greater return for fraudsters. Therefore, it’s important to address how this problem can be fixed and what businesses should be doing to be more vigilant.
Possibly unsurprisingly, tip offs are by far the most common way that fraud is identified, while internal audits and management reviews only identify 15 per cent and 13 per cent of fraud, respectively. Most tips come from employees (53 per cent), but they also come from customers (21 per cent), vendors (8 per cent), competitors (2 per cent), and other sources (21 per cent).
Why most methods of fighting fraud fail
With so many avenues for both intentional fraud and accidental error, and with the difficulty of telling one from the other, how do businesses stop fraud having a hugely negative impact on their operations?
Audits are a very common method to find fraud, but they pose an interesting dilemma. On one hand, you can audit every transaction, from purchases to invoices to expenses. This method doesn’t guarantee accuracy, though, and takes a great deal of resources.
On the other hand, you can save time by auditing a percentage of these transactions at random and hope that you find any fraudulent transactions. Either way, audits are very manual, whether your company has an internal audit team or outsources the task.
So, what’s the best strategy to fight fraud? It might be to go beyond what is humanly possible.
Leveraging technology to find fraud is not a new idea. Data analysis has already been used to find significant financial crimes. In fact, data monitoring and analysis and surprise audits have been correlated with the biggest reductions (52 per cent lower losses) and duration (58 per cent faster detection) compared to alternatives. The difference between yesterday’s technology and today’s, is that now we can bring these tools into processes at companies to identify the everyday fraud that impacts profitability and shareholder value.
Artificial intelligence can look at a user’s spend across the entire organisation to identify suspicious activities. This capability to look for fraud in a comprehensive way is important; if someone finds they can get away with fraud in one area, it suddenly becomes much more tempting to commit fraud in other areas, and soon, there is a steady flow of money leaving an account.
Based on fraud research, we know that 77 per cent of all instances of occupational fraud come from Accounting, Operations, Sales, Executive/Upper Management, Customer Service, Administrative Support, Finance, and Purchasing. Given this information, it’s critical to get all spend for these departments (POs, invoices, contracts, expense reports) in one single platform. Only then can you leverage AI and safeguard company cash by controlling in-flight transactions that are potentially fraudulent across the organisation. By adopting an AI-powered solution to spot fraudulent transactions, organisations can have the upper hand against criminals wanting to compromise their data.
Get ahead of fraud with AI-powered audits
It is now more important than ever to combat fraudulent activity when it comes to managing your spend. With today’s technology, you can shift from detection to prevention, comparing your organisation’s behaviour to the norm at a granular level and identifying potential fraud activity proactively.
Artificial intelligence has advanced to a point where it has the capability to aggregate and analyse billions of transactions from the business community to compile profiles and learn what constitutes ’normal‘ behaviour. Then, systems can compare each transaction to what’s normal and flag anomalies for finance teams to review. This approach can identify and stop losses to fraud more effectively than traditional audit processes while freeing up resources to focus on higher value tasks to drive company strategy.
Fraudulent criminals can be vigilant, but so can businesses. By utilising AI-powered solutions, businesses can arm themselves with valuable tools to combat fraud and accidental errors and protect revenue from slipping through the cracks.
John Callan, Senior Director, Coupa