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Machine learning and credit risk: Empirical evidence from small- and mid-sized businesses

Author

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  • Bitetto, Alessandro
  • Cerchiello, Paola
  • Filomeni, Stefano
  • Tanda, Alessandra
  • Tarantino, Barbara

Abstract

In this paper, we compare two different approaches to estimate the credit risk for small- and mid-sized businesses (SMBs), namely a classic parametric approach, by fitting an ordered probit model, and a non-parametric approach, calibrating a machine learning historical random forest (HRF) model. The models are applied to a unique and proprietary dataset comprising granular firm-level quarterly data collected from a European investment bank and an international insurance company on a sample of 464 Italian SMBs over the period 2015–2017. Results show that the HRF approach outperforms the traditional ordered probit model, highlighting how advanced estimation methodologies that use machine learning techniques can be successfully implemented to predict SMB credit risk, i.e. when facing high asymmetries of information. Moreover, by using Shapley values, we are able to assess the relevance of each variable in predicting SMB credit risk.

Suggested Citation

  • Bitetto, Alessandro & Cerchiello, Paola & Filomeni, Stefano & Tanda, Alessandra & Tarantino, Barbara, 2023. "Machine learning and credit risk: Empirical evidence from small- and mid-sized businesses," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:soceps:v:90:y:2023:i:c:s0038012123002586
    DOI: 10.1016/j.seps.2023.101746
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    Keywords

    Credit rating; SMB; Historical random forest; Machine learning; Relationship banking; Invoice lending;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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