Duality Technologies Launches SecurePlus Query, the First Privacy-Enhanced Query Engine for Data Collaboration
Duality SecurePlus Query utilizes Homomorphic Encryption to enable banks to securely collaborate across institutions and borders in financial crime investigations, without compromising data privacy
Duality Technologies, a leading provider of Privacy-Enhancing Technologies (PETs), announced today the launch of SecurePlus Query, a privacy-by-design query engine for data collaboration. The novel solution opens up new ways for organizations to maximize data insights and leverage collective intelligence. In the financial industry, SecurePlus™ Query enables banks to join forces in their fight against money laundering and financial crime by sharing information without exposing sensitive data. Duality SecurePlus™ Query is the first productized Homomorphic Encryption solution addressing real-world problems.
Duality SecurePlus™ Query enables financial crime and compliance teams to carry out collaborative investigations across groups, institutions and borders by keeping sensitive data encrypted throughout the process. Specifically, it allows different teams and entities to securely query one another’s data – for example, by asking questions about accounts and transactions – and to receive answers in seconds. This approach helps weed out false positives, improve outcomes, increase efficiency, and most importantly – effectively expose financial crime networks worldwide.
“Duality SecurePlus™ Query enables our customers to collaborate digitally in a trusted way while still complying with stringent data usage and privacy regulations,” said Alon Kaufman, CEO and Co-founder of Duality Technologies. “For financial crime investigations, we provide a first-of-its-kind solution that enables banks and law enforcement to automate their collaboration processes, thus increasing their effectiveness and timeliness of response by orders of magnitude in comparison to current manual processes. Duality SecurePlus™ platform enables organizations to leverage the power of Artificial Intelligence and Big Data for privacy-enhanced collaborations”.
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The UN estimates that $1.7 trillion is laundered globally every year. Despite increased efforts and spending by banks, only 1% of laundered funds are actually identified and seized. Combatting this worldwide financial scourge demands that banks cooperate, leveraging collective data and intelligence. Financial regulators such as the UK’s FCA have encouraged inter-bank collaboration to fight financial crime, including the implementation of Privacy-Enhancing Technologies in the face of tightening data privacy regulations like the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
“We believe that encrypted inter-bank data sharing will help eliminate blind spots in AML and FinCrime investigations while protecting customer privacy,” said Vishal Gossain, Vice President, Global Risk Management, Scotiabank. “Advanced technology tools supporting AI and data privacy are needed to achieve this goal. We have partnered with Duality to validate and implement their innovative SecurePlus™ Query solution for AML, in order to fulfill the promise of privacy preservation in information sharing. This platform has the potential to become one of the key tools for inter-bank collaborations.”
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SecurePlus™ Query has been successfully piloted by the Cyber Defence Alliance (CDA), a collaboration of banks that work with law enforcement to tackle cybercrime and financial crime through intelligence sharing. Duality partnered with the CDA to implement a proof-of-concept of a privacy-enhanced inter-bank information sharing system. The pilot established that current manual processes could be automated while fully complying with data privacy regulations – a paradigm shift in the ability to enhance the fight against financial crime.
“Our cooperation with Duality to look at innovative technical solutions to cross-industry analysis of data was extremely promising,” said Steven Wilson, CEO of the Cyber Defense Alliance. “We plan to scale this approach to examine much larger data sets. This technology has the potential to address many of the challenges that exist when analyzing the huge sensitive data sets involved in the investigation of complex global cyber and financial crime cases, whilst still complying with data privacy regulations.”
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