Organizations Seek Better ID Verification, But Most Don’t Think They Do It Well

An overwhelming majority of North American ecommerce and financial services companies consider identity verification a top priority but don’t believe they do it well or have all the tools for success.

That is a critical finding of a report from “The State of Identity Verification Maturity in North America,” from identity data company Whitepages Pro, which comes from a survey of 150 businesses across the U.S. and Canada in early 2018. Organizations were asked about their current practices, motivations for, and perceived obstacles to, adopting more mature identity verification strategies, and the benefits that come with increased identity verification maturity.

For the study businesses were asked, among other things, to rank themselves on a 4-stage scale of identity verification maturity for how they use identity data to combat fraud and improve the customer experience.

“Simultaneously fighting fraud while creating a positive, frictionless experience for customers is a high-wire act for most online businesses,” Ajay Andrews, director, product management, Whitepages Pro said. “Identity verification is critical to achieving both priorities, which is why there is so much interest in doing it well. Even though organizations know that identity verification is crucial, they sometimes struggle to overcome obstacles that prevent them from realizing its full benefits. And, as this survey shows, those benefits — in terms of reduced fraud, efficiency, increased transaction volume and improved customer satisfaction — directly impact the bottom line.”

Among the report’s key findings:

• Driven by the belief that fraud attempts are increasing in frequency and sophistication, identity verification is a priority for most organizations (93%). While they vary in the degree to which they use advanced techniques, most organizations want to improve their methods and outcomes. Just 2% percent believe they are completely successful at identity verification.
• Organizations want access to more data points (just 13% say they have all the data they need) and seek data linkages (relationships between data elements) to improve their verification processes. While access to traditional data (like a street address) is common, many still don’t have or use digital data (like an IP address). Most respondents believe linking data reduces fraud with 77% believing it increases a customer’s identity confidence.
• Organizations want more and improved identity verification automation. However, they often rely on in-house (historical data and white/black lists) that make it difficult to expand the automation use, resulting in an over-reliance on costly and time-consuming manual reviews. A large majority (71%) believe machine learning can help reduce manual reviews and make verification more effective.
• Organizations may not be balancing the barriers to adoption of better identity verification against the true cost of waiting. Those holding back most often cite cost, ROI uncertainty, the perceived lack of in-house skills, and the risk of increased customer friction. But the combination of direct hard dollar costs from fraud (an average of $548,500 per year) along with impacts such as reputational damage, lost business, lower revenues, and fewer repeat customers needs to be factored into the decision to implement a more mature identity verification strategy.
• Achieving the highest stage of identity verification maturity produces the greatest benefits. Organizations that reach the fourth stage of maturity see the largest overall reduction in fraud rates, fewer manual reviews, and an increase in clearing good transactions. This translates into both greater operational efficiency as well as improved customer satisfaction.

The report defined four stages of identity verification maturity:

Stage 1: Not currently performing identity verification. They either do not perceive a need (because they have not been the victim of confirmed identity fraud) or do not know how to verify identities.

Stage 2: Attempting identity verification, but not doing it consistently. These organizations are utilizing a small percentage of available data and are not examining the data linkages they use. They rely heavily on manual review to approve or deny transactions.

Stage 3: Consistently using identity verification, incorporating a larger proportion of available data, and experimenting with data linkages. Often these organizations are highly motivated to reduce fraud and to increase the speed and efficiency of the approval process, which drives them to consider increased automation.

Stage 4: Have embraced holistic identity verification. These organizations verify multiple data elements and link them. They have embraced automation.