Behind the Numbers: The Great BTN Bake (Take) Off — Banking and Payments Trends for 2026
The Banking & Payments Show | January 27, 2026
Host: Marcus Johnson (guest hosting for Rob Rubin)
Guests: Tiffany Montes (Principal Analyst, CA) & Grace Broadbent (Senior Analyst, NY)
Episode Overview
This episode of "Behind the Numbers: The Banking & Payments Show" takes on a playful “Bake Off” format to discuss the biggest banking and payments trends for 2026. With rapid AI transformation in financial services, Marcus, Tiffany, and Grace dive into how AI is reshaping credit card rewards, personalization, mobile banking as a personal concierge, and the future digital battleground for consumer trust and discovery. The episode focuses on three main themes:
- AI-driven credit card rewards personalization
- Agentic AI transforming mobile banking
- AI’s critical role in brand discovery and consumer trust
Key Discussion Points & Insights
1. Icebreaker: $10-a-day Thought Experiment
- Each guest shares a lighthearted answer to how they’d spend $10 a day, reflecting on current spending habits.
- Grace: “I would probably just buy myself, like, coffee every day and not feel bad about it because fortunately, coffee gets very easily to $10 in New York City with a tip.” [02:03]
- Tiffany: Would save up for a bottle of wine.
- Sets the tone for a conversation that blends personal finance with broader trends.
2. Round 1: Signature Take – The Big Predictions
A. AI Automates Credit Card Rewards Personalization
Grace Broadbent’s Take:
- AI and GenAI (Generative AI) will enable tailored rewards options at an unprecedented scale, moving from static one-size-fits-all categories (e.g., groceries, gas) to dynamic, real-time bundles based on actual purchase behavior.
- Example: If you buy a dog crate, your credit card may offer bonus rewards at Petsmart or Chewy. If your spending shifts from gas to groceries, your top rewards follow your new habits.
- “It’s all about reflecting the cardholders’ daily purchase habits to reward them, how they’re actually spending.” [05:30]
- Challenge & Opportunity: AI needs to distinguish between regular and one-off purchases for meaningful personalization.
B. Agentic AI as a Personal Financial Concierge
Tiffany Montes’ Take:
- We’re seeing a structural shift in how consumers discover and evaluate financial services:
- Discovery: About 20% of US banking consumers use AI tools (e.g., ChatGPT, Gemini) to research products. Banks must optimize for “generative engines” or risk being invisible during early consideration.
- Engagement: 70%+ of banks use Agentic AI. Moving away from mere transactions, banks use AI for real-time financial guidance (e.g., journey orchestration, anticipatory advice).
- Barrier: Trust remains an issue, with over a third of US account holders reluctant for banks to use AI.
- “Banks are going to have to make sure that they are using AI in transparent ways, that there's some explainability… and provide value in using that data.” [08:43]
3. Round 2: How Will It Technically Play Out?
A. Real-World Examples: Rewards Personalization
- Fintechs blaze the trail:
- Klarna partners with NIF’s AI to personalize gift card rewards based on past purchases.
- Bilt offers hyper-targeted perks (e.g., free Uber rides for frequent mall shoppers via its “neighborhood program”).
- “I would love that. Personally, I don't know how much you have to spend to earn that but, but yeah…” [11:05]
- Incumbents follow with card-linked offers:
- E.g., Chase Offers (app-based, dynamic discounts); easier initial step than fully reinventing core rewards structures.
- Consumer Impact:
- Rewards top the list of reasons for choosing a credit card—40% cite them as the top factor for cash-back cards.
- “Credit card loyalty is also waning… consumers are always looking for the next best thing and introductory bonuses.” [13:15]
- Personalization and ease may keep users loyal, reducing card-churn.
- Rewards top the list of reasons for choosing a credit card—40% cite them as the top factor for cash-back cards.
B. Agentic AI as Concierge in 2026
- Discovery Process:
- Generative engines (AI search tools) are starting to shape which brands are visible. Early action is key; late-movers risk irrelevance.
- “Banks that fail to appear in generative results risk being excluded from early consideration as consumer preferences form.” [16:27]
- Generative engines (AI search tools) are starting to shape which brands are visible. Early action is key; late-movers risk irrelevance.
- Engagement Process:
- AI agents analyze your finances (cash flow, shortfalls), recommend actions, and even automate certain transactions.
- Practical Example: Buying a car. AI can guide discovery (affordability, loan matching, add-on services) and day-to-day management (gas costs, maintenance budgeting, emergency savings).
- “If you're thinking about AI-driven engagement, you can help a customer… be prepared to pay for things by savings or get product recommendations.” [19:00-20:16]
- Vision for the Future:
- Cross-industry data sharing would enable even more holistic guidance and anticipation of life events.
4. Memorable Quotes & Moments
- On Rewards Personalization:
- Grace: “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.” [23:27]
- On Brand Relevance & AI:
- Tiffany: “Customers are increasingly delegating discovery, evaluation, and even execution to AI systems... Banks that deploy Agentic AI responsibly will reshape how financial guidance is delivered in everyday life.” [24:19]
- On Personal Finance Guidance:
- Tiffany: “Savings 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… and setting money aside to be able to do that?” [21:47]
- On Changing Life Stages:
- Marcus: “Life stages... have become so much more personal recently… everyone's experience looks so different now.” [22:28]
5. Round 3: Showstopping Arguments & Takeaways
- Both guests converge, agreeing the two trends are intertwined—AI is set to become both the “front door” and the “guiding hand” of consumer banking and payments decisions.
- Big Risks:
- For banks: Miss out on AI optimization, and you risk being left out of the conversation altogether.
- For consumers: AI must be accurate and transparent—recommendations that “miss” the mark (e.g., outlier purchases) could frustrate, not delight.
- Immediate Impact:
- Discovery phase via AI likely to see the biggest impact in 2026, with consumers already using generative engines for decisions.
Notable Timestamps
- [03:48] – Grace’s overview of AI-powered dynamic credit card rewards
- [05:55] – Discussion on “dynamic rewards bundles” and data privacy
- [07:00] – Tiffany on generative engine optimization and AI discovery in banking
- [08:43] – Consumer trust and adoption barriers regarding AI in banking
- [10:04] – Klarna, Bilt, and fintech pilots in personalized card rewards
- [12:18] – Significance of rewards in credit card selection
- [16:27] – Tiffany details on AI transforming banking discovery and engagement
- [18:35] – Real-world example: AI concierge for auto purchase and ownership
- [23:27] – Grace’s showstopping argument on seamless, everyday value
- [24:19] – Tiffany on controlling customer experiences with AI
Conclusion
“The big story in 2026? AI in banking is transitioning from theory to everyday utility, driving both how consumers discover financial products and how they manage money. Rewards will become hyper-personalized, and mobile banking will evolve beyond basic transactions into holistic, anticipatory financial guidance. Trust and responsible AI use remain the linchpin for adoption.”
Both guests agree these trends are deeply interwoven—AI isn’t just assisting finance, it’s becoming the infrastructure on which consumer trust, discovery, and loyalty will hinge.
For More: EMARKETER subscribers can access further research and predictions referenced on the show via reports on Banking Trends to Watch in 2026 and Payments Trends to Watch in 2026.