Marcus Johnson (00:00):

Big shifts in creators and commerce media are happening right now. EMARKETER is bringing them into focus with two virtual summits, Creator Trends 2026 on February 13th, and Commerce Media Trends 2026 on March 20th. Join the EMARKETER analysts live as they break down new forecasts, emerging formats, and what needs action this year.

(00:28):

Hello, everyone, and welcome to the Banking and Payment Show, an EMARKETER podcast. Today is Tuesday, January 27th, and I'm Marcus Johnson, guest hosting, don't worry, for Rob Rubin. And today, we're talking all about banking and payments trends for 2026. We've got AI, automating credit card rewards personalization, and how agentic AI will turn mobile banking into your personal financial concierge. My guests today, for that conversation, are principal analyst living in California, Tiffani Montez. Welcome to the show.

Tiffani Montez (00:57):

Hi, there.

Marcus Johnson (00:57):

Hello, hello. And I'm also joined by senior analyst living in New York, it's Grace Broadbent.

Grace Broadbent (01:02):

Hi, Marcus.

Marcus Johnson (01:03):

Hello indeed. So, Rob likes to start his show with an icebreaker, and so this is one I've prepared earlier for you guys. And the question is, because we're talking about trends for this year, banking and payments, money trends, if you will, for the rest of this year. So personally, if I handed you $10 every day for the rest of the year, theoretically, how would you spend it? Tiffani, you go first.

Tiffani Montez (01:27):

I want to say I would buy a bottle of wine, but I am not certain that $10 would take me very far in today's economy.

Marcus Johnson (01:37):

You could save up every week and buy one at the end of the week.

Grace Broadbent (01:40):

It wouldn't be good wine.

Marcus Johnson (01:40):

That could be your Friday treat. All right, so Tiffani is going to probably save her money every day for a week at least, and then buy a bottle of wine. Grace, how about you? What would be your kind of... I was looking at this as kind of a financial news resolution, but then I thought they would all be quite boring, so I thought this would be a kind of spicier, more interesting way of looking at it, but what would you do with your $10 a day?

Grace Broadbent (02:03):

Yeah, I don't know if I have a responsible answer either.

Marcus Johnson (02:05):

We don't want that.

Grace Broadbent (02:06):

I would probably just buy myself coffee every day and not feel bad about it, because unfortunately coffee gets very easily to $10 in New York City.

Marcus Johnson (02:19):

With a tip, yes.

Grace Broadbent (02:19):

So, yeah. So, I would just get myself coffee, be happy every morning, and not feel guilty about it.

Marcus Johnson (02:22):

Feel less guilty is a good answer, yeah. I think I'd probably do the same. Very good. Well, let's get into it. Today's episode is focusing on, I guess I was going to say less personal, but some of these will actually be quite personal, banking and payments trends for 2026. Great banking and payments, I should say, bake off, or takeoff style. So in today's episode, it's styled the same way we've done all of our January episodes, which is a complete ripoff of the great British baking show, but we've been turning our bakers into takers because they're giving takes. It's all very clever. And we'll be cooking up, our bakers will be cooking up some banking payments trends to watch in 2026, a couple, but there are tons and tons more in the research that these both come from, and we'll tell you how to find that at the end of the show.

(03:18):

We've got three rounds, in case you haven't listened to our Bake Off episodes yet. They've been on the Behind the Numbers show and also a Reimagining Retail show as well. So if you're new to the format, we've got signature take, that's our first round. Our second one is going to be the how it technically plays out challenge, and then third is the show-stopping argument. So, round one. So, we meet the contestants predictions in round one. They're going to give us a one-minute or less summary, a premise of their trend. Grace, we're going to start with you.

Grace Broadbent (03:48):

Okay. My take that I'm talking about today, is that AI will automate credit card rewards personalization. So how this will work is issuers can use GenAI solutions, so create tailored rewards options for individual credit card holders at a scale that previously wasn't possible without GenAI. So, this can turn static category bonuses, like groceries or gas, into more dynamic rewards options that reflect a cardholder's real time purchasing habits.

Marcus Johnson (04:18):

Okay.

Grace Broadbent (04:18):

So, for example, if a cardholder buys a dog crate, the issuer can then offer them bonus rewards at PetSmart or Chewy, or another pet company like that.

