Mobile onboarding needs to be fast, frictionless, and risk-free. Minutes count. Extending the mobile onboarding process by a mere five minutes has been shown to increase the application abandonment rate by 200%.
Machine Learning enables computers to recognize patterns and take actions without first being programmed with built-in directives to do so. Machine Learning software “learns” through exposure to data, automatically refining its own ability to recognize and respond to patterns.
At this year’s Money 2020 Conference, we talked to a lot of companies who are coming to the same realization: in an increasingly mobile-centric world, they need to implement and optimize mobile onboarding. Their future growth depends on it.
In financial services, retail, and healthcare, mobile onboarding has become a business necessity. But too often it suffers from the faults described in this infographic.
We’re back from the Lend360 Conference, a conference dedicated to exploring every angle of the online lending market.
On September 7, 2017, Equifax announced that it had suffered a data breach lasting from mid-May through the end of July. As a result of that breach, personally identifiable information (PII)—including names, addresses, birth dates, and Social Security numbers—for 143 million consumers was exposed. Credit card information for about 200,000 consumers may also have been exposed, along with account history information that often provides the basis for Knowledge-based Answers (KBA) authentication.