Notes from the desk: Welcome to this month’s Quarterly Review, a series where I dive into what executives from some of the best brands in financial services are focusing on in this quarter, as well as how they are planning to achieve their goals. It’s a chance for the industry to learn about what goes on behind an FI’s four walls and how leadership manages their priorities.
Unlike news, strategic planning in the offices of some of the most important players in the market is never slow. It’s this planning that this series taps into, much more to come, stay tuned.
In this edition, we will check back in with Wise’s Commercial Director for Wise Platform (Americas), Lauren Langbridge.
Executive Summary
How much can an executive at a big fintech achieve in 4 months?
Wise’s Lauren Langbridge’s answer is this: 2 domestic network expansions with significant strides towards a third and a fourth, one new partnership and the expansion of another, and organizing a dedicated conference for clients like senior payment leaders, as well as key stakeholders like business owners and policy makers.
For Wise, Langbridge’s achievements yield direct business value:
Direct Pix (Brazil) and Zengin (Japan) connections significantly increase Wise’s global capabilities
Wealthsimple and IBKR partnerships expand platform reach across retail and business segments
Industry appearances and engagements, as well as talent acquisition, allow Wise to scale resiliently
The Full Review
Our review articles in this series are an exclusive offering for our TS PRO subscribers. If you want to dive into the juicy stuff and read the details of their labors and fruits —beyond the executive summary below— please consider upgrading your subscription.
Notes from the desk:Welcome to this month’s Quarterly Review and a new year! The Quarterly Review is one of the only media pieces that allow readers to track improvements through time. It’s a chance for the industry to learn about what goes on behind an FI’s four walls and how leadership manages their priorities. And a review mandates a check-in, as I like to say, so enjoy reading about how the exec in the hot seat today overcame challenges, and brought her vision to life.
In this edition we focus on Jeff Pomeroy, SVP, Payments, Services, & Platforms at PayPal.
Executive Summary
Enterprise payments are the engine behind modern commerce. As businesses scale globally, they need payment infrastructure that can keep pace with complexity, volume, and ever-changing merchant demands. PayPal, one of the most recognizable names in payments, is doubling down on its enterprise capabilities to serve the world’s largest merchants.
In today’s story, the spotlight is on a PayPal executive with three decades of payments experience, who shares how the company is unifying its B2B platform across markets, forging partnerships to bring enterprise-grade payments into physical retail, and building value-added services.
The Full Review
[Pomeroy]: When I joined PayPal in 2024, I stepped into a challenge that felt both familiar and fresh. After three decades in payments – from the early days of developing the first consumer e-commerce services in the 90s, to processing payments at scale at Blackhawk, to building issuing and leading the North American product team at Adyen, and creating a brand-new unified cloud-based platform at Fiserv – I knew the opportunity this time was about harnessing PayPal’s tremendous assets and momentum to bring our enterprise payment and service capabilities to full global scale.
PayPal Enterprise Payments (the artist formerly known as Braintree) sits at the center of that effort. We already had incredible technology, deep merchant relationships, and a trusted global brand when I came on board.
The Full Review
Our review articles in this series are an exclusive offering for our TS PRO subscribers. If you want to dive into the juicy stuff and read the details of their labors and fruits —beyond the executive summary below— please consider upgrading your subscription.
Notes from the desk:Welcome to this month’s Quarterly Review and a new year! The Quarterly Review is one of the only media pieces that allow readers to track improvements through time. It’s a chance for the industry to learn about what goes on behind an FI’s four walls and how leadership manages their priorities. And a review mandates a check-in, as I like to say, so enjoy reading about how the exec in the hot seat today overcame challenges, and brought her vision to life.
In this edition, we will check back in with Miki Van Cleave, Chief Design Officer at Chase.
Executive Summary
When we last spoke to Chase’s Chief Design Officer, Miki Van Cleave, she had been in the role for only seven months and she had big process-related plans. It seemed fair to allow her plans to bloom before we put her back in The Quarterly Review hot seat and in 2025. Her aim for the past few quarters was to improve the discovery processes to build better alignment between design decisions and customer needs, and improve her team’s presence across other departments.
“I stepped into the role of Chief Design Officer in August 2024 generally aware of the journey the organization had been on because I had been on the leadership team since 2020. But in 2025, we took everything up a notch,” she said looking back at her year in the new role.
Here is what Van Cleave accomplished:
Strengthened cross-functional collaboration through “the Quad” model, driving measurable results like a 39% conversion boost and 24% reduction in no-shows on key redesigns.
Refined the discovery process with the “Customer Why Template”, creating consistent workflows that reduced costly pivots and led to a 10% drop in customer complaints.
The Full Review
Our review articles in this series are an exclusive offering for our TS PRO subscribers. If you want to dive into the juicy stuff and read the details of their labors and fruits —beyond the executive summary below— please consider upgrading your subscription.
