With a distinguished career in finance and banking, Priya Jaiswal is at the forefront of integrating cutting-edge technology into traditional banking frameworks. As a key architect behind the new partnership between Fifth Third Bank and Brex, she is reshaping how businesses manage their finances. This conversation explores the strategic decisions driving this collaboration, focusing on the shift away from legacy systems toward an AI-native infrastructure. We will delve into how this technology provides a competitive advantage by automating complex financial workflows, the metrics used to gauge its success, and the deliberate, phased approach to its market launch.
The article mentions your corporate card program was previously operated in-house. What specific pain points with that system prompted the switch to Brex’s AI-native platform, and what does the step-by-step transition process for your existing business clients look like during this pilot phase?
Our in-house system, while reliable, was a product of a different era. Our clients were spending an immense amount of time buried in manual work—reconciling statements, chasing down receipts, and wrestling with spreadsheets just to close the books. We heard loud and clear that they wanted to focus on strategy, not administrative tasks. That was the core pain point. The switch to Brex was driven by the need to give them intelligent tools that automate that grind. For our pilot clients, the transition is very hands-on. We start with deep discovery sessions to understand their existing workflows, then we map out the integration, and finally, we onboard their teams with dedicated support to ensure it’s a seamless experience from the very first transaction.
You described your “special sauce” as AI embedded in your core infrastructure, not “bolted on.” Could you walk us through how this AI-native approach specifically automates the month-end close for a client and how that provides a tangible edge over established tools like Amex and Concur?
That “special sauce” is everything. Think of it this way: many legacy systems, like Amex or Concur, are built on older payment rails and then have an AI or software layer placed on top. It’s an addition, not the foundation. We, along with Brex, built the system with AI at its core from the beginning. So, when an employee makes a purchase, a series of AI agents immediately gets to work. One agent captures the receipt from their email, another matches it to the transaction, a third checks it against company spend policy, and a fourth can even automate the approval workflow. This end-to-end automation means that by the end of the month, 90% of the work is already done in real-time. That’s a world away from the traditional model of collecting a month’s worth of data and then trying to make sense of it all at once.
You aim to “redefine expectations” with “real-time visibility and control.” Beyond speed, what specific metrics are you using to measure this improvement for clients, and could you share a brief anecdote from the pilot program that illustrates how this has been a “game-changer” for a business?
“Real-time” is more than a buzzword for us; it’s a measurable outcome. We’re tracking metrics like the reduction in hours spent on month-end close, the percentage of expenses that are automatically categorized and reconciled without human touch, and the time it takes to issue a new virtual card for a specific vendor. I was speaking with a CFO in our pilot program just last week. She told me she used to find out about departmental budget overages three weeks into the next month. With our new dashboard, she saw a marketing campaign was trending over budget on a Tuesday morning, implemented a dynamic spend control with a few clicks, and brought it back in line by the afternoon. She called that level of agility a “game-changer” because it allows her to manage the business proactively instead of just reporting on what already happened.
This partnership is launching in a pilot stage in one regional market and two card verticals. What criteria went into selecting that initial market and those specific verticals, and what are the key milestones you must achieve before expanding across all commercial banking segments next year?
Our selection process was very deliberate. We chose a regional market that represents a diverse cross-section of our commercial client base, from mid-sized manufacturers to fast-growing tech firms. The two card verticals were selected because they have notoriously complex expense management needs, making them the perfect stress test for the platform’s capabilities. Before we go broad next year, we have several key milestones. First is achieving an overwhelmingly positive client feedback score on the platform’s ease of use. Second, we need to see our target metrics for automation—like receipt-matching accuracy and time-to-close—hit our internal benchmarks. Finally, we need to ensure the technical integration is flawless and can handle the massive scale of our full commercial banking segment.
Bridgit Chayt noted a goal of creating a “seamless experience from Day One.” Can you describe the step-by-step process your teams used to integrate the Brex Embedded platform with Fifth Third’s existing systems, and what specific client feedback from the pilot has been most valuable?
Creating that seamless experience required deep collaboration between our teams and Brex’s engineers. The process started with mapping every single client touchpoint, from logging in to running a report. We then used Brex’s embedded platform APIs to deeply integrate their functionality into our own banking portal, so for the client, it doesn’t feel like they’re using a separate product. It just feels like a powerful new part of their Fifth Third relationship. The most valuable feedback has been in the small details. For instance, an early user pointed out that the process for assigning a virtual card to a specific project could be streamlined. We took that feedback, worked with Brex, and rolled out a revised workflow within two weeks. That iterative, client-driven approach is what truly makes the experience seamless.
What is your forecast for the future of AI in corporate banking?
I believe we are at the very beginning of a fundamental transformation. Today, we’re talking about AI automating expense reports, which is fantastic, but it’s just the tip of the iceberg. In the next five to ten years, I forecast that AI will become the central nervous system for corporate finance. It won’t just report on past spending; it will provide predictive cash flow forecasting, automate complex treasury management decisions, and detect sophisticated fraud patterns in real-time. The role of a corporate banker will shift from being a processor of transactions to a strategic advisor, armed with AI-driven insights to help businesses operate smarter and scale faster than ever before. Banking will become less reactive and far more proactive and intelligent.
