By Arik Rashkes, Head of the Financial Institutions Group, Solomon Partners
Artificial intelligence is no longer just a technology story for financial institutions. It is quickly becoming a valuation story.
For years, AI has been framed as a tool to improve efficiency, enhance customer experience and modernize operations. That framing is no longer sufficient. AI is now beginning to reshape how financial institutions are evaluated, acquired and integrated — and it is already showing up in live transactions.
Historically, financial institutions have relied heavily on third-party vendors for core technology — underwriting systems, CRM platforms, reporting tools and more. Those relationships were embedded in operating models and often viewed as a source of stability, if not advantage.
That assumption is shifting. Large institutions are repurposing internal engineering teams to build capabilities that were once outsourced, and AI is accelerating that move. Tasks that used to take days — adjusting models, extracting and reconciling financial data, auditing outputs — can now be completed in minutes.
The impact goes beyond cost. It changes how technology is sourced, maintained and, ultimately, valued.
Institutions are no longer simply asking whether to buy or build. They’re asking how quickly they can build — and how much flexibility they retain when they do so.
A New Lens in M&A: Technology as a Variable, Not a Given
In traditional M&A, buyers focus on revenue growth, cost savings and integration risk. Technology has always been part of that analysis, factored into both integration planning and the cost structure.
Buyers are now evaluating technology much more aggressively. Instead of assuming that existing systems — and their associated costs — will carry forward, they are asking a different set of questions:
- Which systems are essential and which are replaceable?
- What portion of current technology spend is truly fixed?
- How quickly could key capabilities be rebuilt internally using AI-enabled tools?
In many cases, the answers are leading to a reassessment of value.
Costs tied to outside technology vendors — once seen as unavoidable — are now being treated as something buyers can strip out. That creates a new source of savings, alongside the usual cuts to overhead. For some buyers, this is quickly becoming part of the standard playbook.
Compression in Time, Cost and Assumptions
The pace of change is striking. Not long ago, building a proprietary platform could take years and significant capital outlay. Now, in some cases, buyers are assuming they can rebuild key systems in a matter of months and at a fraction of the historical cost.
Whether that proves true every time almost doesn’t matter. Those assumptions are already shaping how deals get priced. Today’s reality is that if you’re not moving forward in AI, you’re moving backwards.
In practical terms, that puts sellers in a different position. Money spent on technology in the past doesn’t necessarily carry the same weight in valuation. If a buyer believes a system can be replaced quickly and cheaply, they are less inclined to pay for it.
In some cases, buyers are discounting entire categories of vendor-based technology spend — not because the systems aren’t useful, but because they can be replaced quickly and no longer provide a lasting edge.
Integration: From Constraint to Opportunity
AI is also starting to change one of the hardest parts of any deal: integration.
Bringing together different systems after an acquisition has always been slow, expensive and messy. Companies often end up stitching together multiple legacy platforms, many of them tied to outside vendors. That limits flexibility and drags out timelines.
AI-enabled development is starting to change that equation. If buyers can build and deploy their own systems more quickly, they can have more control over how everything comes together. Integration becomes less about trying to reconcile a patchwork of old systems and more about moving onto a shared, adaptable platform.
That has real consequences for value. The faster a company can integrate what it buys, the sooner it can realize cost savings and operate as one business. And the more control it has over its systems, the lower the risk of things going wrong. Those factors show up in how deals are priced.
The Emerging Divide in Valuation
As these dynamics take hold, a divide is beginning to emerge.
Institutions with flexible, AI-ready technology stacks — and the ability to keep evolving them — are increasingly in a position to command a premium. Their cost structures are more adaptable, integration is more straightforward, and their economics are easier for buyers to get comfortable with.
By contrast, firms that rely heavily on rigid legacy systems or outside vendors may face a different outcome. In those cases, buyers are more likely to view technology as a constraint rather than an asset — something to be reworked rather than leveraged.
That distinction is not yet fully reflected in every transaction. But it is becoming more visible and more relevant with each deal cycle.
A Different Kind of Urgency
Financial institutions have always moved carefully when it comes to new technology, and with good reason. The stakes are high, and the regulatory and operational risks are real.
AI changes the equation. This isn’t just another upgrade cycle. As AI starts to shape how businesses are run, it is also changing how they are assessed by investors and potential buyers.
If buyers are already incorporating these assumptions into their underwriting, then the relevant question for management teams is not whether to invest in AI at some point in the future. It is how their current technology and cost structure would be evaluated in a transaction environment that is evolving now.
Put more simply: If an institution were brought to market today, how much of its technology stack would be viewed as a source of value — and how much as something a buyer would replace?
The answer to that question is increasingly central to valuation.
Institutions that move quickly to understand and adapt to this shift may position themselves to capture a premium. Those that do not risk being evaluated on a very different basis than they expect.