Whitney McDonald 16:44:01
Hello and welcome to the FinAI podcast, presented by FinAI News. Today is august 27, 2026. My name is Whitney McDonald, and I’m the editor of FinAI News. The FinAI podcast covers current trends and intriguing topics on AI application and beyond, making it your definitive source for insights and news surrounding AI and financial services. Joining the podcast is Michelle Conklin, head of receivables and public sector product and operations for J.P. Morgan Payments. Thanks for being here, Michelle.

Michelle Conklin 16:44:28
Of course, sounds good. Thanks, Whitney, for for having me on. So, Michelle Conklin worked at J.P. Morgan Chase, and I’ve been here for the last 22 years. I currently am the global head of our receivables and public sector business, which includes the operational component, but also the product commercialization, go-to-market strategy. The receivable space has been quite the interesting business over the last, you know, 10-15 years. Significant changes, but at the same time, a lot hasn’t changed. It’s been a really, really interesting journey to see this business evolve, our employees evolve, myself evolve. Make sure that we’re really relevant in this space. That’s a little bit about me and my role.

Whitney McDonald 16:45:08
Thank you. Why don’t we go a little bit a little bit further here into J.P. Morgan Payments itself? Tell me about kind of where you sit within the J.P. Morgan umbrella. Tell me about the the payments operations,

Michelle Conklin 16:45:20
J.P. Morgan. You know, payments. The way that I look at it is, it’s really at the center of the global economy. Every single day, we move nearly $12 trillion in payments. We span across more than 160 countries, 120 currencies, and all of that ultimately results in processing over 5000 transactions per second, and frankly, most of our agenda topics and our investments and the way that we look at technology and our enhancements or new product delivery-it’s-it’s most often focused on how do we remove friction from the payment ecosystem because not every single client is created equal from a scale, complexity, sophistication, and so that’s really where we find ourselves as sitting in the center of that global economy, being you know the client’s primary rail of moving money. It is really an interesting space, and if I think about you know the common themes right now, there’s a tremendous focus on real-time payments, digital wallets, emerging technologies, and many businesses and governments. However, still rely on processes that generate paper. There’s a ton of paper in the industry, which includes remittance information. And if you think about a payment, a payment is a payment, right? It’s moving money, whether it’s paper, it’s electronic. But in the receivables business specifically, there is a strong focus and need to take information and data that is on remittance documents and be able to capture it, validate it, and reconcile. And in this space specifically, in 2025, J.P. Morgan moved more than 130 million checks within the payments ecosystem, and so every single one of those payments comes with information that has to be again matched, validated, and applied correctly. And so my team really leads the receivables and public sector business. We sit under the payments umbrella, specifically within Treasury Services, and so our ultimate and kind of simplified goal is to focus on helping organizations collect, process, and reconcile incoming payments as efficiently as possible. We work with some of the largest corporations, healthcare providers, universities, government agencies across the entire country, with a simple goal of helping them manage everything from consumer payments to tax collections and government receivables, and at the end of the day, our job-you know-I oversimplify a lot of things, but it is actually pretty simple. Where our goal is to help clients get paid faster, better information, and less operational friction. And that’s really one of the reasons why AI has become such an important area of focus for us. It really gives us the ability to rethink longstanding processes that have been around for a very long time, with the goal of eliminating again the word friction is super important in various parts of the payment life cycle that have historically been very very manual. So that’s a little bit about payments and where we fit into the organization.

Whitney McDonald 16:48:24
No, that’s really helpful. Thanks for breaking all of that down. I want to kind of dive in a little bit here about what you mentioned about how you innovate around eliminating or removing friction where you can. You also mentioned a payments a payment. You know, at the end of the day, everybody wants to get paid and make sure that their payment is getting from point A to point b1. process I wanted to dive into, and obviously AI, I am sure, is a big part of this, but is the use of of artificial intelligence to digitize check and remittance processes. This is something that you guys are working on. Obviously, a lot of institutions and organization are looking to AI to remove friction across a lot of processes and applications. But let’s talk about AI within that check digitization and remittance process.

Michelle Conklin 16:49:12
Yeah, absolutely. And you know, to your point, there’s literally not a single conversation a day that goes by without the mention of AI, and you know, I think the kind of overall approach is you know AI is this sometimes scary, sometimes you know really powerful tool. But for us, the the place that is important to start is that we did not look at AI as a project for a specific use case, right? That tends to kind of derail the embedding of AI into your processes. Instead, for us, we had a business problem that we were looking for a better solution, and that’s where AI came in. For J.P. Morgan in the receivables business, we have been helping clients for years, right, to process checks and remittance information through our lockbox business. And while the again the payment itself is really relatively straightforward, the workflow surrounding the payment has traditionally been very very manual. Someone has to physically receive the mail. They have to open up the envelopes, extract documents, capture information, validate data, and resolve exceptions. And this is, you know, a massive, manually intensive process that has multiple, multiple steps throughout, where there are some inefficiencies and there are some friction points just based on the nature of the business. And when you operate at the scale that we do, even the smallest inefficiencies become significant. So several years ago, we began down the modernization journey to create a brand new platform from the ground up. That was really important to us because that gave us the opportunity to rethink the process end to end, rather than simply improving individual tasks. So initially, when we started the platform rebuild, we introduced AI into core activities, right? Things that we knew AI would be really, really good at, such as data extraction, validation, and then since then, we’ve actually expanded into the robotics and document intelligence space, where we now have mail automation robots that are capable of handling more than 4000 different envelope and document permutations. When we heard that number, once we did the proof of concept and testing with our robots, 4000 different envelopes and document permutations is just-it’s a crazy number, which then lends itself to why this has historically been a very complex, manually intensive business. And so, with robotics coupled with AI, that has been helping us automate work that historically has required significant manual effort. One last thing that I’ll say about AI is it’s what excites me the most is not necessarily the technology itself, but it’s ultimately the impact. We are transforming a highly intensive paper process into a more digital, efficient, and scalable experience for both our clients, but also equally for our employees, which is a critical component to the success of our business.

