In today's ever changing fraud landscape, much of the currently used statistical-based fraud detection methodology is creating significant challenges for both organizations and end users. These statistical models generate high false positive rates and provide a risk score that does not effectively distinguish between legitimate and malicious activity.
Additionally, these dated risk-based authentication solutions, working with step-up authentication, were built upon the assumption that authenticating suspicious activity will cause minimal disruption to end users, and effectively stop fraud. However, this has not been the case.
With the introduction of sophisticated threats, such as advanced phishing, pharming and malware, authentication has become less effective. Authentication methods-including out-of-band and one-time passwords-as well as security questions can be bypassed with minimal effort by fraudsters.
Consequently, more sophisticated authentication techniques have been developed. These techniques have severely impacted the customer experience and have been bypassed by advanced threats. The amount of unnecessary challenges and disruptions for end users is growing without a meaningful reduction in fraud. As fraud rises and the customer experience diminishes, there is a strong need for fraud tools that can stop fraud effectively, while actually enhancing the customer experience.