The True Cost of False Positives in the Battle to Prevent Fraud
Loss of revenue from false positives can exceed the cost of fraud
In digital fraud prevention, there is a fine line between flagging too many transactions as potentially fraudulent and not flagging enough. Too many false negatives means that fraudsters are slipping through the cracks, too many false positives means legitimate users and transactions are being flagged incorrectly, leading to undue friction and lost business. As digital transactions grow, 66% of businesses cite balancing friction with fraud prevention as their number one concern (IDology). Given this, it is no longer enough for authentication solutions to just prevent fraud, they need to demonstrate how they can keep false positives low as well.
Just as each industry has different fraud tolerances - an acceptable ecommerce chargeback rate ranges from 0.5% - 1% - low levels of false positives are also seen as a cost of doing business.
With any fraud prevention solution it is impossible not to block some legitimate users.
However, solutions that generate too many false positives are introducing friction that can cause revenue loss due to onboarding drop off, cart abandonment or negative reviews.
Aite Group estimates that the e-commerce industry will experience false positive losses of $443 billion by 2021, a much larger number than the projected fraud losses of $6.4 billion.
False positives are critical to pay attention to from a customer experience perspective also as a seamless user experience is essential for digital channels. A 2018 PwC survey found that 73% of people consider a good experience to be crucial for their loyalty to a brand or service, while one in three customers say they would stop doing business with a company they like after a bad experience. In fact, one industry study cited by American Banker found that 40% of consumers abandon the onboarding process for financial institutions, citing the amount of time and personal information required.
Despite these facts, institutions tend to overcorrect. As businesses notice a growing fraud risk and move to protect themselves, they increase false positives and false declines significantly. But savvy digital retailers, for example, actually give more weight to false positives (80%), than they do actual fraud (62%), when calculating the cost of fraud overall on their organizations, according to Pymnts. This is because false positives are not just friction points, they challenge core business goals. Companies need to factor in the impact false positives have on other business metrics, such as customer acquisition cost (CAC) and lifetime value (LTV). Negative onboarding experiences can lead visitors to drop off, increasing CAC, while friction during login or purchasing can lead to churn or cart abandonment impacting LTV.
Friction during onboarding is an even bigger headache for fintechs and traditional financial institutions that offer online and mobile onboarding. Completing identity proofing measures in order to comply with KYC regulation often leads to a long and cumbersome account opening process that drive away new users. According to American Banker, adding 5 minutes to the onboarding process can increase drop off rates by 200%. A similar report by Osterman Research noted that 56.3% of millennials would abandon an application for a financial services product if they could not complete it on their mobile and would join a more mobile-friendly competitor. These findings emphasize the importance of a quick and seamless onboarding experience to achieving business goals, especially via mobile devices, the channel that now represents the majority of consumer banking interactions. In fact, The Financial Brand projects that 88% of consumer-bank interactions will happen through smartphones by 2022.
With digital transaction and mobile banking adoption growing, a fraud prevention solution that adds security while maintaining the conveniences associated with online and mobile is key. Fraud prevention solutions aren’t really effective unless they can tell a good user from a bad and implement different processes for each.
Behavioral biometrics can help with this balance. By nature, this fraud prevention method is dynamic and adaptive, meaning that it takes into account normal changes in behavior and distinguishes them from anomalies that might indicate fraud. When compared to fixed rules-based solutions that need to be manually adjusted to changes, behavioral biometrics inherently create fewer false positives.
As more transactions move to mobile, companies need to find their optimal balance between fraud and friction.
Behavioral biometric solutions work in the background to provide a risk score which helps eliminate unnecessary friction during mobile identity verification and authentication without increasing the number of false positives. It’s time for companies to demand more from their fraud solutions, it’s no longer acceptable to negatively impact business growth in the name of fraud prevention.