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Large bank stress test tool

Run your own stress test on banks

The potential of large bank failure puts the American taxpayer at risk. Preventing such failure and subsequent bailouts requires understanding the ability of these banks to withstand a large shock, such as a recession. With that understanding will come the motivation to enact government policies that will protect taxpayers. One of the best tools to assess the condition of banks is a stress test. Providing regular, transparent assessments of the health of the largest banks—and whether they will have sufficient capital to support lending during a future economic shock—will help empower the public to make their own assessments of the strength of large banks.

We created the tool below to allow the public to run their own stress tests on the largest banks in America. You can vary the amount of stress that large banks face in this test and see how their financial health (for example, capital buffer) changes. In short, the public will now have the transparency they need to judge the condition of the largest banks.

Results produced from the tool are derived from the model we created that was based heavily on Hirtle, Kovner, Vickery, and Bhanot (2014). You can find output from that original model on the New York Fed web page. A description of the key changes in the Minneapolis version can be found here. We continue to evolve the stress testing tool to increase its power and functionality for the public. You can learn more about potential uses of this tool based on the conference we sponsored on the topic, “Empowering the Public to Assess Large Bank Resiliency, “ by viewing this video and consulting this article. Feedback and suggestions for additional enhancements to the underlying model are welcome.

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Government support See how govt. support reduced losses (21 firm total only. Add'l details.)

0 firms with projected capital below their individual thresholds

Choose a bank to stress:
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Real GDP growth
3m T-bill yield
10yr T-note yield
BBB bond yield
CRE price index
House price index
Stock market
Payout policy
Low (33%)  Medium (66%)  High (100%) 
(% of net income paid out in dividends & share buybacks)

Macroeconomic Variables

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Read Frequently Asked Questions about the Minneapolis stress test model

This zip file includes the computer code and data files used in the Minneapolis stress test model.


  1. The chart above is an extension of the article on stress testing for large banks in the COVID-19 pandemic published on May 12, 2020. This web page allows users to select different paths for the eight macroeconomic variables used in the Minneapolis version of the CLASS model and then see the resulting projection of capital for the 21 domestic banks that are part of (or can opt into) the 2021 DFAST exercise.
  2. The scenarios shown here are not forecasts but are instead hypothetical scenarios. The scenarios were constructed to help illustrate how large banks could react to the adverse economic conditions associated with severe recessions.
  3. The capital projections in the stress scenarios include the performance of banks under the negative economic conditions along with additional losses resulting from operational risk, counterparty default, and the global market shock to large bank trading portfolios (based on the recently released official results from the final 2020 exercise).
  4. A new option has been added that allows users to specify the amount of earnings that will be paid out in the form of dividends and stock buybacks (the “payout policy”). Projected capital will be lower when higher amounts of earnings are paid out in dividends and buybacks.
  5. The dashed red line in the chart labeled “capital threshold” is one of the following:
    • 4.5 percent if an individual bank is chosen that is not one of the eight systemically important firms;
    • 4.5 percent plus the applicable GSIB surcharge if the firm is one of the 8 systemically important firms (the surcharge is 2.5 percent for JP Morgan Chase, 2.0 percent for Citigroup, 1.5 percent for Bank of America, Goldman Sachs, and Wells Fargo, and 1.0 percent for Bank of New York Mellon, Morgan Stanley, and State Street);
    • 5.8 percent if the “21-firm total” is selected, which is the aggregate amount of capital required by the set of firms to meet the 4.5 percent statutory minimum of risk-weighed assets plus the applicable GSIB surcharges for the eight systemically important firms (this amount was roughly $530 billion as of the fourth quarter of 2020).
  6. The Minneapolis version of the CLASS model currently assumes that the individual firms hold a constant balance sheet over the projection period. As such, total assets, liabilities, and risk-weighted assets remain fixed at their starting levels over the nine projection quarters.
  7. An adjustment was made to the loan loss models that rely on the unemployment rate to account for the rapid increase in unemployment that occurred in 2020. Historically, there has been a strong positive relationship between losses on these loan types and changes in the unemployment rate (increases in unemployment are associated with higher losses and decreases are associated with lower losses). The 9.3 percentage point increase in unemployment that occurred in the second quarter of 2020 was the largest ever seen since data were first collected in the late 1940s. Moreover, it was over five time as large as the next biggest quarterly change in the series. However, at the same time, there was no corresponding increase in loan losses given the very unusual nature of the shock to the economy and the massive government response. Not adjusting the models for this extreme observation effectively eliminates the relationship between loan losses and unemployment. As such, quarterly dummy variables have been included in the models to denote the second-quarter 2020, third-quarter 2020, and fourth-quarter 2020 time periods. Utilization of dummy variables in this fashion removes the impact from second-quarter 2020 data points on the estimated coefficients and preserves the pre-existing historical relationship. Additional details regarding this are available upon request.
  8. ^ The “government support” option shown above displays a hypothetical capital path for the 21-firm total. This path includes the implied support the banking sector received from the extraordinary government interventions in the economy that took place during the COVID-19 pandemic. We describe how to calculate the magnitude of this support here. Our rough calculations suggest that government support reduced loan losses between $130 billion and $230 billion for the entire banking system. The 21 firms shown above accounted for roughly 60 percent of total bank loans at the start of 2021, and we assume that they received a proportionate share of the loan loss reductions. We also assume that the avoidance of financial market disruptions eliminates the losses from the global market shock, which are roughly $90 billion for the relevant firms. After taking taxes into account, this results in an increase to capital of $131 billion to $178 billion for the 21 firms. Total risk-weighted assets (RWA) for the firms were $9.2 trillion at the end of 2021. The corresponding increase in capital ratios from the implied government support ranges from 143 basis points to 194 basis points when measured as a percent of RWA. The hypothetical path shown in the chart reflects the average value of the range—roughly 150 basis points —and it is allocated proportionately over the projection horizon.