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This paper aims to outline how certain lessons from ethical systems can be relevant and applicable to tackling unethical behavior, including financial crime, within the finance profession.

This paper adopts a pragmatic perspective while acknowledging that there is a myriad of reasons managers act unethically, including the reality that many do so knowingly and deliberately. The matter is further complicated by human nature, given an individual’s behavior (ethical or unethical) is not easily discernable from their psychological, sociological, theological or cultural attributes.

Although such systems may not solve the problem of corrupt behavior, research suggests that industry professionals can learn to act in a more responsible and ethical manner. Given the wounded reputation of the financial sector, owing to their role in committing financial crimes such as money laundering, advances in ethical conduct would elevate both the effectiveness of the sector, as well as its reputation.

It is impractical to think we can completely resolve the problem of unethical behavior. Improvement, however, seems possible through promoting virtuous character traits and ethical behavior in individuals and organizations. Virtue ethics can play a significant role in combating financial crime and supporting anti-money laundering initiatives.

The prevention of fraudulent activities, particularly within a financial context, is of paramount significance in all spheres, as it not only impacts the sustainability of corporate entities but also has the potential to have a broader economy-wide impact. This paper aims to focus on dual implications associated with financial distress, the first being associated with the temptation to launder funds due to financial distress, and the second being the potential for illicit activities, such as fraud, money laundering or terror financing, to give rise to financial distress.

The paper examines the literature on financial distress and uses theories of financial crime to establish a link between financial distress and financial crime.

In recent years, there has been a surge in corporate financial distress, particularly in the aftermath of concurrent crises such as the COVID-19 pandemic and the Russia–Ukraine war. Through a comprehensive examination of literature pertaining to financial distress and financial crime, this study identifies a proclivity towards fraudulent conduct arising from instances of financial distress. Moreover, the engagement in such illicit activities subsequently exacerbates the financial distress. An analysis of the relationship between financial crime and financial distress reveals the existence of a vicious cycle between the two.

The results of this study have the potential to advance understanding of the relationship between financial distress and financial crime, which has been previously underexplored.

This paper aims to investigate technological innovations within the crypto space that have engendered novel financial crime risks and their potential utilization amidst geopolitical conflicts.

The theoretical paper uses an analysis of recent geopolitical events, with a key focus on using cryptocurrencies to undertake illicit activities.

The study found that cryptocurrencies and the innovations made within the crypto domain are used for both legitimate and illicit purposes, including money laundering, terrorism financing and sanction evasion.

This research contributes to understanding the critical role cryptocurrencies play amidst geopolitical conflicts and emphasizes the need for regulatory considerations to prevent their misuse. To the best of the authors’ knowledge, this paper is the first scholarly contribution that considers the evolving mechanisms afforded by cryptocurrencies amidst geopolitical conflicts in undertaking illicit activities.

Financial distress is a socially and economically important problem that affects companies the world over. Having the power to better understand – and hence aid businesses from failing, has the potential to save not only the company, but also potentially prevent economies from sustained downturn. Although Islamic banks constitute a fraction of total banking assets, their importance have been substantially increasing, as their asset growth rate has surpassed that of conventional banks in recent years. The paper aims to discuss these issues.

This paper uses a data set comprising 101 international publicly listed Islamic banks to work on advancing financial distress prediction (FDP) by utilising cutting-edge stochastic models, namely decision trees, stochastic gradient boosting and random forests. The most important variables pertaining to forecasting corporate failure are determined from an initial set of 18 variables.

The results indicate that the “Working Capital/Total Assets” ratio is the most crucial variable relating to forecasting financial distress using both the traditional “Altman Z-Score” and the “Altman Z-Score for Service Firms” methods. However, using the “Standardised Profits” method, the “Return on Revenue” ratio was found to be the most important variable. This provides empirical evidence to support the recommendations made by Basel Accords for assessing a bank’s capital risks, specifically in relation to the application to Islamic banking.

These findings provide a valuable addition to the limited literature surrounding Islamic banking in general, and FDP pertaining to Islamic banking in particular, by showcasing the most pertinent variables in forecasting financial distress so that appropriate proactive actions can be taken.

The purpose of this study is to test whether the prediction of firm performance can be enhanced by incorporating nonfinancial disclosures, such as narrative disclosure tone and corporate governance indicators, into financial predictive models.

Three predictive models are developed, each with a different set of predictors. This study utilises two machine learning techniques, random forest and stochastic gradient boosting, for prediction via the three models. The data are collected from a sample of 1,250 annual reports of 125 nonfinancial firms in Pakistan for the period 2011–2020.

Our results indicate that both narrative disclosure tone and corporate governance indicators significantly add to the accuracy of financial predictive models of firm performance.

Our results offer implications for the restoration of investor confidence in the highly uncertain Pakistani market by establishing nonfinancial disclosures as reliable predictors of future firm performance. Accordingly, they encourage investors to pay more attention to these disclosures while making investment decisions. In addition, they urge regulators to promote and strengthen the reporting of such nonfinancial information.

This study addresses the neglect of nonfinancial disclosures in the prediction of firm performance and the scarcity of corporate governance literature relevant to the use of machine learning techniques.