A sweeping new study from the New York Federal Reserve presents a long-horizon analysis of U.S. bank failures, built from an expansive balance-sheet database that spans back to the Civil War era. The dataset, unique in scope, tracks the financial health and ultimate outcomes of thousands of banks, offering a window into the drivers of distress and failure that longer histories reveal beyond the post-1970s period typically examined. The findings illuminate how banks deteriorate before collapse, how funding composition shifts in stressed times, and how boom-bust dynamics in lending contribute to volatility in the sector. Against this backdrop, the study is weighed alongside an established, proprietary framework used to gauge bank safety, which highlights the importance of “red flags” and funding structure in predicting risk. The discussion then pivots to current conditions in the banking system, questions about the disclosure of modern failure probabilities, and practical steps for individual readers to assess the safety of their deposits and investments.
The NY Fed Dataset: Scope, Depth, and the Advantage of a Long Horizon
The core of the study rests on a comprehensive, bank-level database that compiles balance-sheet information for a broad cross-section of U.S. banks over more than a century and a half. By compiling data dating back to the mid-19th century, the research captures episodes of financial stress and structural change that are invisible when looking only at recent decades. This extended horizon allows for the observation of thousands of bank outcomes, including more than five thousand failures, and makes it possible to analyze patterns that emerge only with long-run data. The sheer breadth of the dataset raises the reliability of identified correlations and lends credence to conclusions about how banks behave under stress, how losses accumulate, and how funding and asset dynamics interact as banks approach insolvency.
The study’s design emphasizes the evolution of risk over time, not just the occurrence of failures in a single era. By spanning different monetary regimes, regulatory environments, and credit cycles, the dataset helps investigators distinguish persistent vulnerabilities from period-specific fragilities. The authors argue that this comprehensive historical perspective provides a more complete map of the banking system’s stability landscape, especially in light of how modern risks might resemble or diverge from historical patterns. In addition to the raw balance-sheet figures, the research contemplates the interplay between asset quality, earnings capacity, and capital adequacy, considering how these dimensions shift during expansion phases and tightening cycles.
The long-range approach also helps illuminate how a bank’s financing mix can evolve under stress. In particular, the newer findings underscore the recurring theme that funding structures—especially the share of noncore or wholesale funding—become more prominent as banks face liquidity pressures. The dataset enables a cleaner separation of the effects of asset quality deterioration from those of funding vulnerabilities, letting researchers describe how banking crises unfold in a way that is both granular and historically contextualized. Taken together, the dataset and the period it covers provide a framework for understanding how conventional metrics behave over time, and where early-warning indicators may diverge across different historical epochs.
Core Finding 1: Insolvency Risk Climbs as Losses Rise, Preceding Bank Failures
One of the central conclusions of the study is a clear, observable sequence that tends to precede bank failures: losses accumulate and solvency indicators deteriorate before distress culminates in failure. In practical terms, non-performing loans rise, which triggers higher loan-loss provisioning and, in turn, compresses profitability. As earnings erode, the equity-to-asset ratio generally declines, signaling weaker capital buffers that leave the bank more exposed to adverse shocks. This chain of events—rising losses, shrinking profitability, and deteriorating capital—appears consistently across the historical record, making it a recurring prelude to failure rather than an isolated anomaly.
The significance of this pattern lies in its consistency and its implications for risk monitoring. Banks that maintain strong asset quality, robust profitability, and resilient capital ratios are markedly better positioned to absorb unexpected losses during downturns. Conversely, institutions showing persistent increases in problem loans and thinning margins tend to enter a period of heightened vulnerability. The identification of these dynamics in the historical record provides a baseline for understanding how modern banks might exhibit early signals of stress, even when headline indicators appear stable in the near term.
In discussing these dynamics, the study also invites comparison with alternative risk-assessment frameworks. In particular, proprietary methodologies that emphasize a broader set of 20 distinct metrics—beyond the standard solvency and asset-quality indicators—aim to improve the accuracy of predictions. While the 20-metric framework is only one element of a larger analytical approach, its emphasis on combining multiple dimensions of risk aligns with the broader conclusion that straightforward accounting measures, while informative, do not capture the full spectrum of bank fragility. The takeaway is not that traditional metrics are insufficient on their own, but that they gain explanatory power when integrated into a more holistic view of a bank’s risk profile, including qualitative factors and structural vulnerabilities.
