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The purpose of the current study is to identify variables that, when integrated into the random effects parametric survival model, could be used to forecast the failure rate of small banks in the USA. A bank’s income production, efficiency and costs were taken into consideration when choosing the internal components. The breakout of the financial crisis, bank regulations that affect how the banking sector operates and the federal funds rate are the primary external variables.

This study uses the random effects parametric survival model to investigate the causes of small bank failures in the USA from 1996 to 2019. The study identifies several characteristics that failed banks frequently display. The main indications that may help to identify the elevated risk of small bank failures include the ROA, the cost of funds, the ratio of noninterest income to assets, the ratio of loan and lease losses to assets, noninterest expenses and core capital (leverage) ratio to assets. Economic disruptions, financial market distress and industry-based regulatory redress by the government exacerbate the financial distress borne by small banks.

The study revealed that a failed bank typically demonstrates a certain number of characteristics. The key factors that might assist identify which bank would be most likely to collapse include the cost of funding earning assets, the yield on earning assets, core Capital (leverage) ratio to assets, loan and lease loss provision to assets, noninterest expense and noninterest income to assets. Additionally, when a financial crisis occurs or the government changes regulations that could raise the cost of compliance for small banks, the likelihood that a bank will fail increases.

Models based on survival theories are more suitable when the authors examine bank failure as a unique event that happens gradually. The authors use a random effects parametric survival model to investigate the internal and external factors that may influence prospective small bank failure. This model has been developed and used in the medicinal research field. The authors do not choose the Cox proportional hazards model because it does not work well with panel data.

This study seeks to observe the association between mobile banking failures, use of m-banking and customer engagement to determine the contribution of user satisfaction towards m-banking as mediator between the aforementioned relationship.

This study proposes a Mobile Banking Failure Model (MBFM) by integrating four failure dimensions (functional, system, information and service) based on Tan's failure model and DeLone and Mclean's Information Success model. In this paper, data was gathered from 338 respondents, who were the customers of banks and regular users of m-banking services of their respective banks in India. A survey method was employed to collect data. Structure equation modelling (SEM) was used to analyse the collected data.

The results suggest that all m-banking failure dimensions (functional, system, information and service) affect the use of m-banking, which in turn affects user satisfaction towards m-banking and customer engagement. Additionally, this study found that user satisfaction towards m-banking acts as a partial mediator between the use of m-banking and customer engagement.

The banking failure and its use by customers have been examined in the context of mobile banking in India only and thereby limits the generalization of results to other industry and country contexts.

The results of this paper will guide bank managers and policy planners in implementing MBFM in the Indian banking context, specifically for their m-banking apps.

The use of m-banking, user satisfaction towards m-banking and customer engagement have been added as three supportive variables to the basic Tan's failure model and DeLone and Mclean's Information Success model to examine the impact of m-banking failure on bank customers' usage behaviour. This is a novel addition to the extant literature, as most empirical works in this domain are from industries other than banking (specifically m-banking) and with differing contexts.

Despite scholarly effort to understand customers’ recovery evaluation, little progress is evident in deciphering how customers develop online failure/recovery perception. This paper aims to address this issue.

Social constructivism was the epistemic choice for this study. This approach is holistic and offers a comprehensive understanding of each side of the phenomena. This provided social scientific descriptions of people and their cultural bases and built on, and articulated what was implicit in interpretations of their views.

Online banking customer groups were identified as: exigent customers, solutionist customers and impulsive customers. Customers’ position in each group determined failure perception, recovery expectation and evaluation, and post-recovery behaviour. Comparisons were observed and discussed in relation to Albania and Kosovo. It was suggested that banks should expand their presence in social media platforms and offer a means to manage online customer communication and spread of online WOM.

For exigent customers, the failure/recovery responsibility is embedded within the provider. This explains their high sensitivity and criteria to define a failure.

Online banking customers’ request of a satisfactory recovery experience included: customer notifications, customer behaviour, customer determination, and the mediator of request. 10;Providers should examine customer failure/recovery experiences in cooperation with other banks which should lead to a higher order understanding of customer withdrawal and disengagement activities.