Marcus Johnson (04:28):

You mentioned issuers can use GenAI to turn credit card holder's static category bonuses into dynamic rewards bundles that reflect their real-time purchasing habits. What do you mean by the dynamic rewards bundles?

Grace Broadbent (04:43):

So, it can mean a few different things. If a bank knows you applied for a home loan, then it might start offering you higher rewards at Home Depot, or other home stores. Or another example is say your highest rewards rate has been in gas recently, but then this month, you're spending a lot more on groceries maybe due to inflation, or something like that.

Tiffani Montez (05:05):

The price of wine.

Grace Broadbent (05:06):

Yeah, or the price of wine. And it also sees maybe you're driving around less, you're not paying as much as gas, it will automatically swap your highest rewards rate to groceries, give you higher credits on groceries, and take away your gas rate that you're not using.

Marcus Johnson (05:19):

Okay.

Grace Broadbent (05:20):

So, there's a bunch of different examples that I can get into more, but it's all about reflecting the cardholder's daily purchase habits to reward them how they're actually spending.

Marcus Johnson (05:30):

Okay. When it comes to how this works, I was wondering whether it's going to focus on recent purchases. Will it be more frequent purchases? Because I might buy a gift from my niece once, and then the credit card thinks I have a kid, and so personalized ads that use browsing history don't always work so well. So, I was wondering what kind of data information it's going to be pulling from to be recommending these rewards. You said it's going to be most recent, it's going to be most likely?

Grace Broadbent (05:55):

Yes. And I mean, that's where the difficulty comes.

Marcus Johnson (05:57):

Right.

Grace Broadbent (05:58):

The data isn't perfect. And again, you don't need to buy 20 dollhouses in the next month, but that's hopefully, as GenAI advances, it will know more about your past purchase history, and can pull things together and really actually understand your lifestyle, your potential family, your spending habits, and bring past data together, in addition to more recent purchase behavior. Which is the dream, of course.

Tiffani Montez (06:24):

Yeah. It probably could even get better at identifying the outliers in your purchase activity, right? If you can go far enough back, it's like "Was this a one-time situation or is there other purchase history that might lead me to believe that this is more of a permanent situation?"

Marcus Johnson (06:39):

Yeah, yeah, this is a great point. And I guess it's learning all the time, and so what it's going to be capable of in the first couple of months is going to be nothing compared to what's capable of in a year or two, especially once it's got some seasonal, habitual kind of data, Tiffani, to your point, to identify those one-offs, those seasonal one-offs, as opposed to the repeat purchases. All right, Tiffani, let's move on to yours, what will you be cooking up for us?

Tiffani Montez (07:00):

So, I'm going to be talking about brands will put generative engine optimization strategies to test. So, we're starting to see early signals of a structural shift in terms of how consumers discover and evaluate financial services. So, search is no longer about keywords, or even rankings. About 20% of US banking consumers are already using tools, AI tools like ChatGPT and Gemini, to research banking products, and that's according to our 2025 US consumer banking habits. And that tells us that customers are beginning to rely on AI answers, which will help them decide who to trust, what products best fit their needs, and what actions they should take next.

(07:47):

At the same time, we're also starting to see that banks are leaning into using generative AI within their own organization. So, we know that about 70% of banks are using agentic AI to some degree, according to MIT and EY, and that also is going to signal a shift where banks are going to make it easier in a mobile banking environment, to move away from just transacting with customers, to actually move more towards AI-driven financial guidance, and really orchestrating journeys based on what they know about consumers.

Marcus Johnson (08:24):

When I hear agentic AI being able to turn mobile banking into a personal finance concierge, that sounds quite cool. But another way you phrased it in the report is "Personal finance automation," and that sounds a little bit scary to me. And I was thinking, "Well, anecdotally, that's one person," but you do have some data showing that folks are concerned about banks using AI.

