Latest quarterly updates deliver deep cross-dimensional identity intelligence, faster decisioning, and improved model accuracy to combat evolving fraud tactics
Sift, the AI-powered fraud platform, today announced significant new product innovations following the recently unveiled Identity Trust XD framework.
The latest enhancements include the introduction of Global Identity Insights, along with substantial improvements to Sift’s payment fraud protection model and several Sift Console upgrades designed to streamline operations and improve decisioning accuracy across the platform.
“Understanding user identity signals and behavior across digital platforms is the cornerstone of modern fraud prevention,” said Raviv Levi, Chief Product & Technology Officer at Sift. “Our latest product innovations give fraud teams unprecedented context about their users, allowing them to distinguish between legitimate customers and fraud actors in milliseconds. This combination of rich identity data and rapid decisioning both protects revenue but drives profitable growth.”
Read More:Â GenAI in Fintech: Mitigating Risk and Maximizing Value
Key updates to the Sift Platform include:
- Global Identity Insights – a Shortcut to Trust: Reduce research time and minimize human error during reviews through a Sift Console tab providing a comprehensive profile view of users behavior, and risk outcomes with other Sift customers.
- Account Takeover (ATO) Activity Analyzer (Coming April 2025): Intervene before risk undercuts revenue with immediate insights into account security threats. Sift now surfaces behavioral anomalies and suspicious patterns linked to credential stuffing, brute force attacks, and unusual login attempts.
Related insight: Account takeover (ATO) remains a persistent threat to online businesses, jumping 24% year-over-year in Q2 2024 - Console Enhancements: Multiple workflow improvements including Integration Health Reports, Review Queue Auto-Clean functionality, and Feature Pruning capabilities that automatically eliminate unnecessary data points from fraud detection models.
- Payments Model Updates:Â Improvements including Payment Data Intelligence for cryptocurrency transactions, and Physical Address Normalization and Risk Signals.
- Industry-Specific Solutions:Â Track betting patterns more precisely, including minimum and maximum betting matches and deposit/withdrawal velocities, using new Wager Risk Signals for iGaming customers.
Read More :Â Global FinTech Interview with Steve Cover, CTO, iPipeline
[To share your insights with us, please write to psen@itechseries.com ]
