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Learning risk culture of banks using news analytics

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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. Samuel Ronnqvist & Peter Sarlin, 2015. "Detect & Describe: Deep learning of bank stress in the news," Papers 1507.07870, arXiv.org.
    2. Roxana Mihet, 2013. "Effects of culture on firm risk-taking: a cross-country and cross-industry analysis," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(1), pages 109-151, February.
    3. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Villupuram, Sriram, 2014. "Currency jumps, cojumps and the role of macro news," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 42-62.
    4. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2016. "Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.
    5. Chernobai, Anna & Jorion, Philippe & Yu, Fan, 2011. "The Determinants of Operational Risk in U.S. Financial Institutions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(6), pages 1683-1725, December.
    6. Edward H. Bowman, 1984. "Content Analysis of Annual Reports for Corporate Strategy and Risk," Interfaces, INFORMS, vol. 14(1), pages 61-71, February.
    7. Sung C. Bae & Kiyoung Chang & Eun Kang, 2012. "Culture, Corporate Governance, And Dividend Policy: International Evidence," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 35(2), pages 289-316, June.
    8. Tim Loughran & Bill McDonald, 2014. "Regulation and financial disclosure: The impact of plain English," Journal of Regulatory Economics, Springer, vol. 45(1), pages 94-113, February.
    9. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    10. Power, Michael & Ashby, Simon & Palermo, Tommaso, 2013. "Risk culture in financial organisations: a research report," LSE Research Online Documents on Economics 67978, London School of Economics and Political Science, LSE Library.
    11. Bodnaruk, Andriy & Loughran, Tim & McDonald, Bill, 2015. "Using 10-K Text to Gauge Financial Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(4), pages 623-646, August.
    12. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    13. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
    14. Ying Zhang & Peggy E. Swanson & Wikrom Prombutr, 2012. "Measuring Effects On Stock Returns Of Sentiment Indexes Created From Stock Message Boards," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 35(1), pages 79-114, March.
    15. Tsai, Ming-Feng & Wang, Chuan-Ju, 2017. "On the risk prediction and analysis of soft information in finance reports," European Journal of Operational Research, Elsevier, vol. 257(1), pages 243-250.
    16. Balakrishnan, Ramji & Qiu, Xin Ying & Srinivasan, Padmini, 2010. "On the predictive ability of narrative disclosures in annual reports," European Journal of Operational Research, Elsevier, vol. 202(3), pages 789-801, May.
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    Cited by:

    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. 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).
    5. 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.
    6. 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.

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