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How inefficient is an inefficient credit process? An analysis of the Italian banking system

Author

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  • Peter Cincinelli
  • Domenico Piatti

Abstract

Purpose - The paper aims to disentangle the physiological credit risk from the credit risk coming from the inefficient screening and monitoring management process. The analysis is conducted on a sample of 338 Italian banks–56 joint-stock banks (SpA), 23 cooperative banks (Popolari) and 259 mutual banks (BCCs)–over the time period 2006–2017. Design/methodology/approach - The authors use the maximum likelihood method to estimate the efficient frontier, as a set of best management credit practices, which minimises the credit risk defined on the basis of the level of loans granted, the technical structure of the loan portfolio (such as credit lines, mortgages, consumer loans and other technical loan categories) and the interest rate charges. Findings - The empirical results show that the increase in non-performing loans (NPLs) is related both to the severe and protracted recession in Italy, which significantly reduced borrowers' capacity to service their debt, and to other factors, such as banks' lending monitoring policies with limited capacity to work-out defaulted loans. Originality/value - The authors propose a new approach to the study of the performance of the credit process. With the stochastic frontier, the physiological credit risk, assumed by the bank according to its lending activity and management choices, is separated from the credit risk resulting from an inefficient management of the screening and monitoring process. In addition, the authors analyse the determinants of the excess of NPLs. This aspect is considered particularly original because the scientific contributions which consider the causes of NPLs have largely focused on the level of NPLs not considering the physiological part, linked to the structure of the bank's loan portfolio and its operational strategy and therefore not compressible and in any case not attributable to mismanagement or moral hazard.

Suggested Citation

  • Peter Cincinelli & Domenico Piatti, 2021. "How inefficient is an inefficient credit process? An analysis of the Italian banking system," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 22(3/4), pages 209-239, July.
  • Handle: RePEc:eme:jrfpps:jrf-08-2020-0184
    DOI: 10.1108/JRF-08-2020-0184
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    Citations

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    Cited by:

    1. Polina Popova, 2024. "COVID-19, Corporate Non-performing Loans, and Corporate Lending Dynamics: Evidence from Russian Regions," HSE Working papers WP BRP 93/FE/2024, National Research University Higher School of Economics.
    2. Du, Yuqiu & Wang, Wendi, 2023. "The role of green financing, agriculture development, geopolitical risk, and natural resource on environmental pollution in China," Resources Policy, Elsevier, vol. 82(C).
    3. Mirza, Nawazish & Umar, Muhammad & Afzal, Ayesha & Firdousi, Saba Fazal, 2023. "The role of fintech in promoting green finance, and profitability: Evidence from the banking sector in the euro zone," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 33-40.
    4. Li, Zhuolun, 2023. "Do geopolitical risk, green finance, and the rule of law affect the sustainable environment in China? Findings from the BARDL approach," Resources Policy, Elsevier, vol. 81(C).

    More about this item

    Keywords

    Banking industry; Credit monitoring; Stochastic frontier; Italian banks; Lending inefficiency; C14; C33; G21; G30;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

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