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HSBC & BNY Mellon to pilot Quantexa's new AI technology

Tue, 11th Jun 2024

Global experts in the banking industry, HSBC and Bank of New York Mellon (BNYM), are among the organisations participating in Quantexa’s Lighthouse Programme to deploy the company’s new context-aware generative AI technology suite, Q Assist. The debut of Q Assist at London Tech Week marks significant progress in the application of advanced AI tools in the financial sector.

Quantexa's recent unveiling of Q Assist arrives nearly a year after the firm announced a major investment exceeding US$200 million in the global artificial intelligence industry. The AI suite aims to enhance trusted decision-making processes across various teams, including customer service, sales, and compliance within financial services, technology, media, telecom (TMT), and government agencies.

The new Q Assist suite allows organisations to operationalise generative AI with minimal need for substantial infrastructure investment or additional skilled resources. It integrates Quantexa’s Decision Intelligence Platform with generative AI to provide more precise and reliable data interactions across all data types within an organisation.

Leveraging LLMs (Large Language Models) with Quantexa’s Decision Intelligence Platform, Q Assist enhances the understanding of data by grounding responses in the rich context provided by Quantexa's knowledge graph. This offers team members an accurate and up-to-date amalgamation of structured and unstructured data, ultimately improving performance and trust in decision-making processes.

HSBC, a key participant in Quantexa’s Lighthouse Programme, anticipates that the adoption of Q Assist will yield significant productivity gains within its first year of deployment. By streamlining analytics and investigative processes, the bank expects to reduce its dependency on data science and operations teams for ad-hoc requests, allowing these teams to focus on more strategic initiatives.

David Rice, Global Chief Operating Officer of Commercial Banking at HSBC, stated, “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.”

BNY Mellon is also evaluating participation in the Lighthouse effort. Quantexa collaborated with Programme participants to project benefits over one, three, and five-year periods from deploying Q Assist. Early findings suggest significant productivity gains, particularly in time-saving, efficiency improvements, new opportunity identification, and increased conversion rates.

According to Quantexa, a major financial institution employing Q Assist could realise annual savings of over US$17 million by enhancing and automating financial crime and fraud investigation processes. Jamie Hutton, Chief Technology Officer at Quantexa, commented, “Quantexa’s engineering principle of shaping solutions to deliver maximum customer value has allowed our clients to play an integral role in helping to shape the product requirements for Q Assist.”

Eric Hirschhorn, Chief Data Officer at BNY Mellon, remarked, “We are excited to see this continued innovation from Quantexa. Our multi-year collaboration has helped us to break down data silos and unify our data with unprecedented accuracy. The next phase in our innovation efforts will see us exploring the potential of enabling frontline workers across the bank to use Gen AI to act on the data insights confidently and reach new levels of efficiency in the process.”

The Q Assist suite features three main components: the Integration Layer, Prompt Builder, and Copilot. The Integration Layer acts as the framework for secure linkage between Quantexa’s Decision Intelligence Platform and various LLMs and conversational AI systems. The Prompt Builder allows administrators to define and control prompts and responses based on contextual data. The Copilot facilitates real-time querying and summarisation of large and disparate datasets, aiding in research, investigation, and reporting tasks.

Currently, Q Assist is available to a limited set of customers, with a broader public release planned for early 2025.

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