Core Finding 2: Failing Banks Rely More Heavily on Noncore Funding
A second major conclusion of the study concerns funding structures. As banks approach trouble, they increasingly rely on noncore funding sources, diverging from more stable, conventional funding bases. This shift is notable because noncore or wholesale funding tends to be more volatile, expensive in turbulent times, and sensitive to market sentiment. The reliance on such funding can amplify liquidity pressures during periods of stress, making an institution more susceptible to funding squeezes that compound solvency concerns.
The historical and cross-sectional patterns indicate that funding vulnerability is not merely a byproduct of losses. It is a structural factor that interacts with asset quality and earnings to shape a bank’s resilience. By examining funding composition, researchers can identify banks that may be particularly at risk for liquidity disruptions when confidence wanes or when market conditions tighten. The implications for risk management are clear: institutions with a larger share of wholesale funding should be scrutinized for liquidity risk, and those with more stable funding streams—such as a higher proportion of retail deposits—may exhibit greater resilience in stressed environments.
This finding also intersects with the broader debate about funding stability and liquidity risk management in the current era. The analysis emphasizes that a bank’s funding mix matters as much as, or even more than, some traditional balance-sheet measures during periods of stress. Therefore, in practice, lenders and supervisors alike should pay close attention to the composition of liabilities, the maturity profile of funding, and the ability to access liquidity facilities when needed. The research suggests that institutions with a higher fraction of non-interest-bearing demand deposits or other sticky funding instruments tend to weather short-term disruptions more effectively, though they are not immune to systemic shocks.
In parallel with this insight, the study notes the broader methodological stance of the researchers: while the 20-metric framework provides a robust set of indicators, the most crucial aspect of identifying risk lies in recognizing “red flags” and excluding banks that exhibit them. The red-flag approach complements funding-focused analysis by flagging institutions with warning signs that warrant closer inspection, even if some standard metrics appear acceptable at a glance. The combined emphasis on red flags and funding structure forms a practical blueprint for proactive risk screening, both for policymakers and market participants.
Core Finding 3: Boom-Bust Cycles and Rapid Asset Growth Drive Failures
A third key takeaway from the historical analysis is that bank failures often follow pronounced boom-bust cycles. Banks tend to experience rapid growth—both in absolute terms and relative to their peers—for a period of up to three years before failure, after which the expansion reverses and contraction sets in. The surge in growth is typically fueled by loan origination and asset expansion, with lending activity acting as the primary engine of the rising balance sheet during the exuberant phase.
This pattern underscores a familiar risk theme: periods of strong credit growth can mask underlying vulnerabilities if risk controls do not tighten commensurately. The study highlights three lending sectors where growth has accelerated in recent times, and these sectors are especially relevant for evaluating current risk. First, shadow banking has expanded its footprint, absorbing a portion of funding and credit risk outside traditional regulated channels. Second, consumer credit, including revolving and installment lending, has grown rapidly, raising concerns about underwriting standards and consumer leverage. Third, commercial real estate (CRE) lending has seen notable expansion, exposing portfolios to sector-specific shocks. Each of these segments carries elevated risk, and rapid growth within them can amplify the likelihood of distress if conditions deteriorate.
The broad implication is that asset growth, while often a normal feature of a healthy bank, becomes risky when it outpaces the efficacy of risk-management practices. Aggressive growth can outstrip the institution’s capacity to monitor loan performance, maintain credit discipline, and retain adequate loss-absorbency. This dynamic can lead to a vulnerability trap, where rising asset aggregation begets higher exposure to adverse events, thereby increasing the probability and severity of a future downturn. The historical record cautions readers about the dangers of assuming that fast growth is inherently benign, particularly when driven by sectors characterized by elevated risk.
