HSBC and BNY Mellon are participating in the early adopter program for Quantexa’s Q Assist, a context-aware generative AI technology suite.
Quantexa positions itself as an AI, data, and analytics software company focused on “decision intelligence,” assisting organizations in making operational decisions based on data. The company states that its new Q Assist suite enables customers to operationalize generative AI without the need for extensive investments in infrastructure, tools, or skilled resources.
Quantexa’s range of tools allows frontline and information workers to enhance the accuracy and reliability of generative AI models. These models interact with both structured and unstructured data, utilizing context and insights from across the organization. By integrating large language models (LLMs) with the contextual data provided by Quantexa’s platform, users can gain a clearer understanding of their data. This results in improved performance, trust, and access to the most accurate and up-to-date information within a single interface.
HSBC and BNY Mellon intend to leverage this technology to streamline analysis, investigation, and reporting tasks, diminish the dependence on data science teams for ad-hoc requests, and empower customer-facing teams with enriched data. David Rice, global COO of commercial banking at HSBC, commented, “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 approximates that a tier-one global financial institution, with a three-tier defense system against financial crime and fraud compliance, generating around 15,000 alerts per month, could save over £17 million annually by utilizing this technology for investigations and reporting processes related to financial crime and fraud.