ThetaRay, a leading provider of AI-powered transaction monitoring technology, and Piie, Inc., an insurtech providing an intelligent payment engine, today announced a collaboration to implement an advanced AML solution for insurance claim payments.
Through the agreement, Piie (Payments Intelligent Integration Engine) will integrate ThetaRay’s AI-driven SONAR transaction monitoring AML solution to monitor and detect anomalies pointing to suspected financial crime on its payments-as-a-service platform that includes mobile application support.
A scalable, secure payments platform headquartered in Charlotte, NC, Piie serves the insurance industry with an AI-driven real-time payments solution. Using ThetaRay’s transaction monitoring AML solution will further enhance and strengthen Piie’s current robust risk controls.
“Piie is revolutionizing how payments are processed within the insurance sector as the financial industry undergoes a digital transformation that is improving the customer journey for insurance companies,” said Mark Gazit, CEO of ThetaRay. “We are proud to partner with an insurtech that is focused on digital payments that enable companies to process insurance payments with lower costs and greater speed and accuracy.”
Ritesh Kirad, CEO of Piie, Inc. noted that “ThetaRay’s advanced AML monitoring capabilities complement Piie’s focus on a modern, secure payments architecture that reduces cost, improves efficiency, and delights policyholders.”
ThetaRay’s award-winning SONAR solution is based on a proprietary form of AI, artificial intelligence intuition, that replaces human bias, giving the system the power to recognize anomalies and find unknowns outside of normal behavior, including completely new typologies. It enables fintechs and banks to implement a risk-based approach to effectively identify truly suspicious activity and create a full picture of customer identities, including across complex transaction paths. This allows the rapid discovery of both known and unknown money laundering threats, and up to 99 percent reduction in false positives compared to rules-based solutions.
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