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The financial sector is witnessing a significant shift, with a dramatic increase in community banks and credit unions facing immense pressure to sell. Over the past five years, the number of large institutions with indicators of high sell-side pressure has tripled, growing from just 10 to more than 30. Furthermore, nearly 10% of all banks and credit unions now exhibit financial profiles consistent with being acquisition targets within the next 18 to 36 months.
While this might suggest a booming M&A market by 2026, the reality is far more complex. A recent study by Engage fi reveals that while the current environment offers a larger pool of potential targets, many of these institutions are in a precarious financial state. This “running out of oxygen” scenario means they lack the resources to invest adequately in critical areas like growth and technology. Larger sellers, in particular, present substantial post-merger integration challenges, especially concerning their underlying technological infrastructure.
Success in this target-rich but complex environment won’t simply be about identifying a willing seller. The true differentiator will be what happens after the deal is struck, with data — especially core data — emerging as the central factor.
A Surge in Potential Targets
The past half-decade has seen a steady rise in institutions, including those with assets exceeding $1 billion, $10 billion, and even one with over $20 billion, demonstrating significant pressure to sell. As of the latest regulatory data, this group of high-pressure-to-sell institutions now encompasses 32 banks and credit unions, all exhibiting financials that suggest an acquisition is likely within 18 to 36 months.
This trend extends beyond large institutions, with the segment of smaller banks and credit unions (under $1 billion in assets) also seeing a substantial increase in sell-side pressure. Out of 8,837 financial institutions analyzed, 865 were identified as facing high pressure to sell. This includes 651 credit unions (14.7% of those studied) and 214 banks (4.8% of those studied).
Engage fi’s model, which defines ‘pressure to sell’ using five years of FDIC or NCUA data (2021 – Q3 2025) and was back-tested against 74 mergers announced in 2025, accurately pinpointed stress signals in acquired institutions months before deals became public.
Two Categories of Sellers
- Watchlist Institutions: 764 institutions are on a ‘watchlist,’ indicating they may lack the financial capacity to simultaneously invest in growth and necessary technological upgrades. For these, maintaining independence is becoming increasingly difficult for their boards.
- “Highly Likely” to Sell: Another 101 banks and credit unions are nearing critical levels, defined as “highly likely” to sell. These institutions are under such severe strain that a sale or merger is becoming unavoidable. Crucially, their technological infrastructure, which houses the invaluable data underpinning their franchise value, cannot be adequately maintained.
Ultimately, many sellers’ current struggles boil down to technology woes, which are inherently expensive to resolve. Moreover, buyers entering this market are likely to encounter fierce competition, potentially driving up acquisition prices.
Intense Buyer Competition
Despite the challenges, the M&A landscape is also brimming with eager buyers. Engage fi’s analysis identifies 1,736 institutions as viable buyer candidates, based on their size and financial stability, suggesting they possess the balance sheet capacity and strategic positioning to pursue acquisitions.
The buyer pool includes 806 credit unions, with 81 ranking in the top decile for readiness due to strong profitability, efficiency, net worth ratios, and growth momentum. Similarly, 930 banks qualify as buyer candidates, 93 of which are top-decile performers with a median asset size of $2.23 billion, indicating a greater capacity for acquiring larger targets.
This dynamic ratio of approximately two buyer candidates for every institution facing seller pressure points to a highly active M&A market. Sellers will likely find multiple suitors, fostering competitive bidding and potentially higher valuations.
The Overlooked Risks of Post-Merger Data Migration
In an environment with numerous potential sellers who may have deferred technology investments for years, post-merger data migrations represent a significant risk to the overall success of an acquisition. An acquirer unable to seamlessly preserve and integrate the seller’s data onto its own systems might as well have bought a car without the keys. The core value—the “franchise value”—is encapsulated in that data.
Every depositor, borrower, staff member, and even board member relies on an organization’s data as the definitive record of its relationships. This data directly impacts an acquirer’s ability to leverage the seller’s assets across all operations, from payment processing and accounts payable to digital banking and transactions. While executives understand the inherent value of their data, institutions under pressure to sell often struggle with the technology required to maintain it, compounding post-merger integration challenges.
Acquirers simply cannot afford a flawed data migration. But can they truly absorb the cost of doing it perfectly without eroding the very economies of scale that made the acquisition attractive in the first place? KPMG reports that many data migration projects “fail to meet their timelines or are entirely aborted, often exceeding budgets by an average of $0.3 million per data set.”
This “per data set” cost is crucial. Given that a typical M&A deal can involve dozens of data sets, these expenses quickly accumulate, making data migration a significant financial concern. Over 40% of such projects encounter these issues. The larger the target institution, the more systems, silos, and data an acquirer must ingest, which can severely impact the financial benefits of the transaction.
Strategies for Preserving Acquired Franchise Value
While intense buyer competition tends to drive up valuations, the sheer volume of tech-troubled institutions could push prices to a point where the economics simply don’t align. If a project exceeds its budget by $0.3 million per data set, acquiring an institution with “dozens” of data sets can lead to substantial cost overruns. Missing targets on just 10 data sets, for instance, could mean a $3 million budget overrun, assuming average costs. This doesn’t even account for the productivity drain on teams stuck reconciling data, and it assumes a modest 10 data sets.
This challenging data migration equation can either evaporate deal economics, forcing acquirers to factor these additional costs into their bids, or it necessitates finding innovative ways to minimize system and data migration expenses. The former option may render acquirers less competitive in a market where every seller has multiple potential buyers. The practicalities and economics of banking acquisitions increasingly point in one direction:
Expertise in data migration is becoming the paramount strategy for buyers to secure deals and realize their full value, effectively accounting for all the associated costs, effort, and disruption. It is how institutions can leverage M&A not only for growth but also to emerge as stronger, more efficient organizations in the process.
Source: thefinancialbrand.com