Reality Check: Is AI’s Promise to Deliver Competitive Advantage a Dangerous Mirage?
Banking executives must plan for an uncomfortable truth: Every bank has access to the same AI capabilities through their core and digital banking vendors. Banking already is an homogenized product. So what happens when AI tools make our banks' products even more commoditized and undifferentiated?
By Matt Doffing, Senior Editor at The Financial Brand
At a recent bank board meeting, Jason Henrichs, Chief Executive Officer at Alloy Labs Alliance, prompted the AI platform, Claude, with the following: I’m giving a presentation to the board of a bank company about AI. What question is no one going to ask but should?
Claude responded, "Given your background in banking and fintech, let me offer a provocative but critical question that often goes unasked in board presentations about AI: What happens when AI makes our bank’s products completely commoditized and undifferentiated?"
Henrichs shared Claude’s suggestions recently on LinkedIn prompting insightful discussion from bankers, fintech leaders, thought leaders, and even from Claude.
Commoditization Fallout?
What happens when AI makes our bank’s products completely commoditized and undifferentiated? It’s not a defeatist question for the industry. Instead, it suggests a shortcoming in bank and credit union strategic planning about AI, Henrichs says.
"Everyone’s asking about efficiency gains, risk management, and competitive advantages from AI," he suggests. "The uncomfortable truth is that if every bank has access to the same AI capabilities [and increasingly do through vendors like nCino, Q2, and FIS], we’re racing toward commoditization at an unprecedented speed."
Henrichs suggest every bank consider a coming industry normal in which every charter can automate underwriting with accuracy, provide personalized financial advice through large language models, optimize pricing in real-time, and deliver contextual banking experiences.
"The real strategic conversation isn’t just about implementing AI," he says. "It’s about how to maintain pricing power and customer relationships in a world where AI has democratized capabilities that used to be competitive moats."
Banking is Familiar with Commoditization Cycles
Banks have had products-are-commodities syndrome for a while now, even before changes coming from generative AI, says Chris Nichols, Director of Capital Markets at SouthState Bank, Winter Haven, Florida.
"Optimized AI pricing has been around for more than a decade but few banks deploy it for loan or deposit pricing," he says. "Generative AI gives banks another dimension in which to add value."
Henrichs agreed sharing feedback from Claude: "You’ve caught me in the classic consultant trap of ‘everything is different this time!’ Let me push back on my own argument. You’re right – we’ve heard this commoditization story for decades. Free checking, online banking, mobile apps, API banking… each wave was supposed to be the ‘great equalizer’ that would commoditize banking.
Yet somehow Wells Fargo still has a 160-basis-point advantage in net interest margin over most other banks, and JP Morgan still commands premium multiples.
"The reality? Distribution advantages, regulatory scale benefits, and deposit franchises have proven remarkably sticky even as products get ‘commoditized.’ Bank of America can run a money-losing checking account business because they monetize through cross-sell. A [smaller] bank has to actually make money on checking. Maybe the better board question isn’t about commoditization (which banking has survived before), but rather:
How do we ensure AI amplifies our existing competitive advantages rather than just giving us table stakes features?
If history is any guide, banking institutions that win with AI won’t be the ones treating it as a commoditized product layer, Henrichs says. "It will be the ones using AI to extend their structural advantages in distribution, regulatory scale, and customer relationships that win."
Fast-Follower Mentality Enables AI Commoditization
How can boards lead the institution to use AI to amplify existing competitive advantages? It’s not just about the technology.
It’s "the combination of technology stack," say Jim Marous, Co-Publisher of The Financial Brand, with "people, leadership and willingness to take risks that will result in the quality of AI looking far different from bank A to bank Z. AI [is about] rethinking what we do. Further, fast follower doesn’t cut it because trying to copy… ignores the fundamental strategic changes [happening] behind the scenes."
Creativity is not exactly a top priority in an industry accountable day-in and day-out to regulators, yet it’s required as technology applies commoditization pressure. "Many banks will run to Microsoft’s CoPilot because it is the ‘easy button,'" adds Nichols. "Chatbot offerings and AI help will keep banks level. However, the creative banks will find new ways to harness traditional AI and Gen AI into their products and services to differentiate themselves further."
Right now, when a nationwide bank launches a new credit card, Henrichs describes four tactics it can pursue:
- Target existing Chase checking customers
- Run massive marketing campaigns
- Leverage their brand
- Price aggressively using their funding advantage
Claude provides the following upgraded tactics, which are enabled by AI:
- Use transaction data from 60M+ customers to build better targeting models
- A/B test thousands of marketing variations at scale
- Deploy personalized onboarding flows based on customer segments
- Dynamically adjust credit lines and rewards based on real-time behavior
"The raw computing power [of large, nationwide institutions] becomes more valuable because they have more data," Henrichs says. "The personalization works better because they have more products to cross-sell. The risk models perform better because they have richer customer histories."
A smaller bank may try these same tactics but hit walls everywhere – not enough data, not enough products, not enough marketing budget to acquire signal, Henrichs observes. "They can’t [win by] bolting on AI features," he says. "It’s about identifying your structural advantages – maybe it’s local market share or specific industry expertise – and figuring out how AI can extend those specifically."
So, what happens when AI makes banks’ products completely commoditized and undifferentiated?
They are already commoditized. The banks that have found growth through the industry’s decades of commoditization and consolidation have something else that’s kept them viable. Boards must identify those elements of the bank’s business model and work with management to improve differentiators with new technology like AI.
AI will drive commoditization in banking. But the cause of a bank’s commoditization is entirely up to that bank. If it has differentiators already, AI can magnify those advantages. But if not, AI will likely magnify the effects of banking’s commoditization.
