Mobile identity solution provider TeleSign announced the addition of machine learning to its fraud intelligence solution, TeleSign Score. The technology will help the solution to utilize historical indicators to identify hidden insights and predict fraudulent activity.
“With 90 percent of companies experiencing online fraud in the past year, finding ways to proactively block fraudsters has become an increasingly vital component of every online fraud prevention strategy,” Aled Miles, CEO at TeleSign, said in a press release. “The advances we’re making using machine learning within TeleSign Score are helping our customers uncover hidden insights and predict, prevent and respond to fraud in real time.”
According to the latest “Beyond the Password” report from TeleSign, approximately 86 percent of companies reported being extremely or very concerned about authenticating the identity of their users.
TeleSign said the fusion of machine learning and phone number data will deliver an increase in accuracy and effectiveness for predicting and scoring online user risk. That score is customizable based on customer, industry or specific use case, which allows companies to take a proactive approach to fraud detection.
“Everything we do is based on our ability to ensure our renters and landlords are who they say they are,” Jonathan Eppers, CEO of RadPad, explained. “Integrating TeleSign Score has helped our brand reduce fraudsters’ chances of creating multiple fake accounts and disrupting the genuine user experience. TeleSign Score has not only helped us streamline the account registration process; we’ve also increased conversions and securely grown our user base with verified users.”
Key features of the TeleSign Score upgrade include:
- Machine learning
- Labeled data anlysis
- Additional customer-submitted trust anchors
- New IP address rules