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This paper aims to examine the impact of corruption and money laundering (ML) on the profitability and stability of Islamic banks.

This study used the data of 53 conventional and 19 Islamic banks of Pakistan and Malaysia to have comparative insights. The empirical methods include the fixed effect and random effect regression and generalized methods of moment for robust results.

The results indicate that Islamic banks gain from corruption and ML. Corruption and ML affect bank profitability and stability positively in a less corrupt environment, i.e. Malaysia; however, corruption hurts Islamic banks’ performance, and ML favours Islamic banking profitability and stability in a more corrupt environment, i.e. Pakistan.

The present study pioneers the debate on corruption and ML related to Islamic banking profitability and stability. This study provides important insights to regulators and Shariah advisors to build a real model of Islamic banking.

This research aims to examine the impact of money laundering (ML) and corruption on the asset quality of conventional and Islamic banks.

The current study used the data of conventional and Islamic banks of Pakistan from 2012 to 2018. In this study, we used fully modified ordinary least squares, dynamic ordinary least squares and pooled ordinary least square methods to analyze the data.

The results found that corruption and ML positively affect the conventional banking non-performing loans (NPLs). In contrast, corruption and ML harm the Islamic bank’s loan portfolio quality.

To the best of the authors’ knowledge, the relationship between corruption, ML and NPLs in conventional and Islamic banks of Pakistan are examined for the first time.

According to the study’s findings, bank authorities should establish an effective method for monitoring loan activities and developing new and innovative products in Islamic banks. Additionally, the Pakistani government needs to improve anti-corruption and anti-ML policies to earn investors’ trust.

Many studies of corruption and money laundering (ML) have been conducted throughout the previous few decades. The impact of corruption and ML on economic growth, banking performance and corporate financial performance has been the focus of various research. The present study aims to investigate the relationship between ML, corruption and inflation.

This study used the panel data of five South Asian countries from 2013 to 2019 (Pakistan, India, Bangladesh, Sri Lanka and Nepal). Further, fixed effect (FE) and random effect (RE) econometric regression models are used to analyze the data. Additionally, generalized methods of moment (GMM) technique is used to check the results robustness.

This study discovered that corruption and ML have a significant and positive link with inflation in five South Asian nations using the corruption perception index and the anti-money laundering (AML) index.

This research advises that government authorities strengthen anti-corruption and AML laws enforcement.

To the best of the authors’ knowledge, this is the first paper that explains the linkage between corruption, ML and inflation in five south Asian nations.

The purpose of this paper is to address the effect of corruption and money laundering (ML) on banking profitability and stability.

This study uses the panel data of 72 banks of Pakistan and Malaysia from 2012–2018. This paper uses fixed effect (FE) and random effect (RE) regression techniques for empirical testing and generalized methods of moment (GMM) technique for robustness tests.

This study founds consistent evidence that corruption has a positive and ML has a negative relationship with the banking profitability of Pakistan and Malaysia while the empirical evidence suggests that corruption and ML have a diverse impact on the banking stability of Pakistan and Malaysia. Further, this paper also founds that corruption and ML moderates the relationship between risk and banking profitability and stability.

The results reveal that the banks of the highly corrupt environment are more affected by corruption and ML than the least corrupt environment. Thus, it is recommended that the Government of Pakistan should formulate strong anti-corruption and anti-money laundering policies.

As per the knowledge of the authors, this research contributes to understanding the role of corruption and money laundering on the stability and profitability of Pakistan and, in general, it is the first attempt investigating the moderating role of corruption and ML between risk and banking profitability and stability.