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Bank Failures

Structure

The model employed was a top-down structure. The focus of the decision tree is to find states where bank failures are most probable. It, therefore, defines a model where; the liquidity of the bank defines their stability. The more stable a bank, the less likely it is to fail. Using Asset to deposit ratios and further non - current assets to loss ratio will give the best estimate of the stability of different banks in a multitude of states. These three variables will be the major determinants through which the model will be used in determining the nature of the Bank Failures.

Documentation

Different banks have in the past failed. This is often characterized by their inability to meet depositor money. When a bank receives money from a prospective client, often than not, they decide to use the money deposited in investment projects. Should they be in a position to meet the obligations to their depositors, then they are continuing operations, however, in the event, their investments do not return favorable profits, a bank may lose its stability and be declared to have failed (Bruce, 2017). A bank may also be unable to meet its obligations to its creditors. Such instance often leads to an unstable economic and financial environment and have in the past led to the need for banks to receive bailouts through which they can meet their obligations to their depositors (Bruce, 2017). For this analysis, a summary, of different states and the corresponding failures was used to determine the trends between bank failures and states.

To determine the probability of a bank being capable of offsetting some of its debt, the first comparison that will be made will be the ratio between the assets the bank holds, and the total amount made in deposits. This should give a rough estimate of the capacity of the bank to meet its obligations to its main clientele. The higher the ratio, the more stable the bank. Secondly, the banks capacity to mitigates itself from loss is another measure that can be used to determine the stability of the bank. The difference between the Assets and amount Deposited can give a good picture of the overall liquidity of the company. With this figure, finding its ratio against the losses incurred in the last fiscal year (2016) can give a good picture of the stability of the bank and hence the overall probability of it incurring losses.

Evaluation

Data on Bank Failures between 2010 and 2017 was used as the primary information on the trends in bank failures. From the analysis, nine states appear to have experienced a lot of failures over the past seven years ("FDIC: HSOB Commercial Banks," 2017). The states of Arizona, California, Florida, Georgia, Illinois, Minnesota, Missouri, South Carolina, and Washington have noted the highest propensity of bank failures. Georgia ranked the highest with a total of 61 bank failures in this period. Florida then followed with 56 bank failures and then Illinois with 44("FDIC: HSOB Commercial Banks," 2017). Looking at the ratio between assets and deposit for these three banks, all were above 1, which is a sign of stability. However, the banks in Georgia and Illinois recorded significantly lower ratios. The state of Georgia had the least with 1.07("FDIC: HSOB Commercial Banks," 2017). It is important to note that states like Connecticut, Idaho, and Minnesota also recorded low Asset/Deposit ratios.

The second measure of overall failure was to determine the ratio between the difference between the banks capacity to liquidate its assets and the losses that it made. This would make for a clearer picture of the stability of the bank as a recent figure was used in this instance. From the analysis, Connecticut recorded the lowest figure at 0.07("FDIC: HSOB Commercial Banks," 2017). Still, comparatively, the number of deposits for the state was significantly lower compared to that of Georgia. It can be difficult to predict the geographical location of banks that will experience the most loss in the future. It, however, can be assumed that the states of Georgia, Florida, and Illinois present the largest risk for bank failures ("FDIC: HSOB Commercial Banks," 2017). Consequently, states like Connecticut and Minnesota present some of the tales of a dwindling trust and investment into local banks. These states, therefore, present with the highest risk.

To summarize the steps are followed, first, the data is pulled from the site provided by Federal Deposit Insurance Corporation that includes the summary of assets, deposits and loses in banks across fifty different states in the United States. Following that, the ratio of assets/deposits per state, and assets-deposits to loss are used to determine the stability of the banks in different states. As the decision model presents in relation with the defined ratio for stability, banks that scored a ratio above 1.1 in the first instance (assets/deposit ratio) are considered relatively stable, and therefore, they are the ones identified as not likely to fail (see Appendix A for decision tree model). The financial ratio above 1.1 indicates that the banks in the specified area can meet their obligations to depositors, since they have more assets than they do deposits. However, the banks that score below the figure were at a high risk of failing. In the excel attachment, ‘’I’’ and ‘’J’’ columns provide the clear picture of the rational state by state. (see Appendix B for excel analysis). The financial ratio, which is below 1.1, shows that the bank is barely capable of meetings its obligations to depositors, and following that this is considered as not a good sign and a clue of failure.

References

Bruce, L. (2017). What happens to your accounts if the bank fails?. Retrieved from https://www.bankrate.com/banking/what-happens-if-your-bank-fails/