The financial and reputational cost of online fraud to banks can be disastrous. Especially compared to the relatively minor cost of implementing a solution.
Banking customers around the world conduct more of their business online than ever. According to Capgemini, global non-cash transactions are expected to top $1trn by 2022. But as more customers move online, so do cyber-criminals and fraudsters. Banks need to stay one step ahead.
Detection and prevention
In addition to cost, there are a multitude of considerations for banks in preventing online fraud. A recent Forrester ‘Total Economic Impact’ study revealed that improving fraud detection was a top priority for more than 37% of decision makers in financial service and insurance firms. However, many solutions that brands use can impact the user experience, making it more difficult for honest customers to access products and services.
The study examined a bank that used an effective software solution to identify and stop malware-based fraud over a three-year period. It found that the bank realised $21.3m in benefits over the period versus costs of $8.3m, producing a net present value (NPV) of $13m and an ROI of 156%.
The study also revealed that, over the three years, the bank was able to stop up to 90% of malware-based attacks, which had historically contributed up to $7.5m in annual fraud losses.
In addition to the financial cost of fraud prevention, huge reputational damage can be caused by media coverage of fraud. According to a Forrester Analytics Global Business Technographics Security Survey, at least 10% of companies experienced customer churn in the aftermath of a data security event.
Finding effective solutions
There are multiple types of fraudulent activity that can harm banks and their customers, but to take one example, new account fraud (NAF) is one of the fastest growing. NAF involves fraudsters using stolen or “synthetic” identities to open multiple new bank, credit and other accounts. They borrow as much money as they can before moving on, leaving a trail of debt in their wake. New accounts can also be used to launder stolen funds. In the UK NAF surged by 159% year-on-year to reach $38m in 2018, according to UK Finance.
Financial institutions therefore face a serious challenge, in trying to balance the overwhelming need for quick-and-easy on-boarding of new customers with the major financial and reputational risks associated with NAF. Yet legacy fraud solutions can sometimes make the problem even worse.
NAF is hard to spot. Fraudsters either use legitimate information stolen secretly from real consumers, or they stitch together synthetic identities using real and fake info. Either way, it can be difficult for traditional filters to detect using threat intelligence feeds and static data. Alternatives employing ID documentation checks and physical biometrics may be more accurate in spotting fraudsters, but they crucially add friction for the customers, and are often not scalable across regions.
Buguroo is the developer of bugFraud, a comprehensive online fraud prevention solution for banks and retailers. It uses deep learning and behavioural biometrics, alongside device assessment and advanced malware detection, to enable anti-fraud protection at each stage of a customer’s online journey.
To tackle NAF, Buguroo uses a behavioural approach. It analyses thousands of key parameters on how users navigate their banking portal and fill out a new account form. This provides essential information on whether the user has abnormal fluidity or familiarity, flagging the risk that they’re not a genuine customer. It all happens in the background without impacting the user experience.