Notes from the desk:Hello and welcome to another review edition of The Quarterly Review, where I dive into what executives from some of the best brands in financial services are focusing on in this quarter. In the review edition, we compare the exec’s goals with results and see how well his plans stood the test of time.
Our review articles in this series are an exclusive offering for our TS PRO subscribers. If you want to dive into the juicy stuff and read the details of their labors and fruits —beyond the executive summary below— please consider upgrading your subscription.
In this edition, we will check back in with Tom Bianco, General Manager at Newline by Fifth Third.
Executive Summary
Newline by Fifth Third plays a very important role in positioning the traditional bank at the top of the innovation and BaaS sophistication pyramid. My conversation in April with the GM of Newline by Fifth Third, Tom Bianco, revealed that the exec was intent on doubling down on this potential – through a three-pronged strategy that centered on improving products and program experiences, and building better brand awareness.
Here is how his goals panned out:
Launched 3 AI-powered features that enhance developer efficiency, including conversational search, auto-synced documentation, and embedded AI assistance.
Rolled out 5 dashboard enhancements that give clients better transaction visibility, testing capabilities, and direct access to support teams.
Leveraged the experience of technical leaders and a Sandbox environment to showcase Newline’s capabilities.
The Full Review
Our review articles in this series are an exclusive offering for our TS PRO subscribers. If you want to dive into the juicy stuff and read the details of their labors and fruits —beyond the executive summary below— please consider upgrading your subscription.
In this edition, we will check back in with Tom Bianco, General Manager at Newline by Fifth Third.
Executive Summary
Newline by Fifth Third plays a very important role in positioning the traditional bank at the top of the innovation and BaaS sophistication pyramid. My conversation in April with the GM of Newline by Fifth Third, Tom Bianco, revealed that the exec was intent on doubling down on this potential – through a three-pronged strategy that centered on improving products and program experiences, and building better brand awareness.
Here is how his goals panned out:
Launched 3 AI-powered features that enhance developer efficiency, including conversational search, auto-synced documentation, and embedded AI assistance.
Rolled out 5 dashboard enhancements that give clients better transaction visibility, testing capabilities, and direct access to support teams.
Leveraged the experience of technical leaders and a Sandbox environment to showcase Newline’s capabilities.
Notes from the desk:Welcome to this month’s Quarterly Review, a series where I dive into what executives from some of the best brands in financial services are focusing on in this quarter, as well as how they are planning to achieve their goals. It’s a chance for the industry to learn about what goes on behind an FI’s four walls and how leadership manages their priorities.
It seems like only yesterday I was trying to figure out how a series like this could work from a financial services journalism point of view. But its already been more than year since The Quarterly Review launched and we have had some really powerful voices join us on the chair. Executives from fintechs like Acorns, Current, Public, and Zelle, as well as leaders from banks like JPMC, Citizens, Laurel Road, and Fifth Third have joined us on the hot seat to share stories of growth, challenges, and resilience.
In this edition we will check back in with Zelle’s GM, Denise Leonhard.
Improve product reliability, UX, and features to meet the financial needs of more consumers and SMBs.
Seven months later, Leonhard is back to report that Zelle has successfully moved past the $1 trillion mark while significantly growing its partner network and customer base along the way.
Banking digital assistants may be common now, but in 2017, Bank of America was one of the first to be thinking about how they make the firm’s customer experience more powerful. The answer was an in-house build of a digital assistant that required the firm to hire PhDs in linguistics and build a collaboration structure that could facilitate teams from different departments.
In 2024, BofA clients interacted with Erica 676 million times bringing its total interactions since its launch in 2018 to 2.5 billion.
On the show today, Hari Gopalkrishnan, who leads Bank of America’s Consumer, Business & Wealth Management Technology team, joins us to tell the tale of how the firm built its industry-leading digital assistant, Erica.
Hari shares how the firm has gradually expanded Erica’s remit beyond consumer banking to also include multiple lines of business and individual and corporate clients across the firm’s global footprint.
It’s a dive into what it takes to push the boundaries in this industry, how the firm thought about development, testing, expansion, and how Erica’s capabilities can be expanded with the recent innovations of Gen AI.
CX as the impetus behind Bank of America’s investment into building Erica
Back in 2017, Hari Gopalkrishnan’s team realized that despite the expanding remit of the BofA app, customers were still flocking to traditional channels like banks and call centers before they tried self-serving. A dissection of this behavior served as the catalyst for the Erica build.
“We were putting tons and tons of features into our app, a five inch screen, and our customers were still walking into the branch, calling into the call center … It’s hunting and pecking, and it was hard to navigate once you put more than 10 or 15 key features. And so our first insight was, you want to be able to have your customers interact with a platform in a way they choose, not the way you choose,” said Hari.
Why Bank of America decided on a DIY approach to build Erica
Although the industry is pretty well-versed in building, deploying, and improving chatbots now, the landscape was quite different in 2017, when BofA had first thought of developing Erica. There was no blueprint for what a banking digital assistant looked like and technology providers were few and far between. The slim pickings in the marketplace, as well as the limited applicability most software had in the financial services, fueled an internal build.
