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The study aims to evaluate the financial distress position of selected sample banks in India. The top 10 banks with the highest levels of gross non-performing assets (NPA) under both public and private sector ownerships have been chosen for the study. Application of the Altman Z-score model has been used to compare both ownership banks’ financial distress for five years from 2017 to 2021. Based on the study’s findings, it was found that private sector banks demonstrated better financial stability than their public sector counterparts. Specifically, the average Z-score of the selected sample banks was higher than the safe zone threshold of 2.9 during the study period.

The literature has revealed auditors' going concern risk disclosures are examined in research as a homogenous risk class. This is despite the various going concern modifications auditors are entitled to give pertaining to this issue. A five‐level risk class is established in this paper derived from Australian Auditing Standard pronouncements to examine the appropriateness of auditors' going concern reporting relating specifically to the likelihood of firm failure.

Time is necessary to reveal the appropriateness of going concern reporting therefore a longitudinal research methodology was adopted. The research focuses on all Australian listed companies within the building industry in 1989 and follows all of the reporting of going concern by auditors and directors through until 2007. The building industry was selected because of its volatility, which increased the possibility of going concern reporting allowing a more in‐depth focus in the research. All auditors' going concern modifications were examined along with all indications of going concern problems identified by directors. To properly investigate the appropriateness of auditors' reporting, all sampled audit reports were examined using Altman's Z‐score model which were matched with a risk class model using the relevant requirements to report in order to determine the appropriateness of the auditors' and directors' opinions.

The level of under reporting of going concern risk by auditors (75 per cent) implies they are more affected by the agency relationship found in literature than directors who are found to have an incidence of underreporting of 57 per cent.

Literature classifies auditors along with directors as part of the agency problem. Altman's Z‐score bankruptcy prediction model is used because of its enduring nature, reliability and ability to be externally calculated to independently compare the going concern reporting performance of auditors and directors as part of the contribution to this research area.

The paper for the first time examines going concern reporting at a multi‐risk level rather than the binomial level used in research previously. The approach is developed in this paper using auditing pronouncements. These risk levels are linked with an independent measure being the Altman Z‐score to determine the appropriateness of auditors' and directors' reporting of going concern issues.

The purpose of this paper is to investigate, using data on US manufacturing firms, how and when corporate governance affects managers' decisions to use discretionary accruals and thereby artificially influence company financial reports.

Three‐stage least squares is employed to study the relationship between financial status, corporate governance and financial reporting discretion. The sample spans the years 2001‐2003 during a severe downturn in the US stock market. Financial status is measured with the Altman Z‐score.

A significant difference is found between firms not classified as healthy or failed (i.e. the mid‐range group) and the two extreme categories when examining governance quotient using a well‐known index. A positive relationship is found between discretionary accruals and the governance index. Strong governance appears to reduce the incidence of mid‐range firms engaging in accruals management. The least healthy and the most distressed companies have the weakest relationship with discretionary accruals. By contrast, mid‐range firms are more likely to resort to discretionary accruals.

Non‐executive members of boards of directors are warned to be particularly vigilant about discretionary accruals with firms transitioning between healthy and high‐failure risk.

The relationship between firms' financial health and discretionary accruals reveals an agency problem in credit markets with financially stressed firms. More attention is required on firms whose financial condition is uncertain. Also, it is documented that significant findings of importance to the earnings quality and corporate governance literature by documenting the role of corporate governance on discretionary accruals and financial status.

The increasing incidence of fraudulent financial reporting by firms in recent years raises concerns about investors' confidence in capital markets. Academicians and industry practitioners adopt diverse risk management techniques to detect fraudulent reporting of financial statements. This paper aims to determine the effectiveness of the Beneish M-score and Altman Z-score models for the early detection of material misstatements at Comscore, Inc., a media analytics firm in the United States of America.

The financial statements of Comscore Inc. from 2012 to 2018 were analyzed with the primary objective of early fraud detection by employing the Beneish M-score and the Altman Z-score.

The study’s outcomes indicate that the Beneish M-score is less predictable in fraud detection compared to the Altman Z-score. The study results did not confirm the efficacy of the Beneish model in predicting fraudulent financial statements. The study concludes that the choice of forensic tool greatly influences fraud detection outcomes.

The research findings can guide the policy decision-making of investors, financial auditors, and forensic auditors as this study provides some evidence of the effectiveness of forensic tools in the detection of financial statement fraud in corporate entities.

This is the first study to apply these two widely used tools to the most recent big corporate scandal: Comscore, Inc.

