Digital organizations operate in real time, and their users have come to expect easy, frictionless access to services anytime they want it. Those that can deliver on that promise are rewarded with brand capital and economic growth; they develop a community of satisfied, paying customers, and word gets around that this is an organization that delivers where others don’t.
But the pursuit of digital customer growth isn’t simply a binary problem. These organizations always seek a balance between delivering an excellent customer experience, which creates happy users, and eliminating risk, which reduces the potential for fraud. A great customer experience is fast and frictionless—users are onboarded and start using a service in minutes or even seconds. But safeguarding against fraud demands more risk oversight.
You can reduce fraud AND deliver a frictionless customer experience
There are various approaches to identity verification and fraud prevention. Some providers specialize in one approach or technology while others have cobbled together multiple approaches, with varying degrees of accuracy, through acquisitions or partnerships. Some providers verify identities solely on the basis of specific identity components such as device, email, or other elements of PII. Other providers are document-centric, meaning that they put all customers through the process of verifying government-issued ID documents, and additionally require a selfie or video to ensure liveness and a match to the ID document photo, regardless of the risk they present. And still other providers focus primarily on fraud and cybersecurity signals to detect bot activity or other fraudulent behavior. There are a dizzying assortment of options.
Most solutions on the market treat that as a proposition of one or the other, as in, you can have either a good customer experience, or less risk—take your pick.
But here’s the rub: Those solutions that enable a fast experience typically are using very few data sources to inform their decisions about identity and fraud. A surprising number of solutions take this approach, rendering them incapable of providing a truly holistic and accurate explanation of the identities they’re tasked with verifying. The outcomes they deliver are incomplete, or they require additional step-up methods and manual reviews that are costly, prone to inaccuracy, and can result in customers clicking away and lost revenue.
Stop saying “no” to good applicants
The problem with not looking too deeply or broadly into data sources to identify applicant identities is that enterprises are saying “no” to a lot of good applicants. These organizations just don’t know that some of these applicants are good because they aren’t looking very hard to find them. This is typically the result of using solutions that seek only to identify individuals with readily available information like credit bureau data. Their approach is to rapidly accept or reject applicants on the basis of this, and only this, data.
However, there is a huge population of consumers who aren’t easily identifiable through evaluation of standard data sources. These include individuals who simply don’t have digital footprints or are invisible to the financial industry. As a result, they cannot be evaluated by legacy solutions, making them appear ineligible for credit, goods, and or services and ultimately turned away. But consider the demographics of Gen Z and Millennial generations, as well as individuals who are new to the country. They likely have thin or non-existent credit footprints and histories, which doesn’t mean they’re risky customers, it just means that it’s hard to identify them through digital channels. Legacy solutions will identify them as risky and recommend rejecting them, which leads to a large population of false positives, most of whom are actually legitimate customers. What’s more, they are revenue opportunities that are being missed.
Identity verification accuracy as the foundation for customer growth
How does a technology buyer make sense of the market and the numerous messages that identity verification companies hang their hat on? Providers are building products for customization, configurable workflows, know-your-customer, student data, seller data, and other solutions in an effort to differentiate themselves in the crowded identity verification market. But solution specificity is not what’s important—identity accuracy is.
Organizations that rely on these solutions are, in effect, leaving money on the table as they reject good customers simply because they rely on limited and stale data and don’t have the ability to correlate known good and bad identities. A more accurate approach uses redundant data sources, account performance data, as well as connections among those data sources, to tell a more complete story about individuals, which will lead to accepting more of them unless they truly identify as potentially risky.
The digital world is all about immediate access. Economic growth and delivery of important services can only happen when that access is given to “good” customers, but it’s severely hampered when bad decisions about identity result in the introduction of fraud, bias, and bad economic outcomes. A better approach is to implement identity verification that offers a path to 100% verification of all good identities on the internet—while eliminating fraud—so the digital economy can continue to scale and meet the needs of a changing world.
Brigitte Engel is a Senior Director, Product Marketing at Socure responsible for emerging markets such as Buy Now, Pay Later, Cryptocurrency, and Online Gaming. Previously, Brigitte held marketing leadership roles with leading endpoint security companies, including Cylance and Guidance Software, and identity fraud vendor ID Analytics.