The Record - Issue 18: Autumn 2020

131  F I NANC I A L S E R V I C E S V I EWPO I NT How digital behaviours can identify consumers MAR K E L L I OT : B I OCATCH As financial institutions grow their digital business, distinguishing good customers from bad actors is possible by examining the applicant’s digital behaviour patterns D uring the peak of the Covid-19 pandemic, financial institutions observed a 250 per cent increase in digital channel usage. This rise has driven them to accelerate transfor- mation plans as digital shifts from one of many customer-acquisition channels to a primary one. Fraud was an inevitable fallout as cybercriminals capitalised on fear and confusion. Consequently, when reimagining customer acquisition, financial institutions must consider potential fraud losses as well as potential gains from maximising the customer onboarding experience. Traditional security measures are limited in addressing these two considerations. For example, knowledge of personal information is no longer considered a valid form of identity proofing as phishing attacks and massive data breaches have created an abundance of sto- len personal information. In addition, device ID-based controls are extremely limited in pro- tecting the account-opening process as a new customer is likely coming from an unknown device. To overcome these challenges, behav- ioural biometrics have proven to be an effective method of control to reduce fraud risk in the new account-opening process while minimising false declines. Behavioural biometrics identify clear differ- entiations in digital behaviour patterns in the account-opening process. For example, cyber- criminals input data differently as they don’t have the same level of familiarity with personal information as a genuine user. However, they will usually be more familiar with the new account application form than a genuine user since they fill out multiple applications. Once something only seen in science fiction, enterprise-grade advanced behavioural biometrics are now proven science providing financial insti- tutions with immediate value and more effectively detecting fraud in the account-opening process. For example, a digital bank undergoing a new account-opening fraud attack instantly observed a 70 per cent increase in detection when behav- ioural biometrics were introduced to their existing security controls and allowed them to continue accepting new customers with confidence. Amore recent implementation by a large bank in Asia showed significant value within weeks of leverag- ing machine learning-powered risk models. As digital interactions become the new normal, unique approaches are required to build trust and safety in a highly impersonal online world. Behavioural biometrics are a proven solution to identify good customers and for financial insti- tutions to reward them in return. Mark Elliot is the chief marketing officer at BioCatch “As digital interactions become the new normal, unique approaches are required to build trust and safety”