Quantexa debuts Q Assist with early adopters HSBC and BNY Mellon

At London Tech Week 2024, Quantexa, the AI, data and analytics software company, introduced Q Assist, a generative AI technology suite designed to improve decision-making across various sectors. This announcement highlights Quantexa’s progress in platform innovation and follows a substantial investment in the global AI industry.

The Q Assist Technology Suite allows Quantexa customers to operationalise generative AI without needing significant infrastructure investments. Frontline and information workers can leverage copilot features, linked data, and Quantexa’s knowledge graph capabilities to improve the accuracy and reliability of AI models that interact with both structured and unstructured data.

HSBC is among the participants in the Lighthouse Program for early adopters. The program envisions using Q Assist to:

• Streamline analysis, investigation, and reporting tasks for greater efficiency.
• Reduce dependence on data science teams for ad-hoc data requests.
• Empower customer-facing teams with enriched data to enhance revenue and customer experiences.
• Enable consistent, trusted decision-making and accelerate operational improvements.

BNY Mellon is also evaluating joining HSBC in the Lighthouse effort. Quantexa’s collaboration with these early adopters has projected significant productivity gains within one, three, and five years, particularly in time-saving, new opportunity identification, and increased conversion rates. HSBC expects that democratizing analytics and accelerating processes will lead to productivity gains within the first year.

David Rice, Global Chief Operating Officer, 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.”

Quantexa estimates that a tier one global financial institution with three levels of defence in financial crime and fraud compliance, generating approximately 15k alerts a month, could achieve over £17M in annual savings by enhancing and automating investigative and reporting processes.

Jamie Hutton, Quantexa’s CTO, remarked, “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. Through the company’s Lighthouse Program for early adopters, we have the benefit of working with industry leaders that provide valuable feedback throughout our roadmap process.”

Eric Hirschhorn, Chief Data Officer, BNY Mellon, added, “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.”

How Q Assist works

Quantexa’s new generative AI technology suite will combine Quantexa’s Decision Intelligence Platform and Generative AI through a new data integration layer, prompt builder, and copilot that accelerates the ability of teams to make critical business decisions.

 This lets non-technical teams benefit from Quantexa’s critical platform capabilities including a connected data foundation, graph analytics, modeling, and scoring to augment and automate decision making.

The Q Assist Technology Suite comprises three main components:

• Q Assist Integration Layer: A framework of tools, connectors, and APIs to securely link Quantexa’s Decision Intelligence Platform with LLMs and conversational AI systems.
• Q Assist Prompt Builder: A prompt management and sharing capability that integrates with external tools such as Microsoft’s Azure Prompt Flow, allowing administrators to define and control prompts and responses grounded in contextual data.
• Q Assist Copilot: Enables users to query large, disparate data sets via a natural language interface, summarising data and findings in real-time, and automating research, investigation, and reporting tasks.

Q Assist’s capabilities are currently available to a limited set of customers, with broader public availability planned for early 2025.

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