Tiffani Montez (08:43):

So, it was more than a third of US checking and savings account holders said that they don't want banks to use AI at all. And again, that was according to the same survey that I mentioned earlier. I think with any new technology, there always is a barrier to adoption that revolves around trust, and that means that banks are going to have to make sure that they are using AI in transparent ways, that there's some explainability in terms of how their data is used, that they provide value in using that data, meaning that they can demonstrate that there's a trade-off between giving your data, allowing us to use your data, and a benefit that they get, and that there's human oversight. And all of those things have to be in place in order to take that third of people that aren't willing to use AI and to start to shift their perception of what AI is, how it will be safeguarded, and their information is going to protect, and most importantly, the value that is created by using AI.

Marcus Johnson (09:42):

These are some brilliant predictions. Let's move to round two. It's called the How It Will Technically Play Out Challenge. Our chefs will explain in more detail how they expect the trends to manifest throughout the year. So Grace, we flip back over to yours, AI automates credit card rewards personalization, how does this play out in 2026?

Grace Broadbent (10:04):

Yes. So right now, fintechs are leading the way with rewards personalization and pilots. I'll give you a couple examples. Klarna, for example, partnered with NIF's AI-powered platform, which automatically matches rewards to individuals based on their past purchases. Basically, they offer users gift cards at participating merchants based on their past purchases. So, Klarna is a buy now, pay later company that is experimenting with that. Another fintech, Bilt, which is known for its credit card program for rent payments, is also experimenting with personalized rewards through its neighborhood program. So basically, the merchants, in their neighborhood program, can offer targeted rewards to residents based on past purchases they've made in the neighborhood. So, if they know they go shopping at this mall a lot, they can give them validated parking here or a free Uber home.

Tiffani Montez (11:04):

A free Uber home, huh?

Grace Broadbent (11:05):

I know. I would love that personally. I don't know how much you have to spend to earn that, but... But yeah, so these fintechs are leading the way on a smaller scale. We haven't really seen that as much with the larger credit card issuers. My prediction is that it's really going to start with more card-linked offers than full rewards programs. Chase, for example, has a Chase Offers program. You go in the Chase app, and it says "10% off at Lululemon, 10% off at Wegmans," whatever it may be, and so you click on that, and it automatically goes to your cards. So, I think those are going to become easier to automate than overhauling the full 3% cash back here, 2% cash back at gas stations, and things like that. And that will get consumers, I think, more comfortable with it.

Marcus Johnson (11:54):

Okay.

Grace Broadbent (11:55):

So, I think that we're going to start, at least in 2026, I think the large issuers will start with the smaller scaled card-linked offers while the fintechs explore with the wider rewards programs.

Marcus Johnson (12:06):

And how important are rewards to folks looking for a new credit card, or folks with credit cards? Where do they rank in terms of what people are looking for when they're trying to figure out what credit card to take?

Grace Broadbent (12:18):

Unbelievably high. So for our... It is true. I mean, think of why do you pick a credit card? It's because you get high rewards. That's how I always pick my credit cards.

Marcus Johnson (12:28):

Yeah, yeah.

Grace Broadbent (12:29):

In addition to an annual fee of how much it's going to cost you, you're not picking it based off of... Typically, you're not basing it off of fraud protections or the mobile app. You're saying, "Where can I get the most money?" And this came up in our survey we did also, this past summer, it was 40% of prospective cash back credit card holders cited rewards as one of the most valuable aspects when choosing a card to apply for. So, four in 10 is a pretty large segment of cardholders.

Marcus Johnson (12:58):

And you're saying that ranks quite high as well, compared to the other classes?

Grace Broadbent (13:00):

Yes, absolutely.

Marcus Johnson (13:00):

Okay.

Tiffani Montez (13:02):

And also, there's the angle too, that... I mean, oftentimes, they are looking for rewards, but they're also looking for that welcome bonus that will give them the most rewards if they do a large amount of spending within the first, well, whatever that introductory period is.

Marcus Johnson (13:15):

Yeah.

Grace Broadbent (13:15):

Yeah. And off of that also, credit card loyalty is also waning. Consumers are looking always, for the next best thing and the next best credit card. It used to be somebody at the same credit card for 20 years, and that just does not happen anymore. We're going to the next best, introduction bonuses, and things like that, and so these kind of dynamic rewards can also get consumers that stick around with their card longer than they typically would. So, it's a loyalty play in addition to getting the consumers to sign up.

Marcus Johnson (13:45):

And I guess, your existing bank could tailor the introductory offer, right? Because they have passed purchase data on you. So, that is a big hook, I think, for a lot of people, so maybe your bank has a leg up there.

