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HSBC and BNY Mellon early adopters for Quantexa GenAI suite

HSBC and BNY Mellon are among the early adopter programme participants for Quantexa's Q Assist context aware generative AI technology suite.

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HSBC and BNY Mellon early adopters for Quantexa GenAI suite

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This content has been selected, created and edited by the Finextra editorial team based upon its relevance and interest to our community.

Quantexa describes itself as an AI, data and analytics software company focused on "decision intelligence" that helps organisations make operational decisions with data.

The firm says its new Q Assist suite will help customers operationalise generative AI without significant investment in infrastructure, tooling, and additional skilled resources.

Frontline and information workers can use Quantexa's copilots, linked data and knowledge graph to boost the accuracy and reliability of generative AI models that interact with all structured and unstructured data, context, and insight across their organisation.

By combining LLMs with the context within Quantexa’s platform, users get a better understanding of data and increased performance and trust, as well as the most accurate, up-to-date information in a single place says the company.

HSBC and BNY Mellon will look to use the technology to streamline analysis, investigation and reporting tasks; reduce the reliance of data science teams for ad-hoc requests; and empower customer-facing teams with enriched data.

David Rice, global COO, commercial banking, HSBC, says: “This new solution has the potential to enhance the efficiency and accuracy of complex tasks such as anti-money laundering investigations and sales strategies by providing trusted data and contextual analytics. The introduction of contextual analytics and innovation will enable HSBC to concentrate our resources more productively and ultimately help our customers."

Quantexa claims that a tier one global financial institution with three levels of defence in financial crime and fraud compliance efforts, generating approximately 15k alerts a month, could make over £17 million in savings a year by using the technology for investigating and reporting processes across financial crime and fraud.

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