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Press news and social media in credit risk assessment: the experience of Banca d’Italia’s In-house Credit Assessment System

Author

Listed:
  • Giulio Gariano

    (Bank of Italy)

  • Gianluca Viggiano

    (Bank of Italy)

Abstract

This article uses press news and Twitter messages to improve the predictive power of the ICAS rating model of Banca d’Italia. We construct two credit sentiment indicators that display a good discriminating power and marginally increase the discriminating power of the ICAS. Scores based on press news prove more effective than those based on Twitter messages.

Suggested Citation

  • Giulio Gariano & Gianluca Viggiano, 2022. "Press news and social media in credit risk assessment: the experience of Banca d’Italia’s In-house Credit Assessment System," Temi di discussione (Economic working papers) 24, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:misp_024_22
    as

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    File URL: https://www.bancaditalia.it/pubblicazioni/mercati-infrastrutture-e-sistemi-di-pagamento/approfondimenti/2022-024/N.24-MISP.pdf
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    References listed on IDEAS

    as
    1. Tsai, Feng-Tse & Lu, Hsin-Min & Hung, Mao-Wei, 2016. "The impact of news articles and corporate disclosure on credit risk valuation," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 100-116.
    2. Filippo Giovannelli & Alessandra Iannamorelli & Aviram Levy & Marco Orlandi, 2020. "The In-house credit assessment system of Banca d'Italia," Questioni di Economia e Finanza (Occasional Papers) 586, Bank of Italy, Economic Research and International Relations Area.
    3. Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
    4. Lara Cathcart & Nina M. Gotthelf & Matthias Uhl & Yining Shi, 2020. "News sentiment and sovereign credit risk," European Financial Management, European Financial Management Association, vol. 26(2), pages 261-287, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    credit sentiment; corporate default; social networks; natural language processing;
    All these keywords.

    JEL classification:

    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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