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Exploring the role of corruption and money laundering (ML) on bank’s loan portfolio quality: a cross-country investigation

Author

Listed:
  • Nadir Hussain
  • Salman Masood Sheikh
  • Ijaz Hussain Shah

Abstract

Purpose - Corruption and money laundering (ML) are severe concerns for both developing and developed countries. According to international organizations, such as Transparency International, the Basel Institute on Governance and the International Country Risk Guide, corruption and ML exist in every country. This research aims to investigate the impact of corruption and ML on the loan portfolio quality of banks. Design/methodology/approach - From 2013 to 2019, this study used the panel data of 132 countries, including 87 highly corrupt and 45 least corrupt countries: the fixed effect and random effect econometric regression techniques for data analysis. Additionally, this study used the generalized methods of moment technique to check the result’s robustness. Findings - This study shows that corruption and ML have diverse relationships with non-performing loans in highly corrupt and low corrupt countries. It is potentially because of the differences in the regulatory structure of a highly corrupt and least corrupt environment. Originality/value - To the best of the authors’ knowledge, this study is the first attempt that provides a unique perspective on corruption, ML and its effect on the loan’s portfolio quality of banks. Furthermore, this study suggests that governments in highly corrupt environments develop robust anti-corruption and anti-ML regulations.

Suggested Citation

  • Nadir Hussain & Salman Masood Sheikh & Ijaz Hussain Shah, 2021. "Exploring the role of corruption and money laundering (ML) on bank’s loan portfolio quality: a cross-country investigation," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 30(3), pages 265-281, December.
  • Handle: RePEc:eme:jfrcpp:jfrc-10-2021-0086
    DOI: 10.1108/JFRC-10-2021-0086
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    More about this item

    Keywords

    Corruption; Money laundering; Non-performing loans; Random effect; Fixed effect; C33; D73; G2; G21; G28; G32;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • G2 - Financial Economics - - Financial Institutions and Services
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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