In the current discourse on asset and credit growth within the banking system, these themes remain central. Contemporary analyses point to concentrated growth in shadow banking, credit cards, and CRE as areas of elevated fragility. The convergence of rapid lending in riskier sectors with floating funding costs can produce feedback loops that magnify losses and speed up the onset of liquidity stress. The study’s boom-bust lens thus serves as a diagnostic framework for interpreting today’s credit landscape, highlighting where imbalances may be developing and how they might culminate in distress if not checked by prudent risk controls.
The Predictability of Bank Failures: Simple Metrics and Broad Implications
A principal conclusion of the study is the notable predictability of bank failures using relatively straightforward accounting measures drawn from publicly available financial statements. Across the historical record, observable indicators tied to insolvency risk and funding vulnerabilities align with the eventual onset of distress, suggesting that, in aggregate, failures can be anticipated with a meaningful degree of accuracy. This finding reinforces a broader narrative about risk assessment: while no single metric provides a perfect forecast, a constellation of accounting signs often foreshadows trouble, and aggregating multiple indicators can yield actionable signals about vulnerability.
From a methodological standpoint, the study highlights that predictability emerges not just from isolated figures but from the interaction of several dimensions—asset quality, profitability, capital adequacy, and funding structure. When these dimensions deteriorate in concert, the probability of failure tends to rise. The historical evidence supports the idea that, even within noisy financial data, coherent patterns reveal themselves over time, enabling a probabilistic assessment of insolvency risk.
The practical implication for readers, investors, and depositors is that awareness of these signals can inform safer decision-making. While the study’s historical focus is broad, the underlying logic applies to current banks: regular monitoring of loan performance, earnings quality, capital robustness, and funding stability can yield early warnings of emerging risk. This emphasis on accounting-driven indicators aligns with the broader warning that bank failures are not solely the result of rare black swan events but often the outcome of predictable, observable shifts in fundamental financial health.
In parallel with the primary conclusion about predictability, the research notes that the predictive signal becomes strongest when combined with a disciplined evaluation of red flags and an assessment of funding exposures. The integrated approach—relying on a robust set of metrics while remaining vigilant for warning signs—offers a practical framework for ongoing surveillance of banks across the yield, credit, and liquidity dimensions. The upshot is that a well-calibrated, multi-faceted view of risk can translate historical patterns into a useful, forward-looking risk assessment toolkit.
Why the Fed’s Modern Disclosure Stance Remains a Question
A provocative thread in the study’s discussion concerns why the Federal Reserve has not publicly disclosed predicted failure probabilities for the modern, larger banking system. The analysis suggests that the underlying data and methodologies indicate widespread vulnerability among many institutions, particularly among larger banks, based on current financial statements. This observation invites a question about why the central bank has not shared explicit probability estimates for contemporary banks, given the apparent information contained in publicly available statements.
From a policy and communications perspective, several considerations may influence such a decision. Public dissemination of predicted probabilities could generate heightened depositor concern, spur rapid shifts in funding and liquidity preferences, and potentially trigger self-fulfilling runs if panic takes hold. Regulators may also weigh the risk of misinterpretation or oversimplification of probabilistic forecasts in a complex financial system where many banks exhibit intertwined exposures. The decision to withhold explicit probability figures could reflect a cautious stance aimed at maintaining financial stability and avoiding disorderly responses in a fragile environment.
On the other hand, proponents of transparency argue that clearer signaling about systemic risk could bolster confidence by providing a documented framework for understanding risk concentrations and improving market discipline. The tension between transparency and stability is not trivial, and it underscores the ongoing debate about the appropriate balance between disclosure and market dynamics. The study’s authors acknowledge the tradeoffs involved and present their historical findings as evidence of predictability, while recognizing that contemporary disclosure policies are shaped by broader considerations that extend beyond pure statistical accuracy.
In sum, the question of disclosure remains unsettled. The historical analysis demonstrates that predictable patterns exist within financial statements and that accounting-based risk signals can be informative. Whether and how such signals should be communicated in today’s complex banking system is a policy choice that involves assessing the potential benefits of transparency against the risks associated with amplified, rapid feedback effects in the marketplace. Readers and market participants can derive value from understanding that simple accounting metrics do carry predictive information, even as the exact communication strategy for modern risk probabilities remains a matter of regulatory judgment.
