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Discovering bank risk factors from financial statements based on a new semi‐supervised text mining algorithm

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Listed:
  • Lu Wei
  • Guowen Li
  • Xiaoqian Zhu
  • Jianping Li

Abstract

This paper aims to comprehensively uncover bank risk factors from qualitative textual risk disclosures reported in financial statements, which contain a huge amount of information on bank risks. We propose a new semi‐supervised text mining approach named naive collision algorithm to analyse the textual risk disclosures, which can more accurately identify bank risk factors compared with the typical unsupervised text mining approach. We identified 21 bank risk factors in total, which is far more than identified in previous studies. We further analyse the importance of each bank risk factor and how the importance of each risk factor changes over time.

Suggested Citation

  • Lu Wei & Guowen Li & Xiaoqian Zhu & Jianping Li, 2019. "Discovering bank risk factors from financial statements based on a new semi‐supervised text mining algorithm," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(3), pages 1519-1552, September.
    • Handle: RePEc:bla:acctfi:v:59:y:2019:i:3:p:1519-1552
    DOI: 10.1111/acfi.12453
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    Cited by:

    1. Wei, Lu & Miao, Xiyuan & Jing, Haozhe & Liu, Zhidong & Xie, Zezhong, 2023. "Bank risk aggregation based on the triple perspectives of bank managers, credit raters, and financial analysts," Finance Research Letters, Elsevier, vol. 57(C).
    2. Blum, Avinoam & Raviv, Alon, 2023. "The effects of the financial crisis and Basel III on banks’ risk disclosure: A textual analysis," Finance Research Letters, Elsevier, vol. 53(C).
    3. Li, Jianping & Li, Jingyu & Zhu, Xiaoqian & Yao, Yinhong & Casu, Barbara, 2020. "Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S," International Review of Financial Analysis, Elsevier, vol. 71(C).
    4. Li, Jingyu & Yao, Yanzhen & Li, Jianping & Zhu, Xiaoqian, 2019. "Network-based estimation of systematic and idiosyncratic contagion: The case of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
    5. Liu, Mingxi & Li, Guowen & Li, Jianping & Zhu, Xiaoqian & Yao, Yinhong, 2021. "Forecasting the price of Bitcoin using deep learning," Finance Research Letters, Elsevier, vol. 40(C).
    6. Lu Wei & Chen Han & Yinhong Yao, 2022. "The Bias Analysis of Oil and Gas Companies’ Credit Ratings Based on Textual Risk Disclosures," Energies, MDPI, vol. 15(7), pages 1-12, March.
    7. Li, Jianping & Feng, Yuyao & Li, Guowen & Sun, Xiaolei, 2020. "Tourism companies' risk exposures on text disclosure," Annals of Tourism Research, Elsevier, vol. 84(C).
    8. Yu Zhao & Huaming Du & Qing Li & Fuzhen Zhuang & Ji Liu & Gang Kou, 2022. "A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data Perspective," Papers 2211.14997, arXiv.org, revised May 2023.
    9. Qing L. Burke & Terry D. Warfield, 2021. "Bank interest rate risk management and valuation of earnings," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4287-4337, September.
    10. Salman Bahoo & Marco Cucculelli & Xhoana Goga & Jasmine Mondolo, 2024. "Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis," SN Business & Economics, Springer, vol. 4(2), pages 1-46, February.
    11. Li, Jianping & Li, Guowen & Liu, Mingxi & Zhu, Xiaoqian & Wei, Lu, 2022. "A novel text-based framework for forecasting agricultural futures using massive online news headlines," International Journal of Forecasting, Elsevier, vol. 38(1), pages 35-50.
    12. Wei, Lu & Li, Guowen & Li, Jianping & Zhu, Xiaoqian, 2019. "Bank risk aggregation with forward-looking textual risk disclosures," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    13. Xiaoqian Zhu & Yinghui Wang & Jianping Li, 2022. "What drives reputational risk? Evidence from textual risk disclosures in financial statements," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
    14. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
    15. Jianping Li & Yinhong Yao & Yuanjie Xu & Jingyu Li & Lu Wei & Xiaoqian Zhu, 2019. "Consumer’s risk perception on the Belt and Road countries: evidence from the cross-border e-commerce," Electronic Commerce Research, Springer, vol. 19(4), pages 823-840, December.
    16. Zhu, Xiaoqian & Wei, Lu & Li, Jianping, 2021. "A two-stage general approach to aggregate multiple bank risks," Finance Research Letters, Elsevier, vol. 40(C).
    17. Yuyao Feng & Guowen Li & Xiaolei Sun & Jianping Li, 2022. "Identification of tourists’ dynamic risk perception—the situation in Tibet," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    18. Li, Jingyu & Li, Jianping & Zhu, Xiaoqian, 2020. "Risk dependence between energy corporations: A text-based measurement approach," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 33-46.

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