The purpose of this article is to provide commentary on the utility of Altman's Z‐score as a strategic assessment and performance management tool. This possibility is suggested in the recently published book Measuring Organizational Performance – Metrics for Entrepreneurship and Strategic Management Research (Northampton, MA: Edward Elgar, 2006) by Robert B. Carton and Charles W. Hofer.

This paper is a corporate manager's analysis of the utility of Altman's Z‐score as a strategic assessment and performance management tool based on published research, with suggestions for further research.

The analysis supports Carton and Hofer's findings with respect to the utility of the Z‐score as a strategic assessment and performance management tool.

While the Z‐score is both popular and widely used in the fields of credit risk analysis, distressed investing, M&A target analysis, and turnaround management it has received relatively little attention as a strategic assessment and performance management tool. The findings of Carton and Hofer's study, in conjunction with the impressive results achieved by GTI Corporation, suggest that applying the Z‐score in strategy and performance management may also be warranted, especially after more research is undertaken.

This article offers a manager's perspective on new research that indicates the potential of a popular financial distress metric to provide insight in the areas of entrepreneurship and strategic management.

The main purpose of this study is to examine the relationship between credit risk and financial performance in non-financial firms.

In order to test the relationship between Altman Z-score model as a credit risk proxy and the Return on Asset and Equity as indicator for financial performance with control variables leverage, liquidity and firm size. Least Square Dummy Variable regression analysis is opted. This research's sample included 69 non-financial companies from the Pakistan Stock Exchange KSE-100 Index between 2012 and 2017.

This study establishes the findings that Altman Z-score, leverage and firm size significantly impact the financial performance of the KSE-100 non-financial firms. However, liquidity is found to be insignificant in this study. Altman Z-score and firm size have shown a positive relationship to the financial performance, whereas leverage is inversely related.

This study brings in a new and useful insight into the literature on the relationship between credit risk and financial performance. The results of this study provide investors, businesses and managers related to non-financial firms in the KSE-100 index with significant insight about credit risk's impact on performance.

The evidence of the credit risk and financial performance on samples of non-financial firms has not been studied; mainly it has been limited to the banking sector. This study helps in the evaluation of Altman Z-score's performance in the non-financial firms in KSE-100 index as well.

The purpose of this paper is to investigate whether proxies considered under ex ante uncertainty hold true under a fixed price mechanism structure. In particular, the study examines whether pre-initial public offering (IPO) financial performance, measured by Altman Z-score, can serve as a proxy for ex ante uncertainty or signalling in an IPO market where a fixed price mechanism is used to determine the offer price.

This study uses solely ex ante information available to prospective investors prior to the IPO to proxy for ex ante variables. It also applies a more sophisticated and robust approach using quantile regression (QR) technique in addition to ordinary least squares (OLS) regression. Applying the QR technique allows the study to produce estimates for the conditional quantiles of the distribution of IPO initial returns and address the violations of basic assumptions of the standard OLS technique.

The results show that for ex ante variables, such as IPORISK, company size, the Altman Z-score measure of pre-IPO performance, audit quality and the technology industry, are significantly related to IPO initial returns. However, the relationship differs across the conditional quantiles of the distribution of IPO initial returns, which would not have been recognised using standard OLS. However, the sign of the coefficients shown by some of these variables contradicts the ex ante uncertainty hypothesis assumption, but they are found to have predictive power in explaining IPO initial returns. These findings reveal unique characteristics of the IPO process and investors in Malaysia. Most importantly, the Altman Z-score is found to be significant in the lower and upper quantiles, but insignificant around the median quantile, which implies that Altman Z-score is important for IPOs with low and high initial returns.

These findings suggest that theoretical explanations of the ex ante uncertainty hypothesis cannot be generalised across financial markets, particularly in the Malaysian IPO market where fixed price offerings are common, and investors are risk averse, whereby they avoid risky IPOs, and prefer to take a small amount of returns against high risks. In addition, the composition of the companies in the market is not as large as the developed markets. This implies that the share price of the IPO may be sensitive to other disclosures in the prospectus, market sentiments or financial news. This study recommends the need for more empirical evidence for this purpose by including other important proxies of ex ante uncertainty, such as the use of IPO proceeds and risk factors that are disclosed in the prospectus to test whether the ex ante uncertainty hypothesis holds true in Malaysia.

This study fulfils the need for finding an appropriate theory that better explains IPO initial returns in the Asian IPO market by focussing exclusively on the pre-IPO information available in the prospectus. It also sheds light on important selected pre-listing information.

Introduction: Financial failure is a concept that may arise from many internal and external factors such as operational, financial, and economic items and may incur serious losses. Over-indebtedness arising from managerial misjudgments may cause high financial distress, insufficiency, and bankruptcy. In this regard, determination of effects of capital structure decisions on financial failure risk is crucial.

