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Using the Logistic Regression Statistical Test to Determine Which of the Forty National Credit Union Administration's Mandated Financial Ratios are Good Predictors of Credit Union Failure

Posted on:2019-12-21Degree:Ph.DType:Dissertation
University:Northcentral UniversityCandidate:Atchley, Curtis WFull Text:PDF
GTID:1479390017989622Subject:Accounting
Abstract/Summary:
Credit unions, much like banks and other financial institutions, provide financial services to their customers. Although the financial services provided to customers by both credit unions and banks are similar, the method by which these institutions operate are completely different. Banks are for-profit institutions and can freely operate much like other for-profit entities with the objective of generating profit. Credit unions operate as non-profit institutes and are bound to the regulations as defined by the Credit Union Act of 1934. This act stipulates that because credit unions can operate as non-profit institutions, they can only provide financial services to its owners, or otherwise known as members, and credit unions can only generate income via the financial services provided to those members. Due to this income generating limitation, credit unions must be very careful to avoid downward financial trends because resources are limited to reverse these downward trends. As such, the National Credit Union Administration mandates that 40 financial ratios must be created by all reporting credit unions to monitor their financial health; however, even with these 40 financial ratios being monitored, credit unions are still failing. Therefore, a quantitative study was created where logistic regression was used to determine which of the 40 financial ratios were statistically significant in predicting those credit unions that had actually failed. The objective of this study was to identify which of these 40 financial ratios had the potential of being good predictors of credit union failures. If a specific list of financial ratios could be developed, this could be a valuable tool in identifying credit unions with downward trends and allowing corrective actions to be implemented early enough to prevent these distressed credit unions from failing.
Keywords/Search Tags:Credit, Financial, Good predictors, Logistic regression, Downward trends, Institutions
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