Grace Broadbent (13:55):

Yeah, and get you to switch to a higher annual fee card, or something like that.

Marcus Johnson (13:59):

Yeah. Tiffani, what do you make of this AI automating credit card rewards personalization take for 2026?

Tiffani Montez (14:06):

I think there's a lot of opportunity for AI rewards to be personalized. Grace is hitting a really great point, that consumers oftentimes have more than one card, right?

Marcus Johnson (14:15):

Mm-hmm.

Tiffani Montez (14:16):

So, if they have four or five cards, they're oftentimes thinking about which card am I going to pay for this purchase with that will maximize the reward structure? So if you could take that kind of, we'll call it mental math out of the equation, then to Grace's point, you do have a competitive benefit, because people won't be out browsing for the next reward structure. The reward structure will reset based on your own spending.

Marcus Johnson (14:42):

So, that's fascinating. So, does this mean there's going to be, we are going to go from having four or five, I don't know what the average is, credit cards, and one's for gas, one's for my rewards when I fly, one's for groceries, et cetera, to one card to rule them all, and it's going to just personalize everything? Is that kind of how this plays out, do we think?

Grace Broadbent (15:00):

I don't know about one card, but I definitely think we'll get closer to that. Not in 2026, but five, 10 years down the line.

Marcus Johnson (15:09):

Because it can just adapt. It's dynamic enough to know-

Grace Broadbent (15:10):

Yeah.

Marcus Johnson (15:10):

Yeah.

Grace Broadbent (15:10):

To know where you want to spend, and do it without even having to think about where you're going to get the most points. That's really going to be key, is doing this so you don't have to go in your app every day and change your rewards, or you don't really have to think about where you're spending which card.

Tiffani Montez (15:24):

Yep. And what will also play into that is can banks actually underwrite a higher credit line on cards to be able to keep people there and this spending concentrated to one card. Because if you only have $5,000 on this card and you got $10,000 over here and $30,000 over here, there's got to be some consolidation of line if you really want to centralize all the spending.

Marcus Johnson (15:48):

Yeah. All right, let's move back over to Tiffani's.

Tiffani Montez (15:51):

I don't know, I like Grace's.

Grace Broadbent (15:53):

I like it too, does that mean I win? Does that mean I win the bake off?

Marcus Johnson (15:56):

That's not how the competition is supposed to go. If this was bake off, Tiffani's walked over to your station and gone, "That looks delicious, forget what I was making." She's abandoned her own dish. She started helping you with hers.

Grace Broadbent (16:09):

I will take it. I'm ready to walk out.

Marcus Johnson (16:12):

This is often how these episodes go, people start collaborating on the dishes and it makes for one fantastic meal. I'm going to force you back over to your station, Tiffani, if I may.

Tiffani Montez (16:22):

All right, all right.

Marcus Johnson (16:22):

And I'll ask you to talk a bit more about agentic AI turning mobile banking into a personal financial concierge. What does this look like in 2026?

Tiffani Montez (16:28):

I think I'm going to tackle this from two different angles, because I think there's the discovery process, and then I think there also is the engagement process, which would be more about the mobile banking experience. So, if I think about it under that context, AI-driven discovery and AI-driven engagement is advancing faster than traditional banking models are designed to support today. So, if we think about the discovery process, we've got the generative engines, which are already shaping which brands consumers consider, while agentic AI is the one that's driving the engagement once they actually log in. So, if we take it from the discovery side, the risk is concentrated. So today, we know that there are a small group of digital banks that control 80% of AI-generated visibility. So for banks, late movers face a much steeper hill to climb as it relates to relevance and generative engine optimization.

(17:27):

Banks that fail to appear in generative results risk being excluded from early consideration as consumer preferences form. If we think about it under the context of the engagement side, agentic AI raises expectations. The most immediate opportunity for banks is really around personal finance optimization, where AI agents can analyze cashflow. They can anticipate shortfalls in account balances. They can recommend the best action for consumers to take, and they can even initiate routine transactions within approved limits. And this is really where mobile banking starts to function less like an application and more like the personal financial concierge that we mentioned earlier.

