Quantexa’s Copilot, Linked Data and Knowledge Graph enable frontline and information workers to integrate structured and unstructured data, context and insights from across the organization to increase the accuracy and reliability of generative AI models.
The company says that by integrating large-scale language models (LLMs) and contextual data within Quantexa’s platform, users gain a deeper understanding of their data, improving performance and reliability, and ensuring the most accurate and up-to-date information is available in one place.
HSBC and BNY Mellon plan to leverage the technology to streamline tasks related to analysis, research and reporting, reduce reliance on data science teams for ad-hoc inquiries, and provide enhanced data to customer-facing teams.
David Rice, global COO of HSBC’s commercial banking division, said: “By providing trusted data and contextual analytics, this new solution has the potential to increase the efficiency and accuracy of complex tasks such as anti-money laundering investigations and sales strategies. The introduction of contextual analytics and innovation will enable HSBC to focus resources more productively, ultimately helping its customers.”
Quantexa claims that a top global financial institution, which covers three levels of financial crime and fraud compliance and generates around 15,000 alerts per month, could save more than £17 million per year by using the technology for its financial crime and fraud investigation and reporting processes.
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