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Bank Rating Definition
Bank Rating refers to a formula developed by the Federal Deposit Insurance Corporation (FDIC) to rate the safety and soundness of banks, thrifts, and other financial institutions. The Formula used for bank rating is CAMELS, an acronym that represents the capital of the bank, asset quality, management, earnings, liquidity, and sensitivity to risk.
The bank rating uses a rating system on a scale of 1 to 5, the rating also used alphabetical ranking. If a bank or thrift institution has a rating of 1 to 2, it means the bank is sound.
A Little More on What is Bank Rating
Bank ratings or CAMELS ratings are not released to the public by FDIC, these ratings are high-class information not meant for public consumption. Also, it is not only the FDIC that rates financial institutions, there are other rating services for the safety and soundness of banks.
If a financial institution gets a rating of 1 and 2, it means it is in a sound condition while 3 indicates an average condition. 4 to 5 rating on the CAMELS scale tells that the bank or financial institution has serious fundamental problems that need to be checked by regulatory bodies. A rating of 5 is rarely given, except in cases where the bank or financial institution is absolutely prone to fail or collapse in the nearest time.
Bank Rating and Examples of CAMELS Criteria
There are different rating services and agencies, each agency may give a rating different from others. While the common criteria used for reading banks and financial institutions is CAMELS, there are some other criteria used by other agencies.
According to the CAMELS standard, there are clear cut criteria that must be considered when reading banks. There are six of them, they are:
- C – Bank’s capital
- A – Asset quality
- M – Management
- E – Earnings
- L – Liquidity
- S – Sensitivity to risk.
All these criteria are important when rating a financial institution.
Reference for “Bank Rating”
Academics research on “Bank Rating”
A multicriteria decision support system for bank rating, Doumpos, M., & Zopounidis, C. (2010). A multicriteria decision support system for bank rating. Decision Support Systems, 50(1), 55-63. Bank rating refers to the analysis of a bank’s overall viability, performance and risk exposure. Within the recent financial turmoil, bank rating has become extremely important. Typically, bank rating is performed through empirical procedures that combine financial and qualitative data into an overall performance index. This paper presents a case study on the implementation of a multicriteria approach to bank rating. The proposed methodology is based on the PROMETHEE II method implemented in an integrated decision support system. Special emphasis is put on the sensitivity of the results with regard to the relative importance of the evaluation criteria and the parameters of the evaluation process.
The sovereign-bank rating channel and rating agencies’ downgrades during the European debt crisis, Alsakka, R., ap Gwilym, O., & Vu, T. N. (2014). The sovereign-bank rating channel and rating agencies’ downgrades during the European debt crisis. Journal of International Money and Finance, 49, 235-257. We investigate the rating channel for the transmission of changes in sovereign risk to the banking sector, analysing data from Moody’s, S&P and Fitch before and during the European debt crisis. Sovereign rating downgrades and negative watch signals have strong effects on bank rating downgrades in the crisis period. The impact is stronger for multiple-notch sovereign rating downgrades, and more pronounced in PIIGS countries. Secondly, we investigate rating agencies’ competition in the banking sector during the same periods, finding significant differences in rating policies across the agencies. S&P credit actions tend to be the more independent ones, while Moody’s appears to be more cautious, although it is by far the most likely to assign multiple-notch downgrades. In the pre-crisis period, we find no evidence that bank rating actions are linked to sovereign rating signals (nor vice versa) nor to prior bank rating changes by a competing agency.
Using differential evolution to improve the accuracy of bank rating systems, Krink, T., Paterlini, S., & Resti, A. (2007). Using differential evolution to improve the accuracy of bank rating systems. Computational Statistics & Data Analysis, 52(1), 68-87. Credit rating is the evaluation of the likelihood of an obligor to default on a loan. Each obligor in the bank’s credit portfolio is assigned to a certain rating class, or PD (probability of default) bucket; all obligors in a PD bucket then receive the same “pooled” PD, based on which a capital charge against credit risk must be computed. The only analytical approach to this problem is based on k-means and has some limitations in practice. An error minimization approach to credit rating using differential evolution (DE) is introduced. The performances of DE and other common search heuristics are compared using credit rating data of a major Italian bank. Empirical results show that DE is clearly superior compared to a genetic algorithm (GA), particle swarm optimization (PSO), random search (RS) and two naı¨ve partitioning approaches. Moreover, the proposed approach obtained better results than k-means in much less runtime for a simplified instance of the problem where within-groups variances can be used for clustering.
Asymmetric benchmarking in bank credit rating, Shen, C. H., Huang, Y. L., & Hasan, I. (2012). Asymmetric benchmarking in bank credit rating. Journal of International Financial Markets, Institutions and Money, 22(1), 171-193. This study proposes an information asymmetry hypothesis to examine why bank credit ratings vary among countries even when bank financial ratios remain constant. Countries are divided among those with low and high information asymmetry. The former include high-income countries, those in North America and West Europe regions, and those with strong institutional environment quality, whereas the latter group possess the opposite characteristics. This study hypothesizes that the influences of financial ratios on ratings are enhanced in low information asymmetry countries but reduced in countries with high information asymmetry. The sample includes the long-term credit ratings issued by Standard and Poor’s from 86 countries during 2002–2008. The estimated results show that the effects of financial ratios on ratings are significantly affected by information asymmetries. Countries wishing to improve the credit ratings of their banks thus should reduce information asymmetry.
The impact of sovereign rating actions on bank ratings in emerging markets, Williams, G., Alsakka, R., & Ap Gwilym, O. (2013). The impact of sovereign rating actions on bank ratings in emerging markets. Journal of Banking & Finance, 37(2), 563-577. This paper analyses the effects of sovereign rating actions on the credit ratings of banks in emerging markets, using a sample from three global rating agencies across 54 countries for 1999–2009. Despite widespread attention to sovereign ratings and bank ratings, no previous study has investigated the link in this manner. We find that sovereign rating upgrades (downgrades) have strong effects on bank rating upgrades (downgrades). The impact of sovereign watch status on bank rating actions is much weaker and often insignificant. The sensitivity of banks’ ratings to sovereign rating actions is affected by the countries’ economic and financial freedom and by macroeconomic conditions. Ratings of banks with different ownership structures are all influenced strongly by the sovereign rating, with some variation depending on the countries’ characteristics. Emerging market bank ratings are less likely to follow sovereign rating downgrades during the recent financial crisis period.