Current Risk Environment: Large Banks vs. Community Banks, and Sectoral Heterogeneity
Turning to the present-day risk landscape, the study emphasizes a nuanced distinction between the risk profiles of larger banks and smaller, community institutions. While the larger banks often carry a broader, more diversified footprint and substantial funding access, they can simultaneously be exposed to higher absolute levels of complex risks—particularly in areas such as commercial real estate, consumer debt, long-duration securities, and sophisticated over-the-counter derivatives. The proliferation of shadow banking activity, nontraditional lending channels, and the interconnected nature of modern balance sheets means that problems in any one area can reverberate across the system, especially when liquidity and capital positions are under stress.
In contrast, community banks—typically smaller, more relationship-focused, and with more conservative balance sheets—tend to weather certain shocks differently. The historical record and contemporary observations suggest that many community banks adopt conservative business models, fund more stable deposits, and emphasize prudent underwriting standards that reduce downside risk. Nevertheless, not all community banks are immune to risk, and there are notable examples of weaker institutions within this segment. The overarching message is that size alone does not determine resilience; risk management quality, asset-liability mismatches, and exposure concentration matter just as much, if not more, in predicting outcomes during stress episodes.
The current environment also features structural risk factors that cut across bank size. Commercial real estate remains a focal point of concern, given its concentration in both major and regional lenders and its sensitivity to cycles in the broader economy and interest rates. Rising consumer debt levels, particularly when paired with high leverage and limited income growth, can strain households and translate into higher loan delinquency rates. Long-term securities—especially if purchased at elevated prices or with mismatched durations—pose interest-rate and market-value risks that can materialize during shifts in rates or liquidity crunches. Over-the-counter derivatives and other sophisticated risk positions add layers of counterparty risk that require robust risk governance to avoid amplification of shocks. Lastly, the expansion of shadow banking signals ongoing transformation in credit intermediation, implying that surveillance must adapt to evolving forms of credit risk and liquidity risk that do not fit traditional firms or channels.
Taken together, the current risk environment is characterized by a broad spectrum of vulnerabilities that can manifest differently across institutions. The convergence of sector-specific exposures with concentrated funding and balance-sheet weaknesses can produce complex, system-wide dynamics. This complexity calls for rigorous, multi-metric risk monitoring that accounts for both conventional indicators and the more nuanced risks associated with newer market structures and lending practices. The historical perspective provided by the NY Fed study serves as a reminder that predicting banking sector distress benefits from acknowledging both enduring patterns and evolving risk factors.
Community Banks, Due Diligence, and Practical Guidance for Depositors
A recurring theme in the analysis is the emphasis on due diligence, especially for readers who hold money in banks of various sizes. The evidence suggests that while many community banks offer solid risk profiles and conservative business models, there are notable exceptions where risk conditions are less favorable. The takeaway is not a blanket endorsement of all community banks, but rather a call for thorough evaluation of each institution’s balance-sheet health, risk concentrations, underwriting practices, and funding structure. For individual depositors and investors, the prudent path is to conduct independent due diligence and to rely on a methodical framework for assessment rather than relying on reputation alone or broad sector assumptions.
The suggested approach to due diligence centers on a structured methodology that extends beyond traditional balance-sheet ratios. It involves examining the following core dimensions: asset quality indicators (non-performing loans, charge-offs, and troubled debt restructurings), earnings quality (net interest margin, fee income stability, and operating efficiency), capital adequacy (capital ratios adjusted for risk, buffers against downturns), and funding characteristics (deposit composition, liquidity coverage, and access to liquidity facilities). An emphasis on deposit dynamics—particularly the balance between stickier, non-interest-bearing shares and more volatile funding sources—helps gauge resilience under stress. By combining quantitative indicators with qualitative assessments of governance, risk management culture, concentration risk, and strategic clarity, readers can form a more robust view of a bank’s safety profile.
