Predicting Bank Failure


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This white paper explores the ramifications of the coming wave of defaults in credit cards, home equity lines, and commercial real estate on the U.S. banking system. The paper also describes a new statistical model that predicts bank failure (i.e. seizure of a U.S. financial institution by the FDIC) using publically available data.

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Predicting Bank Failure

  1. 1. Predicting Bank Failure An Investigation of Financial Institution Risk for 2009 and Beyond Bill Cassill, Numerical Alchemy, Inc. 425.996.8732 Office May 2009
  2. 2. Introduction Given the turmoil in the banking sector over the last few months, people have naturally been worried about the solvency of financial institutions. While terms like “hedge funds,” “CDO’s”, “credit default swaps,” and “structured investment vehicles” get bantered around in the media, a less mentioned threat is the growing tsunami of defaults on commercial real estate loans, consumer credit cards, and home equity lines of credit that banks, large and small, have kept on their own books. In the last year, we have seen Washington Mutual, Indy Mac Bank, and a host of smaller banks go under. Despite the recent illusion of “stability,” what is currently unfolding is a train wreck in slow motion where continued credit losses threaten the continued solvency of already undercapitalized banks. Because of the recent turmoil, Numerical Alchemy took up to answer the question “Just who is solvent?” Using publically available data from the FDIC, specifically the quarterly reported Statistics on Depository Institutions, Numerical Alchemy modeled the likelihood of a banking institution (not the holding company) to fail or need FDIC “assistance” 6 to 9 months from the end of a given quarter’s reported data. What we developed from this exercise is a predictive model for bank failure based on multiple risk factors. The resulting model proved highly accurate in isolating the most at risk institutions. Same period validation captured better than 80% of failures/assistance in the top 10% of most at risk institutions. The out-of-time validation was even more accurate capturing better than 90% of failures in the top 10% of riskiest institutions. In addition, we went one step further and used FDIC and Bureau of Labor Statistics to forecast total bank failures, net credit losses, and unemployment rates for the next few months. Anyone looking for a turnaround in the financial sector this year shouldn’t hold their breath. Things are about to get even uglier. What Nobody Wants You to Know If you listen to the Wall Street talking heads, the economy is on the mend. We have had a recent rally in equities from the March lows, and there are little glimmers of evidence to suggest that things might finally be getting better or at least not any worse. Even the stress test results for the top banks were a yawn for investors. Given all of this, things can’t be all doom and gloom. Right? The truth is that the steep increase in the number of banks that will fail or need extraordinary assistance is just now beginning to get under way. Copyright © 2009 Numerical Alchemy, Inc. 2
  3. 3. Bank Failures: Actual and Forecast 350 324 300 236 250 Bank Failures 200 148 147 150 125 100 102 50 30 7 4 11 4 3 0 0 3 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Actual Forecast Lower 95% CI Upper 95% CI Data Source: FDIC Failures and Assistance Transactions Data; Modeling Technique: Single Series ARIMA Interestingly, it isn’t just smaller banks that are in trouble. Almost all of the top national banks in terms of deposit holdings score in the top 10% of banks most likely to fail. Failure Total Deposits Failure Risk Decile Odds Risk Institution Name Bank Holding Company Q4 2008 (in Probability (10% cut of (Q3 Percentile thousands) (Q3 2009) sample) 2009) rd JPMorgan Chase Bank JPMorgan Chase & Co. $1,055,765,000 0.0128 1 in 78 Top 10% 3 th Bank of America Bank Of America Corp. $954,677,580 0.0009 1 in 1116 Top 20% 11 rd Citibank Citigroup Inc. $755,298,000 0.0132 1 in 76 Top 10% 3 nd Wachovia Bank Wells Fargo & Company $424,599,000 0.0216 1 in 46 Top 10% 2 rd Wells Fargo Bank Wells Fargo & Company $346,850,000 0.0148 1 in 68 Top 10% 3 Although these banks (except for Citi) are not officially listed by the FDIC as having failed or needing extraordinary assistance, all have been the recipients of billions in Federal aid. Copyright © 2009 Numerical Alchemy, Inc. 3
  4. 4. “Bulls and Bears Make Money, But Pigs Get Slaughtered” – Jim Cramer What’s driving this risk? It is largely on balance sheet credit exposure. While securitized debt, primarily in the form of home mortgages have already taken steep losses, many banks, particularly the largest ones, have significant exposure to credit card debt, home equity lines of credit, and commercial real estate. Our forecasts indicate that net loan losses held on the books of banking institutions (i.e. total loan charge-offs minus recoveries) for 2009 will exceed $200 billion. Losses through the end of 2010 could exceed $400 billion. The $400 Billion Question: Forecast Cumulative Net Charge-Offs to Loans, Leases, and Lines-of-Credit $600,000,000 Cumulative Net Loan Charge-Offs (in thousands) $500,000,000 $400,000,000 $300,000,000 $200,000,000 $100,000,000 $0 Q1 2009 Q2 2009 Q3 2009 Q4 2009 Q1 2010 Q2 2010 Q3 2010 Q4 2010 Predicted Net Loan Losses (Cumulative) Lower 95% CI Upper 95% CI Data Source: FDIC SDI; Forecasting Technique: Single Series ARIMA Outstanding net loans and leases as of Q4 2008 was $7.7 trillion. As large as the projections may seem, the $400 billion in losses represent only 5.2% of the outstanding credit on banks’ balance sheets as of the end of Q4 2008. Unfortunately, these losses also represent better than 40% of the entire tier I capital of the U.S. banking system (approximately $1 trillion as of Q4 2008). Copyright © 2009 Numerical Alchemy, Inc. 4
