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Security specialist ThreatMetrix announced the availability of its Spring 2016 technology release, which introduces deeper decision analytics, an enhancement to mobile offerings and stronger authentication capabilities.
The latest release includes Smart Analytics, which pairs behavioral analytics with machine learning for a more integrated approach, according to the company.
Smart Analytics includes Smart Rules behavioral analytics algorithms and a transparent approach to machine learning called Smart Learning.
Smart Rules offers a customizable toolset that enables customers to more accurately detect and analyze changes in user behavior, helping to more accurately identify fraudsters without adding friction for good consumers, the company noted.
“As more and more consumers buy goods and access services and content through digital channels, gaining insight across different industries and channels can accelerate and personalize user experience while reducing fraud and operational cost,” Vanita Pandey, vice president of Product marketing at ThreatMetrix, told eWEEK. “However, consumers behave in very diverse ways that are hard to predict and fraudsters use new techniques to mimic legitimate user behavior.”
Pandey noted both consumer behavior and fraud patterns are evolving fast, and translating events into a set of interpretable rules or incorporating increasing amounts of information is critical but can be difficult for the businesses.
“This makes data analysis and modeling hard to scale. As such, organizations need a better way to protect a trusted user while preventing fraud,” she said.
A new software development kit (SDK) for Apple OS X and Microsoft Windows provides a faster way to activate endpoint applications across the business, according to the company.
The SDK profiles devices for specific platform-based applications, providing advanced risk analysis, fraud detection and device recognition.
In addition, a new identity verification feature combines static identity checks with dynamic information from the ThreatMetrix Digital Identity Network to more accurately verify a user’s true identity.
A two-factor authentication feature combines secondary authentication with dynamic information from the ThreatMetrix Digital Identity Network to reduce instances of step-up authentication.
“Decision analytics deliver to businesses the ability to use real-time intelligence across regions, industries and use cases to help correlate seemingly disconnected events and security incidents,” Pandey said. “This can enable organizations to identify anomalies between current and historical behavior and differentiate between trusted and fraudulent users.”
ThreatMetrix’s products allow organizations to differentiate between trusted users and potential threats by analyzing the relationship between devices, digital personas and contextual behavior over time to establish a true digital identity that is continuously evaluated in the context of every interaction, she said.