Ontop chooses ThetaRay’s SONAR AML Solution to Identify Threats From Financial Crime

Ontop chooses ThetaRay's SONAR AML Solution to Identify Threats From Financial Crime
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One of the top suppliers of AI-powered transaction monitoring technology, ThetaRay, today announced that Ontop, a FinTech platform reshaping the future of work, has chosen ThetaRay’s cutting-edge SONAR anti-money laundering (AML) solution to track and identify both known and unidentified financial crime threats.

Mark Gazit, CEO of ThetaRay, said, “Ontop is a global leader in the new digital economy that is creating financial opportunities for companies and people through remote work. “We are proud to partner with an innovative fintech that is helping remove barriers in the financial world. ThetaRay AI tech will give Ontop the ability to process payroll transfers smoothly and quickly, meet any regulatory compliance requirements, and win the trust of business partners.”

ThetaRay’s SONAR solution is based on a proprietary type of AI called artificial intelligence intuition, which eliminates human bias and gives the system the ability to detect anomalies and discover unknowns outside of typical behaviour, including completely new typologies. It makes it possible for banks and FinTechs to implement a risk-based strategy to efficiently identify suspicious activity and build a complete picture of customer identities, including across intricate, international transaction paths. In comparison to rules-based solutions, this enables the quick identification of both known and unidentified money laundering threats and a reduction in false positives of up to 99%.

Julian Torres, Chief Strategy Officer and Co-Founder of Ontop, said, “The biggest pain points in cross-border payments are high costs and a lack of speed and transparency. The next-gen AI solution from ThetaRay will give our business confidence by covering known and unknown crime typologies. The machine learning will also deliver operational efficiency and help customer satisfaction by reducing false positives and more accurately identifying truly suspicious cases.”

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