  5. 5. Don’t Expect Any Help From an Improving Employment Picture The good news is that the large banks needed little in the way of additional capital based on the recent stress test results. However, the tests do seem not to have been very stressful from an employment perspective. The most dire scenario used in the stress tests assumed an unemployment rate slightly in excess of 10%. By our forecasts, it is likely that the unemployment rate will exceed 10% by July and could exceed 12% by the end of the year. If unemployment continues to edge higher into 2010, this will only add to the stress of financial institutions with heavy credit exposure. Unemployment Rate by Month: Actual and Forecast 16 Unemployment Rate 14 >12% by December 2009 Unemployment Rate (Percentage) 12 Unemployment Rate >10% by July 2009 10 8 6 4 2 0 Unemployment Rate Forecast Lower 95% CI Upper 95% CI Data Source: Bureau of Labor Statistics (seasonally adjusted); Forecasting Technique: Single Series ARIMA Copyright © 2009 Numerical Alchemy, Inc. 5
  6. 6. The Drip, Drip, Drip of Bad News Anyone looking for a quick turnaround to the current bank crisis will likely be disappointed. If, as some predict, we see a bottoming out of the economy by 4th quarter 2009, credit losses may abate in 2010 leaving many at-risk firms intact. However, if our forecasts are correct, many of the at-risk firms will become increasingly challenged to remain solvent in the face of mounting credit losses and falling deposit share. We believe that if net-charge offs continue into 2010, then many banks, including some of the largest ones, will become effectively insolvent making nationalization a moot point. In many ways, at risk banks sealed their fate in the last several years. However correct the arguments for individual consumer responsibility, many of the national and regional banks were active participants and promoters of cash out refi’s and home equity lines. As late as last year, there were credit card providers who were actively firing customers with high credit ratings who paid off their balances every month because they were not deemed as profitable as the revolvers who carried balances month-to-month. Other banks dove head first into the commercial real estate market in the building frenzy of now empty strip malls and large tract residential developments. The fate of many purveyors of easy credit will be decided in the coming 18 months. The Opportunity Amidst the Carnage Despite all of the doom and gloom contained herein, the fact remains that many banks are in relatively good shape. The risk and the losses will be concentrated among a relatively smaller segment of players. The real winners from the crisis will be a handful of larger players and the host of smaller regional banks that maintained safe lending practices during the credit boom. The question becomes how do these banks effectively exploit the opportunity? The first is to tout their financial stability by referring to sites like and other sources that provide information as to the stability of different banks on a regular basis. Making this fact a central piece of messaging in all advertising will go far. The second is to proactively target retail customers and business prospects with potentially large balances. Many of these wealthier people and businesses are looking to diversify the number of banks with whom they do business to better protect their assets in uncertain times. Actively targeting these people with special rates and promotions is a solid way to win extra business and grow it over time. However, understand that there is still competition given the number of banks still in good shape. The determinant of success is mounting an effective, aggressive, and sustained campaign in your local market place. Copyright © 2009 Numerical Alchemy, Inc. 6
  7. 7. For More Information This has been a free report by the folks at Numerical Alchemy, Inc. Specialized individual reports on over 8300 different financial institutions are available upon request for a nominal fee. For more information, please contact: Bill Cassill Numerical Alchemy, Inc. 425.996.8732 Office Copyright © 2009 Numerical Alchemy, Inc. 7
  8. 8. About Numerical Alchemy, Inc. Numerical Alchemy is a Seattle based data mining consultancy with experience in predictive analytics and other advanced techniques that help drive insight and value from company’s customer and research data. Since 2006, Numerical Alchemy has consulted with financial services clients like Bank of America, Wachovia, Washington Mutual, and ING Direct on projects ranging from sophisticated customer research to predictive analytics and anti-money laundering systems. Numerical Alchemy offers a host of low cost but effective analytical services that increase cross sell, reduce customer churn and fraud activity, and enable highly targeted customer acquisition strategies. If you would like more information on what Numerical Alchemy can do for your business, contact us at: This is Bill Cassill, the President and owner of Numerical Alchemy, Inc. Bill Cassill Numerical Alchemy, Inc. 425.996.8732 Office Copyright © 2009 Numerical Alchemy, Inc. 8