4 min read

Key takeaways

  • Generative AI can help streamline productivity and increase efficiency for corporate treasurers while enhancing the customer experience.
  • Conversational analytics assistants could hold the power to making complicated data more accessible. And as AI capabilities mature, capabilities like self-driving treasury may also emerge.
  • Security and innovation are key to responsible AI. Our firmwide technology investment, controls and discipline enable us to approach AI capabilities thoughtfully.

Since their introduction to the public in 20221, Generative Artificial Intelligence (GenAI) capabilities continue to evolve rapidly, offering promising opportunities to transform multiple aspects of modern life. The impact GenAI could have on the payments industry, and corporate treasury in particular, is no exception.

For instance:

  • Productivity: Text generation, summarization and knowledge retrieval capabilities could provide reconciliation productivity gains by improving the link between payments and their corresponding invoices. Card dispute responses may also see a boost in productivity by summarizing unstructured responses from merchants and customers.
  • Efficiency: Code generation and revision capabilities may provide the payments ecosystem with a more efficient way to provide developer-ready code for embedding payments in commerce applications.
  • Customer experience: Chatbots and virtual assistants may become more powerful, enabling more effective customer service by allowing deeper-level questioning and real-time responses in plain terms.

A conversational analytics assistant and the corporate treasury experience

With that in mind, J.P. Morgan Payments is pursuing a conversational analytics assistant, a particularly promising GenAI application that could have the power to significantly enhance the corporate treasurer experience by making complicated data more accessible.

As we look to the rapidly approaching horizon, we see how corporate treasurers may soon be able to use plain language prompts to query their data in real-time—empowering them to retrieve information, create custom reports and visualizations, and run more complex analytics—without coding.

With a conversational analytics assistant like this, prompts and questions such as “show me a bar chart that captures how balances across my different accounts have changed over the last 3 months”, “what’s my average quarterly payment frequency to my suppliers” and “show my last quarter’s foreign currency flows organized by currency pairs” have the potential to be answered clearly and in seconds.

And as GenAI capabilities mature, self-driving treasury might also emerge. Not only could GenAI provide insights to corporate treasurers, it could evolve into providing recommendations that can streamline workstreams, save companies time and money and help identify potential human errors or fraud.  As those recommendations become more and more accurate over time, GenAI may reach a point where it can execute on behalf of corporate treasurers within specific parameters they set.

A concept that could quickly become reality

While open banking trends have simplified corporate treasury access to raw payments data significantly over the past decade, leveraging this data for GenAI capabilities usage remains a daunting task for many corporate treasury departments. To better serve our clients’ needs, we have rapidly transformed into a “Fintech that is part of one of the world’s largest banks” says Tony Wimmer, Head of Analytics & Insights for J.P. Morgan Payments.

The team successfully developed a conversational analytics assistant prototype that allows corporate treasurers to interact with their payments data in plain language. The prototype is trained to understand the context of payments and the corporate treasurer workflow, and the ChatGPT-like prototype is an interface connected to payments data. Initial results are highly promising with information retrieval, reporting and analytics workflows taking seconds instead of days. 

To create the best experience for clients, we engaged corporate treasurers to experience the prototype, leveraging our payments expertise and our position as a technology leader to stay on top of ‘the art of the possible’ to help solve real world problems for our clients.

Excited about the potential positive impact on their workflow, clients are particularly interested in how we’re leveraging AI to transform corporate treasury solutions. These solutions could provide greater visibility into accounts and balances in seconds, streamline payments to the same beneficiary to reduce fees, and ultimately give treasurers recommendations that improve processes, amount of time spent and reduce costs.

Keeping security at the core of innovation

With the global scale of a world-class bank and the innovation of a tech company, we have the ability to create software solutions quickly, while our $15B firmwide investment in technology2 helps ensure our innovation meets the standards required to protect the global financial system. And we’re embracing Gen AI a thoughtful way with the controls and discipline you can expect from the world’s largest payments franchise.3

Looking forward

Moving the conversational analytics assistant from a working prototype to a broadly available product solution of the future will take some time. But the opportunities it could offer are worth the wait.

“Our clients’ needs are at the center of all of our software development efforts. We look forward to leveraging GenAI technology to co-develop solutions with our corporate treasury clients.”

At J.P. Morgan Payments, we’re not just keeping an eye on the future. We’re building it. See how we can help you with your needs of today, and join us on the journey to tomorrow.

For more information on our Analytics & Insights solutions, visit: https://www.jpmorgan.com/payments/solutions/analytics-and-insights



JPM proprietary data, based on JPMorgan Chase business structure and internal revenue

*Future capabilities of a GenAI virtual assistant for Cash Flow Intelligence are under development; features and timelines are subject to change at the Bank’s sole discretion.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of
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