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UOB first to adopt new Tookitaki-HP AML solution

Singapore A.I. fintech Tookitaki teams up with Hewlett Packard Enterprises to offer banks new regtech solutions.



Abhishek Chatterjee, Tootitaki

Hewlett Packard Enterprise has announced a collaboration with Tookitaki, a provider of compliance solutions for the financial services industry, to provide a new offering designed for banks and financial institutions across Asia-Pacific. Singaporean bank UOB is the first to adopt it.

The new offering delivers Tookitaki’s artificial intelligence-powered anti-money laundering (AML) solution in a secure and flexible as-a-service consumption model using HPE GreenLake for big data.

The new solution enables financial institutions to create a central big data platform that can perform AML data analytics and enable A.I. AML solutions. Delivering the solution as a service through HPE GreenLake affords banks the agility, flexibility and scalability of a cloud experience while providing increased control, cost effectiveness and governance when deploying A.I.-optimized infrastructure platforms and solutions on-premises.

Singapore’s UOB is the first financial institution in the world to have chosen Tookitaki’s AML solution on HPE GreenLake to enhance the bank’s AML system through A.I. UOB customized Tookitaki’s AI solution to meet the bank’s needs.

Abhishek Chatterjee, co- founder and CEO at Tookitaki, said “Together with HPE’s deep domain expertise in big data as-a-service, our systems use a combination of distributed data-parallel architecture and machine learning to ensure scalability across multiple layers of technologies and systems. Banks are able to benefit from this collaboration by implementing high module accuracy systems to ensure they are staying compliant.”

UOB was able to pioneer an A.I.-enhanced AML system which concurrently applies two AML risk dimensions: transaction monitoring and name screening.

UOB screens 60,000 account names    monthly using the technology to determine if they belong to the individuals or entities on global regulatory watch lists. UOB’s A.I.-enhanced AML system can pinpoint more accurately higher-priority cases from the more-than 5,700 average monthly suspicious transaction alerts flagged.

This enables the bank to deploy more deliberately the necessary resources in investigating potential money laundering attempts. The models used for name screening and transaction monitoring have achieved 96 percent prediction accuracy in the ‘high priority’ category.

“By complementing Tookitaki’s expertise in regulatory compliance with our data analytics platform and our as-a-service offering, we are able to seamlessly bring real-world A.I. solutions that can yield business outcomes,” said Khai Peng Loh, Hewlett Packard Enterprise’s general manager of Asia Pacific solution sales. 

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