Post-recovery behaviour is linked to the decline of online banking usage, switching to new providers, and the spread of negative online and off-line word-of-mouth.

This is the first empirical study on online service failure and recovery strategy to provide information on customers’ unique preferences and expectations in the recovery process. Online customers are organised into a threefold customer typology, and explanation for the providers’ role in the online customer failure-recovery perception construct is presented.

Motivated by agency theory, this paper aims to explore the impact of bank diversification and bank independency on the likelihood of bank failure. The effects of corporate governance (ownership and board structures) are also examined.

Logistic regressions are used to explore the role of corporate governance on bank failure risk. This sample covers 608 banks from eight European countries.

The results suggest that the well-documented finding that diversification and bank independency may increase bank failure risk does not persist under strong corporate governance mechanism. Thus, to reduce the bank failure risk, diversification should be strongly monitored by the management to avoid excessive risk-taking by shareholders.

The approach used in this study differs from that used in previous studies from certain perspectives. First, unlike most previous studies that focused on the relationship between bank performance and bank diversification, the impact of income and asset diversification on bank failure is tested. Also, the impact of a combined effect of diversification and corporate governance variables on bank failure is tested. This allows the control for different ownership and board variables as factors that would potentially affect the likelihood of bank failure.

This study aims to analyze the factors related to the failure of 535 Federal Deposit Insurance Corporation (FDIC)-Insured United States banks in conjunction with the 2008 financial crisis.

The research consists of an analysis of the following three five-year partitions: pre-crisis (2002–2006), crisis (2007–2011) and post-crisis (2012–2016). The main hypothesis is that the factors explaining bank failures vary by period. Using logistic regression analysis, the authors identify the desirable models by period based on three model selection strategies.

Liquidity and non-risk-based capital ratios are important explanatory factors in all three periods. As the authors can see from the results, when comparing the full period (2002–2016) and the three five-year period partitions (2002–2006, 2007–2011 and 2012–2016), the ratios change from period to period, but they measure the same financial areas of concern in different contexts as follows: liquidity, leverage/risk exposure and capital adequacy. Risk-based capital ratios are not effective predictors of bank failures.

Recent academic studies have analyzed bank failures during periods that cover the years before, during and after the crisis, but most of these studies discuss bank failures in the forecasting context only. This study includes an analysis of failure determinants during pre-crisis, crisis and post-crisis subperiods based on the FDIC monitoring system of bank failures and identifies what ratios are more relevant during each period and how they change from period to period.

This paper aims to examine the characteristics of banks that were the target of intervention in the form of bailout or failure during the financial crisis and, of those subjected to intervention, what characteristics distinguish those that received bailout funds from those that were deemed failures.

The study estimates a series of logit regressions in an effort to identify the causes of regulatory intervention while controlling for bank-level characteristics and the economic and regulatory environment.

The empirical results indicate that many of the same characteristics associated with banks receiving bailout funds are similar to the characteristics associated with failed banks. However, non-performing loans increased the likelihood of failure, but reduced the likelihood of a bank receiving Capital Purchase Program (CPP) funds, suggesting that regulatory authorities discriminated in their use of CPP funds based on the quality of a bank’s asset portfolio. Further, those banks located in states with limits on de novo branching and those banks that are part of a multi-bank holding company structure were less likely to fail but were more likely to receive CPP funds.

This paper provides a comprehensive analysis of regulatory intervention in the banking industry during the late 2000s financial crisis and the impact of different banking organizational structures, economic circumstances, and financial fragility on the likelihood of a bank failing or receiving bailout funds.

This paper aims to examine the impact of charter type (national vs state), holding company structure, and measures of bank fragility on the likelihood of bank failure during the late 2000s financial crisis.

The study estimates a series of logit regressions in an effort to identify the causes of failure and assess the role of the bank‐level characteristics while controlling for the economic and regulatory environment.