Marcus Johnson (18:10):

So, as you explain in your research, it's this multi-step financial tasks. And as you just laid out, there are these different pieces that make up the whole consumer journey, so to speak, and you're saying that will analyze cashflow, it'll identify cash shortfalls, recommend actions, take actions within a certain limit. I was trying to think of an example. How does this play out in the real world? What would an example look like in practice?

Tiffani Montez (18:35):

Let me pick something complex, because I think that's probably the best way to bring this to life. So let's think about automobile ownership. The consumer wants to buy an automobile, which automobile market today is similar to the wine market, prices are extremely high and it's hard to know what you can afford.

Grace Broadbent (18:51):

Yep.

Tiffani Montez (18:52):

But let's say that you're doing the discovery process, and you're researching what might be the best product for you to actually purchase a vehicle. So, how much of a loan can you afford to take out? What is that loan going to cost you? And then also, what are some of the other things that you should anticipate paying for when you buy the car? Should you get paint protection, should you get tire protection? What are some of those other services that you might add on, and how does that impact the total cost of ownership outside of just paying for the loan, but also just paying for the day-to-day of a loan? So, that's sort of one on the discovery process.

(19:29):

And then when we start to think about the engagement process, how do you help someone manage that car as an asset? So, how do you help them understand how much money you're going to be spending on gas and what does that mean to your cashflow? How much money should you be saving for emergencies, whether that is something goes wrong with the car or it's an anticipated maintenance item that you need to take care of. Perhaps you need to add new tires to the car, you need to change the brakes, you need to change the oil, if you're thinking about AI-driven engagement, you can help a customer be able to anticipate when those stages in the ownership of a car will happen, and be prepared to either pay for that by savings or be able to understand and get product recommendations on how to actually pay for those different things.

Marcus Johnson (20:16):

That's incredibly forward-looking. So, you're not just saying it's going to look at your past history, in terms of what you've done transactionally, you are saying if you're trying to buy a car, buy a home, buy a something, it's going to say, "Hey, there are these things to consider."

Tiffani Montez (20:33):

There are these things to consider. And I think there is a future. I'm going to use Grace's line here, I don't think it's going to be in 2026, but I think there is a future where you'll have cross-industry data sharing, which allows this type of experience that I've just described to you much more cohesive, and you're able to pull in data about other events into one central location to help someone really understand what is happening now, what could you expect to happen, and how do I help prepare someone for those different things that will occur throughout that particular, we'll call it life stage.

Marcus Johnson (21:06):

Yeah. Grace, what do you make of this one?

Grace Broadbent (21:07):

Even though Tiffani likes my trend, I like hers as well. I feel like this definitely fits into other banking research. I know you've written about, and we've discussed, Tiffani, about life stages and how banks need to meet customers in their certain life stages, and they don't feel like banks are really doing that well right now. Because buying your first car can be intimidating, buying your first house can be intimidating, saving for your children's college, all things like that, banks really need to meet consumers where they're at better. And I think this really plays into it, and does it kind of more behind the scenes, and really offers the help that consumers are demanding today, and lacks right now from banks.

Tiffani Montez (21:47):

Yeah. Even if I think about the context of just savings, we, as an industry, for years, have talked about putting things in savings buckets, savings pools, and we're thinking about customers to think about what do you want to save for rather than telling them what should you save for. Because saving isn't just about putting money away for a rainy day, savings is also about helping them understand how much money can I expect to potentially pay every year on unexpected expenses related to my car, to my home, medical expenses. How do you help someone really understand where they are in their life and how much money that they should be spending on different expenses, and setting money aside to be able to do that?

Marcus Johnson (22:27):

Yeah. And life stages, I feel like, have changed. They've become so much more personal recently. The generations before, it was, "This is when you go to college and this is when you get married, and this is when you buy a home. This is probably when you have kids, this is when you should retire," and throw that in the trash because everyone's experience looks so different now. All right folks, let's move to... I could stay on round two forever, but we should probably move to round three, which is called the showstopping argument. Our chefs will pull out their best closing arguments as to why. I'd say as to why their trend is most likely to happen more so than their colleagues, but they're apparently working together. So, it's turned from a competition into a team sport, of which there is only one team, so instead, just give me 20 seconds, Grace, as to why you think your trend is likely to happen, perhaps not more so than Tiffani's, but just will happen in 2026.

