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Due to the growing complexity and unpredictability of contemporary markets as evidenced by the financial crisis of the past ten years, the field of financial distress prediction (FDP) research is receiving more attention. For creditors, investors, and other stakeholders to make well-informed decisions on their financial relationships with a given entity, financial distress prediction is essential. This paper identified the risk indicators that are the cause of financial distress and latest tools and methods to predict financial distress with identifying the risk management strategies for eradicate the distress condition. In this context, this study explores the landscape of the literature published in this area.  We have used systematic and bibliometric approach for studying the existing literature. For the study, we have collected articles from the Scopus database for the period 1985 to 2022. Science mapping technique has been used for the analysis data has been conducted with the help of Vosviewer and Biblioshiny software. Various important component of a literature review like most relevant authors, most relevant sources, keywords co-occurrence network, thematic analysis and others have been explored. The study will help the scholars and future researchers in getting a comprehensive understanding and insights in the concerned field and add to the existing body of literature.

This study analyses the cost of financial distress of non-financial firms listed on the Pakistan stock exchange. Furthermore, it considers the moderating role of concentrated ownership in the relationship between debt and expected financial distress costs. We used the panel data of 214 firms from 2010 to 2018 to analyse the results. We apply fixed effect model to test the hypotheses. We find that ex-ante financial distress costs are based not only on the probability of financial distress but also affect the amount of time and money spent during the distress period. The use of tangible fixed assets and long-term leverage lowers the cost of financial distress, whereas the use of short-term debt has no significant impact on the cost of financial distress. Furthermore, the company's ownership structure dampens the impact of these factors. Corporate management may reduce the cost of financial distress through better management of fixed assets and financial leverage.

The tremendous impact of the coronavirus pandemic on the global aviation industry has led to many cases of airline financial distress and bankruptcy. The Asia–Pacific region (APAC) contains more than half of the world’s population, and its airlines had the highest profit margin of any region. In this study, we investigate whether corporate sustainability practice can reduce the financial distress risk of air carriers, and, if so, what would the effect be in APAC? We first examine the relationship between environmental, social, and governance disclosure and the likelihood of financial distress of airlines as measured by the Altman Z″-score. Second, we analyze the moderating role of being an APAC airline in this relationship. The findings support the claim that implementing environmental actions may increase financial distress risk, and by improving social and governance activities, airlines can mitigate the risk of financial distress. The negative influence of the environmental pillar and the positive influence of the social pillar can be smaller for APAC airlines. Our study provides empirical evidence of the influence of environmental, social, and governance (ESG) on the likelihood of financial distress in the airline industry. Moreover, we analyze the moderating role of being an APAC airline in the relationship between sustainability and financial distress. This study has significant implications for executives, managers, and policymakers in the aviation industry on ESG strategy decisions and the general issue of sustainability.

Purpose The purpose of this study is to present the evidence of the association between financial statement comparability and corporate financial distress. Design/methodology/approach This is an empirical study, and this study uses multiple regression analysis to evaluate hypothesis. Findings The authors find a significant decrease in the probability of financial distress as accounting comparability increases. Findings of this study suggest that distressed firms tend to produce financial statements that compare poorly to those of peer firms; the effectiveness of predicting financial distress with accounting ratios may be conditional on comparability with peers; and financial statement comparability may be predictive of financial distress. Research limitations/implications First, this study only used publicly available financial data, which may not be representative of all countries and could differ because of differences in accounting practices. Second, although this study found a connection between accounting comparability and financial distress, it cannot prove a causal relationship, as other factors that were not controlled for may also have an impact. Third, this study used various measures of financial distress, but other measures could lead to different results. Finally, this study did not include all relevant variables, such as industry-specific factors and macroeconomic conditions, which could influence the relationship between accounting comparability and financial distress. Practical implications For investors and financial analysts, the results imply that accounting comparability can serve as a useful signal for identifying companies that are more likely to remain financially stable in the long run. Thus, they may prefer to invest in or recommend highly comparable firms over their less comparable counterparts. For auditors, this study underscores the importance of promoting and enforcing accounting standards that improve comparability, as this can help mitigate the risk of financial distress among their clients. Regulators may also consider the implications of the study’s findings when designing policies and guidelines related to financial reporting and disclosure. Originality/value To the best of the authors’ knowledge, this is the first study investigating the association between financial statement comparability and corporate financial distress of the US firms. This study uses large, comprehensive and multi-year data. Furthermore, this is the only study that presents the evidence of negative association between comparability and firm financial distress.

Ireland’s policy approach to personal insolvency went through sudden changes in 2012 after a lengthy period of stability. This article presents the findings of a study examining one of the remedies introduced with the Personal Insolvency Act 2012 (as amended), the Debt Relief Notice (DRN). The study examined the DRN’s effectiveness in addressing the financial well-being of over-indebted individuals. The results revealed a reduction in participants’ financial distress after obtaining a DRN, which in turn enabled increased control over day-to-day finances. Improved health, increased resourcefulness, and lifestyle improvements were also identified when the participants’ financial distress was reduced. However, participants were incapable of attaining long-term financial resilience, and, therefore, were unable to achieve high financial well-being. A negative impact on social mobility was also identified as an outcome. The short-term impact identified is similar to findings of earlier research (Stamp, 2012) examining Ireland’s previous policy approach to personal insolvency.

