Quantexa Debuts new Gen AI suite with HSBC, BNYM
Technology leader in decision intelligence (DI) solutions for public and private sectors, Quantexa, has announced the launch of Q Assist, a context-aware generative AI (Gen AI) suite designed to help organisations augment decision-making across front-line and information workers.
The introduction of this new suite highlights progress against Quantexa’s platform innovation roadmap and comes a year after Quantexa previewed Q Assist as a stand-alone LLM agnostic pilot.
Now ready for deployment, Quantexa customers will be able to operationalise Gen AI for transformative gains, without additional investment in infrastructure, tooling and any additional skilled resources.
A boost for Q Assist early adopters: HSBC & BNYM
An early adopter of Q Assist, HSBC has been supporting Quantexa on the development of its Gen AI suite by signing up for its Lighthouse programme, and granting early access to Q Assist.
US banking giant, Bank of New York Mellon (BNYM), is close to joining HSBC in the Lighthouse programme.
Eric Hirschhorn, Chief Data Officer, BNY Mellon, says: “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.”
Now, frontline and information workers at HSBC (and soon BNYM) will be able to leverage co-pilots, linked data and Quantexa’s knowledge graph capability, alongside a string of other DI platform features to help improve the accuracy and reliability of Gen AI models that interact with both structured and unstructured data. This will help them provide additional organisation-wide insights.
HSBC workers can combine large language models (LLMs) with the rich context of Quatexa’s DI platform to enable a better understanding of data, safely ground responses, increase performance and trust, ensuring teams have the most accurate, up-to-date information in a single place.
- Streamlining analysis, investigation, and reporting tasks for information and knowledge workers to achieve greater efficiency.
- Reducing the reliance on data science and operations teams for ad-hoc data requests, giving them time to focus on more strategic tasks.
- Empowering customer facing teams with access to enriched data and insights they need to increase revenue and enhance customer experiences.
- Enabling teams across an organization to consistently make trusted decisions that are traceable and accelerate operational process improvement.
David Rice, Global Chief Operating Officer, Commercial Banking at 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.”
HSBC expects that democratising analytics and speeding up processes in these areas could result in productivity improvements within the first year of implementation.
Additionally, the bank anticipates that this will free up employees' time, enabling them to concentrate on other strategic tasks.
HSBC's partnership with Quantexa comes after its recently published report examining how emerging tech, including AI, robotics and quantum computing will shape the next decade of financial services.
Quantexa’s CTO, Jamie Hutton, adds: “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.”
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