“There were a bunch of startups that were coming out, we spent a few weeks with them and either they disappeared or were going to get gobbled up. So it was a very volatile marketplace for acquiring software that did this. People were trying to play in this game, but weren’t quite getting it. The ones that understood some level of NLU (Natural Language Understanding) didn’t understand financial ontology,” he said.
“We did an assessment, and we looked at third parties, like we always do, but at the end of the day, it just wasn’t going to work out. At the same time, we found a couple of really good open source NLP engines. They were strong, solid, and very well regarded in the industry. We actually hired up a team. We always had good technical engineers. But we also actually hired people with PhDs in linguistics to work on this. Then we started to work with our teams to figure out: what is the digital experience going to look like?”.
How Bank of America structured teams across the org to build Erica
Building Erica required BofA to think across organizational silos, and really invest into creating a collaboration framework that would allow Erica to improve CX without compromising on risk tolerance.
“We actually took the Agile construct to the next level. We had teams set up in [different] regions which were actually in the room. It was the engineering team, the UX team, the appropriate legal team, all opining day in, day out, on all aspects of the platform. The sprints were not just engineers running off and UX coming in weeks later. It had UX teams embedded. In fact, when I used to visit the teams, it was sometimes hard to tell who was in the design team and who was in the engineering team. That was actually the power of how this came together,” Hari shared.
The fork in the road: User testing proved presumptions wrong
Designers and developers have a conceptual map of the software they are building and they also spend time trying to understand their users’ behaviors and pain points. But there is no silver bullet for getting everything right, right off the bat. Hari shares how testing motivated a major pivot in Erica before it launched.
“We thought we would have to invest just as much in voice as in text -– that people would half the time talk into the app, and half the time they would type into the app. Then we go to a small group of customers, and we get more feedback from this. And the feedback we got there was people were just typing in text 90% of the time. They were rarely using voice.”
Gen AI potentialities for Erica
Bank of America is not sleeping on Gen AI – it’s just chosen to stay quieter than most. “As we look at the emergence of Generative AI, we actually see that classification can actually get a lot better. You can actually talk even more naturally in a natural language. So that is just a natural sort of expansion of where we go with Erica. We have about 25 different proof of concepts right now, many of them are actually about to get into production, which use a Large Language Model in some way, shape or form, to continue to enhance the work that we’ve been doing,”.
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The following excerpts were edited for clarity
BofA’s blueprint for Erica’s expansion into multiple lines of business
Some of it actually is using fit for purpose language models that are pre-trained on certain things. So, for example, for employees there are available technologies that actually are trained on things like integration into your HR system and integrating into your help desk system. We don’t want to go build a whole bunch of things that actually have been built by somebody before.
The reason we built what we built is because nobody was building that before. When it came to employees, we realized that we can leverage all the goodness we have on NLU (Natural Language Understanding) and User Experience. We also found that there are available models that actually do a really good job of NLU to service intent and to calling of existing HR platforms.
We had to figure out case by case, do we start a native build? Do we integrate with existing models when it comes to Erica for business banking there? We had to go to a different set of data sources. You had to make sure those sources were clean. You had to make sure, in some cases, that there was an API available to make that interaction happen … in some cases, many of the services in the past may have been built for a specific User Experience or a specific application, we had to make sure that they get rebuilt or reimagined to be invoked by a chat bot, because sometimes you may need clarifying steps. You may have a multi-step process before you actually call an interaction. That also helped us become better in our core platforms, because that helps us now be ready for the future.
How BofA is balancing ROI, risk, and innovation when it comes to Gen AI
We have an AI Council. Even though we’re obviously a very large company, we try to work in a very integrated fashion and look to learn from everything that’s going on across the company. There are lots of parts of this company, and we come together. You could say it slows us down, but we’re okay with that. We ask, what are the pilots and POCs you want to run? And why do we want to run those POCs and pilots? The people involved in that council involve senior business leaders, senior strategy leaders, senior risk leaders. We’re asking, does this thing align with our risk framework? We have a risk framework that has 16 points of risk. You can imagine bias, intellectual property, transparency, and explainability, in there.
Is the work you’re going to do, going to abide by those risk frameworks? Is there an adequate human in the loop so that you can make sure that the thing doesn’t run away? How do you measure the performance? What guardrails are you going to implement? Those are the things we look at as we implement any of these proof of concepts and eventually take them to commercial use.
The second part is we also look at, what is the mindset you have on the ROI generation of doing this work, because none of this stuff is cheap. This is something everybody is wrestling with. There’s so much hype out there that people are throwing out, I’m going to spend a billion dollars. I’m going to spend $5 billion and when you ask the question, tell me what your bottom line is going to be, what are you going to get in return? The answers are a little bit more diffused.
So we’re taking an approach of saying, we want to understand how work gets done. We want to understand activities, jobs, tasks. We want to understand what part of those tasks cost, what money. And then, when you implement solutions like this, what’s the ROI?
