In 2020, account origination and account takeover (ATO) fraud cost organizations and consumers over $9 billion. Nearly half of adults in the U.S. experienced one of these forms of identity theft in the past two years. Each identity fraud event severely jeopardizes a customer relationship and the associated lifetime value.
Fraudsters continually probe for weaknesses in authentication processes. Low-quality authentication processes not only waste operational resources and fail to prevent fraud, but also frustrate consumers with unnecessary friction and interrogation.
Forward-thinking organizations are improving fraud prevention, customer experience, and operational efficiency via dynamic data elements. For example, the attributes specific to an individual mobile device—such as activity, tenure, or prepaid status—are stable and reliable. These attributes cannot be spoofed or hacked—they reliably give clues as to whether consumers are who they say they are. Dynamic device data, when used in combination with online and offline data, significantly increases fraud prevention and the ability to let legitimate customers through faster.
- The six common authentication data types, and the strengths and weaknesses of each
- How to mitigate the weaknesses in common authentication approaches
- Why dynamic data can't be spoofed or hacked, and how to use it effectively to reduce fraud and improve the consumer experience