Over the past several years the changes in regulations have transformed the landscape for public funds. On the one hand it has increased the attractiveness of public funds for community banks and has also increased the management challenges for state Treasurers. The largest banks currently hold the majority of the public fund deposits in the U.S. according to FDIC data. With the implementation of the Basel III Liquidity Coverage Ratio (LCR) these deposits become less attractive to the large banks given the run-off rate calculations required by LCR and requirement for collateralization. While public funds are less attractive for the large institutions they remain very attractive for the community banks that are not affected by LCR.
On the other hand state treasury operations are faced with the challenges of having a standardized collateral requirement, uninsured exposure, the task of developing a risk adjusted methodology for setting collateral based on the financial strength of each individual banking institution or working with the banks in the state to develop pooled collateral requirements.
One of the key challenges is how to assess the financial strength of each banking institution. Often we see State Treasurers use ratings or rating-type services. While ratings are useful they are not enough. We have always believed in a multiple models approach with total transparency by providing a highly detailed technical guide. Others use Credit Default Swap (CDS) spreads as a measure of risk but make the mistake of trying to infer default probabilities from these quotes. Further only a handful of banks have traded CDS and based on DTCC data for the week ended September 23, 2016 only three US Banks had actual trades.
In 2014 Kamakura introduced its U.S. Bank Default Model. The Kamakura model is a modern “reduced form” quantitative default probability model that complements the KRIS public firm model. This allows a user to see the risk differential between the parent holding company and the insured depository. The user also can determine whether the parent is a source of strength for the bank. The bank model incorporates 17 explanatory variables including 11 financial ratios and 6 macro factors from the Fed CCAR test. The factors include measures of the quality of capital, loan concentration, asset quality, liquidity, management efficiency and earnings. The model incudes a term structure of default which provides the user with a forward-looking view of the risk of term funds. Examples of both can be seen below with the chart comparing Bank of America Corporation to Bank of America National Association and looking at the term structure of default for Well Fargo Bank National Association.
Use of these models are not only beneficial in managing deposit risk and monitoring and managing collateral levels but also can assist Treasurers in the management of short term investments, counterparty risk, and develop methodologies to prevent “wrong way” risk with respect to counterparty risk and collateral value inderivative transactions.
Modern quantitative default probabilities like those provided by Kamakura Risk Information Services are essential tools for bank credit risk assessment. Information on KRIS default probabilities for publicly listed bank holding companies is available here:
KRIS default probabilities have become the best practice tool for bank credit assessment. Prof. Robert A. Jarrow, Managing Director of Research at Kamakura, was the lead author of the FDIC’s 2003 Loss Distribution Model, which is based on the reduced form approach to credit risk assessment. The Office of the Comptroller of the Currency made the announcement on February 18, 2012 that it had renewed its contract for default probabilities from Kamakura Corporation for another five years:
Why have organizations with responsibility for supervising the riskiness of financial institutions turned so heavily toward modern default probabilities like the KRIS service? The answer is best summarized by the following chart that compares the accuracy and granularity of KRIS default probabilities with legacy credit ratings:
The KRIS default probabilities are based on the best statistical analysis available. “Ratings,” by contrast, are described as “expert judgment” credit assessment tools. Quantitative analysis is a complement to fundamental analysis and provides an unbiased approach to risk management.
For more information on default probability models, please contact us at email@example.com.