Aim: The main purpose of this study is to explore the relationship between capital structure decisions and financial failure risk. For this purpose, data from Borsa İstanbul (BIST) for listed food and beverage companies for the period from 2004 to 2019 is used. Another purpose of this study is to compare the financial failure models considering capital structure theories.

Method: In the study, capital structure decisions are associated with five different financial ratios; while the financial failure risk is proxied by financial failure scores of Altman (1968), Springate (1978), Ohlson (1980), Taffler (1983), and Zmijewski (1984). Therefore, five different panel data models are used for testing these hypotheses.

Findings: The results of panel data analysis reveal that capital structure decisions have statistically significant effects on financial failure risk for all models; however, those effects vary from one financial failure model to another. Also, the results show that in the models in which financial failure risk is proxied by the Altman (1968) and Taffler (1983) scores, the aggressive financial policies increase the financial failure risk. However, regarding the models in which financial failure risk is proxied by the Springate (1978), Ohlson (1980), and Zmijewski (1984) scores, aggressive financial policies decrease the financial failure risk.

Originality of the Study: To the best of our knowledge, this chapter is original and important in terms of revealing the effects of capital structure decisions on the financial failure risk and comparing the financial failure models.

Implications: The results revealed that the risk of financial failure models represented by Altman (1968) and Taffler (1983) scores are found to be statistically stronger and more successful in meeting theoretical expectations compared to other models. Therefore, it would be more appropriate to refer Altman’s (1968) and Taffler’s (1983) financial failure models in financial failure risk measurements.

We assess the impact of NZ IAS 32 on the financial reporting of convertible financial instruments by retrospective application of the standard to a sample of New Zealand companies over the period 1988 ‐ 2003. NZ IAS 32 has a broader definition of liabilities than does the corresponding current standard (FRS‐31) and it does not permit convertibles to be reported under headings that are intermediate to debt and equity. The results of the study indicate that in comparison with the reported financial position and performance, the reporting of convertibles in accordance with NZ IAS 32 would result in higher amounts for liabilities and higher interest. Thus, analysts using financial statement information to assess risk of financial distress will need to revise the critical values of commonly used measures of risk and performance when companies report under NZ IAS

The purpose of this study is primarily to implement the emerging market (EM) Z‐score model to predict bankruptcy and to measure the financial performance of major Islamic banks in the UAE. In addition, this study aims to introduce the Z‐score model to this industry as a beneficial diagnostic tool for possible causes standing behind the deterioration of financial performance.

The methodology that has been used in this study is based on Z‐score model for EMs developed by Altman. The related studies have proved that Z‐score has more than 80 percent accuracy and verified it is a robust tool and is useful in assessing the business performance and prediction of potential distress of firms. The approach determined in this study is to examine the financial statements of the UAE Islamic banks by calculating the EM Z‐score for the past three years and comparing it with the current year's score as an effort to measure the overall financial performance as well as the likelihood of bankruptcy of the UAE Islamic banks.

The paper finds that UAE Islamic banks should work on improving the ratios that are dragging their scores down to better understand their past performance and realize their current position in the industry; Z‐score can be adopted by the UAE Islamic banks as effective evaluation approach toward financing the potential long‐term partnership projects including small and medium business enterprises (SMEs); Z‐score model can be adapted by Islamic banks as an independent credit risk analysis approach to measure the competencies and financial strengths of potential projects; Islamic banks in the UAE are by and large financially sound and healthy and that Z‐score is a beneficial analytical tool that can be adapted by Islamic banks in the UAE to complement other financial analysis techniques to establish Islamic banking industry averages. The study also finds that the ratios used in calculating Z‐score can be considered to provide valuable instrumental indicators.

Z‐score model is a valid model to measure the performance of Islamic banks and the ratios used in calculating Z‐score can be considered to provide valuable instrumental indicators. Z‐score can be adopted by the UAE Islamic banks to finance long‐term partnership projects and SMEs. Limitations including the Islamic banking industry are still considered small size, which might has negative effect on the maximum outcomes of the study. Future studies are needed toward updating the coefficient values connected to each ratios in Z‐score model as per the inputs from the Islamic banking industry.

Z‐score model is a valid model to measure Islamic banks performance and the ratios used in calculating Z‐score can be considered to provide valuable instrumental indicators. Z‐score can be adopted by the UAE Islamic banks to finance long‐term partnership projects and SMEs.

The model is believed to widen the industry exposure in order to finance more projects and companies which is believed will reflect positively on the society welfare. By adopted Z‐score SMEs will be provided with all financings needed specially providing the microfinance for small projects.

Introducing Z‐score to the Islamic banking industry as crucial credit risk measuring tool.