Purpose This study aims to analyze whether and how a set of financial ratios calculated on the basis of financial statement information would allow auditors of Italian local governments (LGs) to get an indication of LGs’ financial distress risk and, hence, to support politicians and managers in promptly detecting financial distress. Design/methodology/approach A model comprising a set of financial indicators that would distinguish distressed from not distressed LGs through a logistic regression approach has been estimated and applied to Italian LGs. The model is built on the basis of information pertaining to 44 distressed and 53 not distressed LGs for up to five years prior to bankruptcy and covers the period 2003-2012. Findings The model reveals that the percentage of personnel expenses over revenues, the turnover ratio of short-term liabilities over current revenues and the reliance on subsidies (calculated as subsidies per capita) are factors discriminating non-distressed LGs from the distressed ones. Practical implications The model could have political and practical implications. The possible use of this model as a complementary tool in auditing activities might be helpful for auditors in detecting financial distress promptly, thus potentially enabling politicians and managers to search for different ways to manage public resources to avoid the detrimental consequences related to the declaration of distress. Originality/value This model, contrary to existing models that use accrual accounting data, is applicable to LGs that adopt a modified cash accounting basis.

Early studies on financial distress prediction (FDP) seldom consider the problem of industry's relative financial distress concept drift and neglects how to dynamically predict industry's relative financial distress. This paper proposes a novel model for dynamic prediction of relative financial distress based on imbalanced data stream of certain industry, and the whole model is divided into the three submodules: the financial feature selection module based on plus-L-minus-R approach, the financial condition evaluation module based on principal component analysis, and the FDP modeling module based on SMOTEBoost-SVM/DT/KNN/Logistic. After feature selection, the results of industry financial condition evaluation are used as class labels for industry's relative FDP modeling, and the model keeps updating with time window sliding on. The empirical experiment is carried out based on the financial ratio data of Chinese iron and steel companies listed in Shanghai and Shenzhen Stock Exchange, and the results indicate the effectiveness of the dynamic model for industry's relative FDP.

This study explores the association between earning management practices and financial distress in commercial banks. Earning management is measured through discretionary loan loss provisions and non-discretionary loan loss provisions. Modified Altman’s Z-score has been used as a proxy for financial distress. Panel regression with fixed and random effect has been employed for empirical analysis. The study finds a significant positive association between DLLP, NDLLP and financial distress in terms of the Altman Z-score. In the case of NDLLP, liquidity reduces the probability of financial distress. Whereas, a bank’s SIZE, LEVG and AQ enhance the likelihood of financial distress. The robustness tests were applied to find the association between NDLLP and FD using logistic regression to validate baseline estimates results of the random effect model. The findings of this study have implications for the policymakers, regulators and internal stakeholders to devise effective regulatory measures for well-informed investment decisions.

Unstable economic conditions have an adverse impact on the financial performance of firms, leading to financial distress, which is an unfavourable situation for investors as it may affect their investment returns. Thus, this study attempted to predict financial distress and to examine the effect of financial distress on stock returns by using firms listed on Bursa Malaysia from 1990 to 2020. This study used the logit model to find the probability of bankruptcy and also as a proxy for financial distress risk in the asset pricing model. From this study, financial distress risk was found to be insignificant in pricing stock returns in all tested models. This finding demonstrates that financial distress risk does not affect stock returns since this risk may be eliminated through diversification.

Financial ratios play an important role in revealing corporate financial soundness, a role which helps to maintain the competitive position of an enterprise, with the achievement of stable development contributing to the elimination of potential financial risks. This paper aims to analyse and compare financial ratios used in the models of transition countries. The analysis focuses on the prediction of the future financial development of a particular enterprise as well as the determination of potential dependencies among the nation in consideration of financial ratios and country of origin. More than 400 prediction models of the Slovak Republic, the Czech Republic, Poland, Hungary, Romania, Lithuania, Latvia, Estonia, Croatia, Russia, Ukraine and Belarus were analysed. The crucial significance of financial ratios in divergent conditions is revealed using a cluster analysis, categorical data and a correspondence analysis. The cluster analysis identified similarities among three groups of countries: i) Belarus, Estonia, Croatia and Latvia; ii) Lithuania, Russia, Hungary and Ukraine, and iii) Czech Republic, Slovakia, Romania and Poland. The results of the correspondence analysis indicate that the individual groups of countries prefer different financial ratios in developing models of prediction of financial distress, differences which arose as a consequence of common changing political, market and economic conditions within each group of nations. In contrary to results suggested by our findings, the most frequently used financial ratios in the prediction models throughout the countries remain current ratio, total-liabilities-to-total-assets ratio, and total-sales-to-total-assets ratio.