Whitney McDonald 16:52:24
Maybe we can talk a little bit here about you know what does this mean for you know the human employees that maybe used to handle some of these processes. How does this free up you know manual labor and kind of where can you redeploy those resources.

Michelle Conklin 16:52:40
We’ve really improved their employee experience. So where you look at a traditional receivables, paper-intensive role, our employees are now able to transition from spending time on repetitive data entry and manual reviews of transactions and remittances and checks. Now our teams have greater visibility into the items that truly require a human-in-the-loop experience. They now have visibility into exceptions, operational performance. They can really focus on oversight, problem-solving, client support, and that’s really where the human expertise creates the most value, and frankly, like just does not go away. You can have the best models, you can have the best workflows, you can have the best technology and equipment, but you still need that human expertise because, frankly, no system, no AI model is ever going to be able to sell for 100% of the 4000 permutations of what we see on a day-to-day basis. We’ve also achieved really, really impressive processing accuracy rates of 99.999. So those three nines after the point are actually really important because if you look at the scale at which we process, right, around 130 million checks. Annually, those percentages matter, and really, the clients depend on accurate receivables information to manage cash flow, to reconcile their transactions, and frankly, run their business. Receivables funds ultimately run and are critical to a client’s working capital, critical to making payroll, critical to supporting you know small businesses, hospitals, you know every single type of company or corporation that you can think of. Accuracy is critical because if a client receives a payment but they don’t know how to apply that payment, who to apply that payment, and or for what goods and services were rendered, that payment kind of becomes irrelevant, and frankly, creates more friction. So, if you think about, you know, the overall ultimate success is that, you know, for us, it’s changing the client experience, but also the employee experience, where they now have much more intuitive systems. Right, there are incremental validations and quality controls, so that ultimately not only does the process become faster, it also becomes more accurate. More information is a better experience for both our clients and the and the employee, and that’s really where AI is helping us to deliver on those key initiatives.

Whitney McDonald 16:55:18
Now, I want to kind of bring it back to what you were talking about at the top of the call regarding you know identifying areas of friction. How can we make payments process processes easier? Obviously, employee feedback. Obviously, coming from client feedback. But touching on this AI point here, how do you determine where artificial intelligence is a good fit, where to innovate, what are those areas of friction that you do grab onto and say, you know what, we need to innovate around this and and lean into AI.

Michelle Conklin 16:55:48
One of the challenges I think some companies are facing is, you know, they because AI has so much hype and has so much potential and is you know so incredibly impressive in terms of its results. We look at areas that already have a need, right? A need for some sort of automation, a process that is disjointed, and that’s really where we look to see what solutions do we have, as opposed to bringing a solution to a potential problem that doesn’t exist. It goes back to again that word friction. Where in any payment life cycle or any process is there friction that can be resolved or even eased with AI and with you know any type of technology? Nobody builds a platform or a system with AI just because. Like you have to think about what problem are you trying to solve, and then that really helps determine what type of AI solution. Are you looking at different models, you know, talking to each other? Are you looking to take out the maker checker and just have the final exceptions be a human, and have the maker checker be AI? Right. Those are all the things that we have explored, embedded, and operationalized, and again, it’s looking at where do you have friction points, and that’s where you look for the solution.

Whitney McDonald 16:57:08
Is there anything that I did not ask you about that you wanted to be sure to touch on? One

Michelle Conklin 16:57:14
of the kind of turning points in this entire evolution and our journey to you know automate, streamline, and reduce some of the friction was during the pandemic, right? So during the pandemic, we were considered the receivables business was an essential service. We didn’t have the ability to reroute mail to our employees’ homes. It just doesn’t work that way. We needed all of our employees to show up, and that you know really resonated with us. Where are there tasks that are being done physically that can be performed digitally, right? Or that we can do from a variety of different locations that don’t require somebody to be sitting there and reviewing a check, and that really started to generate the thought process is how do we remove the the physical nature and the physical reliance on people being in the office and create more digital workflows. That’s really what kind of even accelerated this entire initiative further is thinking about you know the next pandemic or the next geopolitical event that you know shuts down a city; those are just natural part of business. And every single disruption in the you know United States, or frankly, world has the ability to impact us. And so, how do we get people to have more digital capabilities, make those decisions instead of doing it upfront while holding a check in the office?

Whitney McDonald 16:58:40
You’ve been listening to the FinAI podcast, presented by FinAI News. Please follow us on X and LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Be sure to visit us at finiews.com for more AI news. Thanks for listening.

Transcribed by https://otter.ai