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Learning risk culture of banks using news analytics

Author

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  • Agarwal, Arvind
  • Gupta, Aparna
  • Kumar, Arun
  • Tamilselvam, Srikanth G.

Abstract

Risk culture is arguably a leading contributor to risk outcomes of a firm. We define risk culture indicators based on unstructured news data to develop a qualitative assessment of risk culture of banks. For US banks participating in an annual stress test program, we conduct a supervised learning ridge regression analysis to identify the most significant features to evaluate banks’ risk culture characteristics. These features are used for unsupervised clustering to determine the high to low quality of risk culture. The distinct groups obtained from clustering define and allow monitoring changes in the quality of risk culture in banks.

Suggested Citation

  • Agarwal, Arvind & Gupta, Aparna & Kumar, Arun & Tamilselvam, Srikanth G., 2019. "Learning risk culture of banks using news analytics," European Journal of Operational Research, Elsevier, vol. 277(2), pages 770-783.
    • Handle: RePEc:eee:ejores:v:277:y:2019:i:2:p:770-783
    DOI: 10.1016/j.ejor.2019.02.045
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    References listed on IDEAS

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    1. Dervis Kirikkaleli & Pelin Yaylali & Okan Veli Safakli, 2020. "The Perception and Culture of Operational Risk in the Banking Sector: Evidence From Northern Cyprus," SAGE Open, , vol. 10(4), pages 21582440209, October.
    2. Matteo Cinelli & Valerio Ficcadenti & Jessica Riccioni, 2021. "The interconnectedness of the economic content in the speeches of the US Presidents," Annals of Operations Research, Springer, vol. 299(1), pages 593-615, April.
    3. Beatriz Fernández-Muñiz & José Manuel Montes-Peón & Camilo José Vázquez-Ordás, 2022. "The influence of organizational climate, incentives and knowledge sharing on misconduct and risk-taking in banking," Risk Management, Palgrave Macmillan, vol. 24(1), pages 55-80, March.
    4. Semeyutin, Artur & Kaawach, Said & Kara, Alper, 2023. "CEO risk-culture, bank stability and the case of the Silicon Valley Bank," Economics Letters, Elsevier, vol. 233(C).
    5. Ghafoori, Eraj & Mata, Fernanda & Lauren, Nita & Faulkner, Nick & Tear, Morgan J., 2023. "Measuring risk culture in finance: Development of a comprehensive measure," Journal of Banking & Finance, Elsevier, vol. 148(C).
    6. Stevenson, Matthew & Mues, Christophe & Bravo, Cristián, 2021. "The value of text for small business default prediction: A Deep Learning approach," European Journal of Operational Research, Elsevier, vol. 295(2), pages 758-771.
    7. Matteo Cinelli & Valerio Ficcadenti & Jessica Riccioni, 2020. "The interconnectedness of the economic content in the speeches of the US Presidents," Papers 2002.07880, arXiv.org.
    8. Gao, Renzhi & Yao, Xiaoyu & Wang, Zhao & Abedin, Mohammad Zoynul, 2024. "Sentiment classification of time-sync comments: A semi-supervised hierarchical deep learning method," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1159-1173.

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