Bank Consolidation in 2025: Using Network Data to Measure Risk and Value
Most bank mergers and acquisition (M&A) strategy still treats customers as dots on a map. Yet in 2025, funding and credit risk move along networks: depositors react within their social circles, and firms transmit distress through supply chains. A deal that looks diversifying on a branch map can stack correlated tails if both institutions are tied to the same hubs; a deal with complementary networks can improve relationship value and resilience. With reviewers focusing on competitive effects beyond deposit shares, the central diligence task is to measure how your depositors and borrowers are connected across places and products. The next two sections apply that lens to funding networks and credit networks.
Regulatory Shifts
Banks still underwrite mergers using branch maps, deposit Herfindahl indices, and static portfolio correlations. Those are necessary, but they miss a key margin of risk and value: how borrowers and depositors are linked across places and products. Social and commercial networks transmit shocks, accelerate runs, and shape cross-sell potential. Boards that quantify those links will make better go or no-go decisions and will be better positioned with regulators and investors.
Recent policy changes increase the importance of a forward-looking, evidence-based narrative. The Office of Comptroller of Currency (OCC) recently streamlined its merger review in May 2025 and rescinded its 2024 policy statement, shifting emphasis back to durable supervisory principles. The FDIC similarly rescinded its 2024 Statement of Policy and reinstated its prior framework. Meanwhile, the Department of Justice’s 2024 Banking Addendum clarifies how the 2023 Merger Guidelines apply to banks, signaling that the government will look beyond deposit shares to product overlaps and competitive effects. Taken together, you should assume qualitative arguments will matter, especially those tied to customer outcomes and financial stability.
Role of Network Effects
Traditional geographic analysis underweights two channels that materially affect post-merger performance. First, funding networks: deposits and attention flow along social ties and information channels, not only along county lines. The Social Connectedness Index (SCI) provides a tractable measure of the strength of friendship links between regions; in multiple applications, areas socially linked to a shock-hit place experience funding and behavior changes even without physical proximity. Recent work directly connects social ties to deposit movements, and the 2023 stress episode showed how social media accelerated uninsured outflows, and my own work has used the SCI to quantify the effects of economic sentiment on consumption at a local level. Incorporating these weights into pre-deal models improves estimates of run sensitivity and funding beta.
Second, credit networks: borrower defaults travel through supply chains and relationship webs, amplifying losses relative to borrower-by-borrower models. Multi-layer network approaches that combine bank-firm credit links with inter-firm trade links quantify this contagion and often raise expected loss and tail risk estimates compared with stand-alone models. Evidence from the United Kingdom and newer European datasets shows that shocks propagate from banks to firms and along production networks, with measurable effects on loan performance and bank equity buffers. For M&A, this matters in two directions: overlapping exposures to the same supply-chain hubs can synchronize downside tails, while complementary networks can diversify them.
A network-aware diligence exercise can be executed with standard internal data and a few external inputs. Start by mapping the combined footprint as a graph whose nodes are your deposit and lending markets and whose edges reflect SCI weights. Use historical weekly or monthly deposit data to estimate how flows in one node respond when highly connected nodes experience news or stress, yielding a network-adjusted measure of run exposure. On the credit side, match commercial portfolios to industry and supplier-customer relationships where available; compare probability-of-default and loss-given-default distributions across the two banks to identify where tails overlap, then run contagion scenarios that allow shocks to travel across customer links. The goal is not a perfect system-wide model, but a decision-ready quantification of correlated liquidity and credit risk that geography alone would miss.
Implementation Details
This information feeds both valuation and regulatory positioning. On valuation, depositor networks identify where the merged institution is stacking correlated funding risk versus where it can lower acquisition costs by growing share in communities already tied to both banks. On credit, supply-chain centrality highlights where concentration limits or tighter underwriting should accompany integration. For regulators, the same analysis supports a narrative that addresses competition and stability with concrete evidence. The DOJ has indicated it will assess competitive effects beyond crude deposit shares; a network map that explains how the merger changes customer access, product overlap, and failure propagation risk speaks directly to that brief. The OCC’s and FDIC’s changes put more weight on well-documented, case-specific reasoning, which network analysis provides.
When, then, does overlap—that is, similarities in the distribution of borrower characteristics across locations—help rather than hurt M&A likelihoods of success? Overlap is constructive when two banks touch adjacent parts of the same community network with different products or relationship roles, because it raises lifetime value per relationship and improves screening through better soft information. Research on syndicated lending shows that well-connected lenders structure larger, better-priced deals with lower risk retention, consistent with information advantages accruing to central network positions. By contrast, if depositors and borrowers are tightly linked to the same external hubs, liquidity and credit tails can align under stress, raising capital and liquidity needs post-close.
Banks do not need to wait for perfect data to act. A workable approach for 2025 deals is to pair a parsimonious SCI-weighted funding model with a focused contagion analysis for the top commercial segments, report the delta versus geography-only models, and size integration safeguards accordingly. That means committing, in prose not platitudes, to branch retention or consolidation choices that reflect connected communities, to liquidity buffers that reflect estimated network betas, and to portfolio limits or enhanced underwriting where supply-chain links are dense. The resulting package gives boards a cleaner view of value and equips counsel to meet the DOJ’s broader competition inquiry and the banking agencies’ renewed emphasis on case-specific analysis.