The empirical results indicate that established institutions were more likely to fail, dependent upon whether a bank received bailout funds or not, if they were relatively large, had relatively low capital ratios, had relatively low liquidity, relied more heavily on brokered deposits, held a relatively large portfolio of real estate loans, had a relatively large proportion of non performing loans, and had less income diversity. Consistent with being financially fragile, de novo banks and those banks that grew substantially prior to the crisis faced an increased likelihood of failure relative to established banks. However, capital levels were not significantly related to the likelihood of failure in de novo institutions.

This paper provides a comprehensive analysis of the possible business models' impact on the likelihood of failure during the recent financial crisis. It contributes to the ongoing debate regarding appropriate regulatory reform in the banking industry by shedding light on the extent to which the business model decisions made by bank managers have an impact on the stability of the banking system.

Banks' service failures are a major determinant of bank customers' switching behavior, which ultimately affects the profitability and stability of banks. Guided by the expectancy violation theory (EVT), this study aims to examine whether and how bank reputation influences the relationship between service failure and customers' switching behavior in the Malaysian banking industry.

By distributing questionnaires to Malaysian bank account holders, the authors gathered 320 usable responses, which were subsequently subjected to explanatory factor analysis, confirmatory factor analysis, Logit regression, Probit regression and independent-variables T-test to identify and elucidate the relationship existent between the dependent and independent variables.

This study discovered that bank reputation affects the bank customers' switching behavior directly and indirectly via banks' service failure, thereby verifying the application of EVT in the context of customer management.

Although the profile of respondents in this study presents a reasonable representation of the Malaysian population, the use of convenience (non-probability) sampling method via online survey may not provide generalizable results.

This study empirically revealed that bank reputation plays a moderator role between service failure in banks and customers' bank-switching behavior. This observation offers useful insights to bank managers into the role of bank reputation in managing customers' switching behavior.

The purpose of this paper is to identify the causes behind the failures of virtual banks. This work underscores the importance of the differing financial metrics in the virtual and brick and mortar banking channels, when analyzing bank failures.

“Probit” analysis on the failed virtual banks and the failed brick and mortar banks revealed that the interest incomes in both banks are significantly different. The non‐interest income and non‐interest expense (NIE) of the surviving banks and the failed banks are explored to examine the causes for failure.

Similar to previous research it was found that the brick and mortar banks failed due to bad asset quality, but the failure of virtual banks is mainly due to high NIEs. For virtual banks to succeed, the institutions must focus on controlling the burden.

A larger sample size would have been preferable and non‐availability of data limited the scope of the study. Continuing studies could explore the performance of Internet channels of existing brick and mortar banks.

This study accentuates the importance of the differing business models underlying the two banking channels (virtual banks and brick and mortar banks). These channel specific differences underscore the significance of the financial metrics in operational evaluation.

This is probably the first study to examine the causes of failures of virtual banks and contrast them with brick and mortar banks.

The purpose of this paper is to investigate the determinants of the timing of bank failure in North Cyprus over the period of 1984‐2002 using a discrete‐time logistic survival analysis.

The empirical methodology employed in the paper allows for the determination of the factors that influence the time to bank failure. The model links the time of bank failure to a set of bank‐specific factors and macro‐environment that may have exacerbated the internal troubles of the financial institutions.

An empirical examination of the results on survival analysis reveal that the three variables, namely: low asset quality (total loan as a percentage of total assets), low liquidity (total liquid asset as a percentage of total assets), and high credit extended to the private sector (ratio of the private credit to gross domestic product) are the main factors that explain the survival time of banks in North Cyprus.

For further research this paper may better distinguish time to bank failure if it extends the time period and if it uses exchange pressure from Turkey that may have a direct effect on bank failure in North Cyprus.

Nowadays bank failure is an important problem in the world. Using time technique to investigate bank failure will help to learn the factors that determine time to bank failure, which will further help to take precautions and prevent the cost of bank failure.

The analysis would appear to be the first to provide evidence and investigate the time to bank failure in the North Cyprus banking sector.