This section also reinforces the importance of recognizing that even within a generally sound segment, there can be meaningful differences between institutions. Some community banks may exhibit conservative risk appetites, prudent underwriting standards, and high levels of capital adequacy, which collectively enhance safety. Others may display riskier lending concentrations, aggressive growth, or funding vulnerabilities that elevate the probability of distress, especially in a challenging macroeconomic environment. The practical implication is that readers should implement a disciplined due-diligence checklist tailored to their exposure horizon, liquidity needs, and risk tolerance, ensuring that money is placed in institutions whose business models and risk controls align with their financial objectives.
In addition to deposit safety considerations, the analysis highlights the broader implications for market confidence and systemic stability. If a sizable portion of the banking sector exhibits early warning signs, the effects can ripple through funding markets and deposit flows, potentially amplifying stress across institutions. Therefore, ongoing, transparent information about risk factors—even when not distilled into precise probability figures—can contribute to more informed decision-making and better risk-sharing across financial segments. Readers are encouraged to stay informed through independent research, engage in regular reviews of their bank’s risk posture, and consider diversification strategies that align with their financial goals and spendable liquidity.
Public Banking Narratives, SVB, and the Warning Signals for the Market
The discussion around large institutions, high-profile failures, and early warnings extends to recent episodes that have captured public attention. Historical analysis identifies patterns and drivers that can surface again in a different guise, including factors that contributed to prior crises and others that reflect contemporary developments in the banking sector. The takeaway from these discussions is that the core principles of prudent risk management—attention to asset quality, maintenance of adequate capital, and careful monitoring of funding structure—remain relevant across eras. While headlines may shift with new institutions or regulatory changes, the underlying mechanics of banking risk persist.
In examining potential alerts presented by public cases, readers are reminded that even banks perceived as solid can encounter idiosyncratic or systemic shocks. The trajectory of distress often involves a confluence of stressors: deteriorating asset quality, pressure on funding liquidity, rising leverage, and exposures to sensitive sectors. The cautionary examples—from well-known stress events to more muted episodes—underscore the need for a vigilant, disciplined approach to risk assessment, both for individual account holders and for institutions weighing capital allocation decisions.
The broader narrative also stresses that early signals often appear in the form of sectoral imbalances and concentrated vulnerabilities. For example, if a bank’s loan book shows outsized exposure to cyclical sectors or if funding comprises a disproportionate share of volatile instruments, these become red flags—even when other metrics seem manageable. The historical lens provided by the long-run study helps readers anticipate how such imbalances may surface under different macroeconomic scenarios, offering a framework for interpreting current conditions in light of past experience.
Practical Steps for Depositors: Deploying a Robust Due-Diligence Toolkit
Given the insights from the historical and contemporary analyses, readers are encouraged to adopt a proactive, methodical approach to evaluating where their money is parked. The practical steps outlined below form a structured toolkit for ongoing due diligence, with an emphasis on clarity, transparency, and risk awareness.
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Build a multi-maceted risk view: Rather than relying on a single ratio or metric, assemble a dashboard that includes asset quality indicators (delinquency rates, charge-offs, loan loss reserves), earnings quality (net interest income, non-interest income, efficiency), capital adequacy (risk-weighted capital ratios and buffers), and funding stability (deposit mix, wholesale funding reliance, liquidity coverage ratio). Consistent monitoring across these dimensions helps detect early signs of stress.
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Assess funding resilience: Analyze the funding profile with a focus on the maturity structure, reliance on noncore funding, and the share of non-interest-bearing deposits. Banks with more sticky deposits and diversified, stable funding sources tend to weather liquidity squeezes better than those dependent on volatile wholesale markets. Consider the potential for rapid liquidity shifts under adverse conditions and how the bank would manage such stress.
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Evaluate sectoral risk exposures: Identify concentrations in sectors such as commercial real estate, credit cards, shadow banking avenues, or other high-risk lending lines. Consider how macroeconomic developments—interest rate trajectories, housing markets, consumer debt levels, and employment conditions—could impact these exposures and what mitigation measures the bank employs.