Grace Broadbent (23:27):

Okay. With AI set to transform basically every industry, the credit card space and credit card rewards are going to be no different. The winners won't be the banks that offer the most points, but the ones that offer the most everyday value to cardholders in a seamless way that fits into their lives.

Marcus Johnson (23:44):

Final question for you, is there a world where this could be frustrating to consumers? If they're getting recommended the wrong thing to spend their money on, is there a way that this could potentially backfire?

Grace Broadbent (23:57):

I would say it wouldn't be frustrating if it's done right.

Marcus Johnson (23:59):

Right.

Grace Broadbent (24:00):

If it's, again, like your example, you buy your niece a dollhouse and it keeps recommending kids stuff to you, yes, that's frustrating. But if the GenAI, and their solutions, do what they're supposed to do and realize that's an outlier, then it should be beneficial in the end.

Marcus Johnson (24:16):

Yeah. All right. Tiffani, how about you?

Tiffani Montez (24:19):

So, what connects the two trends that I talked about is really about controlling the customer's decision moment, and just controlling their experiences. And so customers are increasingly delegating discovery, evaluation, and even execution to AI systems, whether it's through the discovery process or evaluation, and those systems are going to favor brands that they understand, that they trust, and that they can confidently recommend. And the banks that invest now in generative engine optimization will influence how AI surfaces their products and their brands, and banks that deploy agentic AI responsibly will also reshape how financial guidance is delivered in everyday life. And the banks that do neither risk falling out of the consideration set as AI becomes the front door to financial decision making.

Marcus Johnson (25:12):

Final question for you, Tiffani, do you see this hitting a certain part of what you've talked about more so in 2026 than others? Do you see it being discovery, the engagement piece? Do you see it helping folks save more, pay off credit cards more, help them with the buying of houses more? Is there a certain area you're expecting to impact the most this year?

Tiffani Montez (25:30):

I think this year, it's going to be more around the discovery phase, because I think consumers are already, as we can see, they're using it to find financial products and services. So, the real risk for financial institutions is that someone's out there controlling your narrative and someone's out there controlling how your brand is positioned, the tone that you're using, and even the information, or misinformation, that is being given by ChatGPT. So, the bigger risk is if you don't know exactly what to do, what you should do is just make sure that you're keeping your brand safe.

Marcus Johnson (26:01):

Yeah. And just as a teaser, Tiffani has some fantastic predictions listed in this section of the report, this one being on banking, and there are multiple other predictions. I think five total, we've only talked about one. Grace's as well, there are about five predictions in there, that one on payments. I'll give you the information to those in a second. Well, I can give it to you now, because this would be the part where I crown a star baker, but it's both of them because they threw the rules out the window, moved into a shared kitchen, and created a fantastic dish. So, congratulations to both, you are both today's star bakers.

Tiffani Montez (26:44):

Thank you.

Grace Broadbent (26:44):

Thank you. I'll take it.

Tiffani Montez (26:44):

All right.

Marcus Johnson (26:45):

That's all we have time for. Thank you so much to both of my guests. Thank you to Grace.

Grace Broadbent (26:49):

Thank you for having me.

Marcus Johnson (26:50):

Of course. And to Tiffani.

Tiffani Montez (26:51):

Thank you for having me.

Marcus Johnson (26:53):

Yes, indeed. Thank you to Rob for letting me host this one. Thanks to the whole production crew, John working behind the scenes.

Tiffani Montez (27:01):

Come back, Rob.

Marcus Johnson (27:01):

Yes, please, we miss you.

Tiffani Montez (27:01):

I'm just kidding, Marcus. You did a great job.

Marcus Johnson (27:02):

Yeah, could have saved that until the end. Thank you very much, Tiffani, after we're finished recording. But she's right, please come back as soon as possible and do a way better job than me. Thank you to everyone for listening to my voice and bearing with me for being the guest host on this Banking Payment show and EMARKETER podcast. For banking trends to watch in 2026 and payments trends to watch in 2026, both two separate reports, links are in the show notes, or [inaudible 00:27:25] subscribers can of course go to EMARKETER.com and search for those things. Susie will be here tomorrow with you, with our first monthly Reimagining Retail Awards.