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Credit Scoring in SME Asset-Backed Securities: An Italian Case Study

Author

Listed:
  • Andrea Bedin

    (Research Center SAFE, Goethe University, 60323 Frankfurt am Main, Germany)

  • Monica Billio

    (Department of Economics, Ca’ Foscari University of Venice, 30121 Venice, Italy)

  • Michele Costola

    (Research Center SAFE, Goethe University, 60323 Frankfurt am Main, Germany)

  • Loriana Pelizzon

    (Research Center SAFE, Goethe University, 60323 Frankfurt am Main, Germany
    Department of Economics, Ca’ Foscari University of Venice, 30121 Venice, Italy)

Abstract

We investigate the default probability, recovery rates and loss distribution of a portfolio of securitised loans granted to Italian small and medium enterprises (SMEs). To this end, we use loan level data information provided by the European DataWarehouse platform and employ a logistic regression to estimate the company default probability. We include loan-level default probabilities and recovery rates to estimate the loss distribution of the underlying assets. We find that bank securitised loans are less risky, compared to the average bank lending to small and medium enterprises.

Suggested Citation

  • Andrea Bedin & Monica Billio & Michele Costola & Loriana Pelizzon, 2019. "Credit Scoring in SME Asset-Backed Securities: An Italian Case Study," JRFM, MDPI, vol. 12(2), pages 1-28, May.
    • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:2:p:89-:d:232160
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    References listed on IDEAS

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    Cited by:

    1. Pranith Kumar Roy & Krishnendu Shaw & Alessio Ishizaka, 2023. "Developing an integrated fuzzy credit rating system for SMEs using fuzzy-BWM and fuzzy-TOPSIS-Sort-C," Annals of Operations Research, Springer, vol. 325(2), pages 1197-1229, June.
    2. Yusuf Priyo Anggodo & Abba Suganda Girsang, 2024. "A Novel Modified Binning and Logistics Regression to Handle Shifting in Credit Scoring," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2371-2403, June.
    3. Iryna Yanenkova & Yuliia Nehoda & Svetlana Drobyazko & Andrii Zavhorodnii & Lyudmyla Berezovska, 2021. "Modeling of Bank Credit Risk Management Using the Cost Risk Model," JRFM, MDPI, vol. 14(5), pages 1-15, May.
    4. Pranith Kumar Roy & Krishnendu Shaw, 2021. "A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    5. Pazhouhi , Asrar & Marzban , Hossein & Dehghan Shabani , Zahra & Moradi , Javad, 2020. "The Effects of Asset Securitization on Banks' Performances (Case Study: Bank Saderat Iran 2005-2015)," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(1), pages 1-24, January.
    6. David Edmund Allen & Elisa Luciano, 2019. "Risk Analysis and Portfolio Modelling," JRFM, MDPI, vol. 12(4), pages 1-4, September.
    7. Chrysovalantis Gaganis & Panagiota Papadimitri & Fotios Pasiouras & Menelaos Tasiou, 2023. "Social traits and credit card default: a two-stage prediction framework," Annals of Operations Research, Springer, vol. 325(2), pages 1231-1253, June.

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    More about this item

    Keywords

    credit scoring; probability of default; small and medium enterprises; asset-backed securities;
    All these keywords.

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • E - Macroeconomics and Monetary Economics
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • G - Financial Economics

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