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Examine governance and risk culture: Look beyond numbers to assess governance quality, risk-management practices, board oversight, stress-testing capabilities, and response protocols during downturns. A strong risk culture often correlates with more prudent lending and a greater capacity to adjust to evolving risk landscapes.
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Test resilience under stress: Review the bank’s stress-testing framework, including scenarios that capture adverse macroeconomic conditions, rising default rates, and liquidity shocks. Consider the institution’s contingency plans, capital-raising abilities, and liquidity facilities, and how quickly these instruments could be mobilized if needed.
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Diversify and monitor deposit funds: For individual depositors, diversification across institutions can reduce exposure to idiosyncratic risk. Maintain awareness of the macro backdrop and how systemic risks could influence the stability of the banking system, adjusting allocations if risk perceptions change materially.
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Stay informed with independent analyses: Complement official filings with independent research that triangulates across multiple perspectives. Look for consensus signals and acknowledge areas of disagreement, using the range of analysis to refine risk assessments rather than accepting any single viewpoint uncritically.
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Periodically reassess: Establish a cadence for re-evaluating bank risk profiles as conditions change. A quarterly or semiannual review—especially during periods of economic evolution or regulatory shifts—helps keep risk assessments aligned with current realities.
The Bottom Line: Navigating an Environment with Elevated Risk Signals
Overall, the study presents a compelling narrative about the predictors of bank distress and the components that make banks more vulnerable during stress periods. While historical evidence underscores the existence of predictable patterns in insolvency risk and funding vulnerabilities, the practical application of these insights requires careful, ongoing due diligence tailored to individual risk tolerances and financial objectives. The banking system as a whole faces a confluence of risk factors, including real estate cycle vulnerabilities, rising consumer indebtedness, duration mismatches in securities, the expansion of over-the-counter derivatives, and the evolving landscape of shadow banking. These factors contribute to heightened sensitivity to macroeconomic shifts and to liquidity dynamics, thereby elevating the importance of robust risk management and informed decision-making for both institutions and their clients.
For readers and investors, the message is clear: do not assume safety based solely on sector or size. While many community banks can offer strong risk profiles and sound governance, a prudent approach is to conduct thorough, institution-specific due diligence and to implement diversification strategies that reflect the spectrum of potential scenarios. Awareness of the long historical context reinforces the value of vigilance and resilience, encouraging readers to anchor their decisions in rigorous analysis rather than complacency or overreliance on any single data point. The overarching goal is to safeguard hard-earned money by engaging in careful, ongoing evaluation and by prioritizing institutions with demonstrable risk-management discipline and stable funding structures.
Conclusion
The NY Fed study provides a historically rich lens on how bank failures unfold, identifying a consistent sequence of deteriorating solvency, rising losses, and weaker capital buffers that precede distress. It also highlights the structural role of funding patterns, with noncore funding increasingly shaping liquidity risk as banks grow and cycle through booms and busts. The convergence of rapid asset growth, concentrated exposures in riskier lending sectors, and evolving funding dynamics underpins a fragile equilibrium that can be vulnerable to abrupt shifts in market sentiment or macroeconomic stress. The research further emphasizes that bank failures have a measurable degree of predictability when accounting-based signals are considered alongside broader risk indicators, reinforcing the value of a comprehensive, multi-metric approach to risk assessment.
In light of these findings, readers are urged to conduct diligent, institution-specific evaluations rather than relying on general impressions or broad sector narratives. The current environment, characterized by elevated risks in commercial real estate, consumer debt, long-duration securities, derivatives, and shadow banking, calls for heightened vigilance and proactive risk management. While the discussion acknowledges the uncertainties inherent in signaling exact probabilities for modern banks, the historical evidence underscores the importance of monitoring key indicators, recognizing red flags, and maintaining robust liquidity and capital buffers. By applying a disciplined due-diligence framework and remaining attentive to sectoral dynamics, depositors and investors can make informed choices that align with their financial goals and risk tolerance, helping to safeguard wealth in an evolving banking landscape.
