IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v75y2025ics1544612325000443.html

Impact of judgment readability on financial crimes

Author

Listed:
  • Pathak, Jalaj

Abstract

Using NLP techniques, we extract the financial judgments from the overall set of supreme court judgments and find a one-unit increase in readability, implying harder-to-comprehend supreme court judgments, is significantly associated with a 2% increase in financial crimes for the next year. The results hold true for different categories of financial crimes and are robust to the other proxies for readability. This is in line with the theories of how the comprehensibility of the judgments often leaves scope for debate and calls for easier-to-read and comprehensible judgments so that such loopholes can be avoided.

Suggested Citation

  • Pathak, Jalaj, 2025. "Impact of judgment readability on financial crimes," Finance Research Letters, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:finlet:v:75:y:2025:i:c:s1544612325000443
    DOI: 10.1016/j.frl.2025.106779
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325000443
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2025.106779?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Fang, Bin & Ye, Qiang & Kucukusta, Deniz & Law, Rob, 2016. "Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics," Tourism Management, Elsevier, vol. 52(C), pages 498-506.
    2. Ayse Imrohoroglu & Antonio Merlo & Peter Rupert, 2004. "What Accounts For The Decline In Crime?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(3), pages 707-729, August.
    3. Mahambare, Vidya & Pathak, Jalaj, 2021. "Differential impact of diversity in policy communication," Economics Letters, Elsevier, vol. 209(C).
    4. Mauro Costantini & Iris Meco & Antonio Paradiso, 2018. "Do inequality, unemployment and deterrence affect crime over the long run?," Regional Studies, Taylor & Francis Journals, vol. 52(4), pages 558-571, April.
    5. Pazzona, Matteo, 2024. "Revisiting the Income Inequality-Crime Puzzle," World Development, Elsevier, vol. 176(C).
    6. 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.
    7. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 48(5), pages 1049-1102, December.
    8. Neha Bansal & Arun Sharma & R. K. Singh, 2019. "Fuzzy AHP approach for legal judgement summarization," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(3), pages 323-340, July.
    9. Leo Katz, 2010. "A Theory of Loopholes," The Journal of Legal Studies, University of Chicago Press, vol. 39(1), pages 1-31, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
    2. Jiao Ji & Oleksandr Talavera & Shuxing Yin, 2018. "The Hidden Information Content: Evidence from the Tone of Independent Director Reports," Working Papers 2018-28, Swansea University, School of Management.
    3. Alastair Marais, 2024. "Audit Quality and Financial Statement Manipulation: The Moderating Effect of Tone at the Top," International Journal of Economics and Financial Issues, Econjournals, vol. 14(5), pages 220-232, September.
    4. Yingying Xin & Xiao Zeng & Zhengying Luo, 2022. "Customers' tone in MD&A disclosure and suppliers' inventory efficiency: Evidence from China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(8), pages 3833-3853, December.
    5. Liu, Pu & Nguyen, Hazel T., 2020. "CEO characteristics and tone at the top inconsistency," Journal of Economics and Business, Elsevier, vol. 108(C).
    6. Ahmed, Yousry & Elshandidy, Tamer, 2016. "The effect of bidder conservatism on M&A decisions: Text-based evidence from US 10-K filings," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 176-190.
    7. Liebmann, Michael & Orlov, Alexei G. & Neumann, Dirk, 2016. "The tone of financial news and the perceptions of stock and CDS traders," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 159-175.
    8. Todd, Andrew & Bowden, James & Cummins, Mark & Su, Yang, 2025. "A multimodal sentiment classifier for financial decision making," International Review of Financial Analysis, Elsevier, vol. 105(C).
    9. Allen H. Huang & Jianghua Shen & Amy Y. Zang, 2022. "The unintended benefit of the risk factor mandate of 2005," Review of Accounting Studies, Springer, vol. 27(4), pages 1319-1355, December.
    10. Özgür Arslan‐Ayaydin & James Thewissen & Wouter Torsin, 2021. "Disclosure tone management and labor unions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 102-147, January.
    11. Jiwoo Seo & Adam Esplin & Yun Ke, 2025. "CEO political ideology and risk factor disclosure," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 65(2), pages 1468-1496, June.
    12. Diego Téllez & Maximiliano Gonz�lez & Alexander Guzm�n & Mar�a Andrea Trujillo, 2017. "What do you say and how do you say it: Information disclosure in Latin American firms," Documentos de Trabajo de Valor Público 16358, Universidad EAFIT.
    13. Yingzhao Ni, 2024. "Media coverage and disclosure of short‐termism tone: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(S1), pages 5107-5131, December.
    14. Raphael Müller & Johannes Voget & Jan Zental, 2024. "The Effects of Mandatory Private Disclosure On Public Disclosure—Evidence from CbCR," Schmalenbach Journal of Business Research, Springer, vol. 76(4), pages 533-571, December.
    15. James P. Ryans, 2021. "Textual classification of SEC comment letters," Review of Accounting Studies, Springer, vol. 26(1), pages 37-80, March.
    16. Sanjiv Das & Xin Huang & Soji Adeshina & Patrick Yang & Leonardo Bachega, 2023. "Credit Risk Modeling with Graph Machine Learning," INFORMS Joural on Data Science, INFORMS, vol. 2(2), pages 197-217, October.
    17. Mohamed Malek Belhoula & Naima Lassoued & Imen Khanchel & Dorsaf Ghraidi, 2026. "Beyond numbers: negative disclosure tone, bank risk, and ownership structure in Middle East and North African Banks," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 23(1), pages 224-239, March.
    18. An, Suwei, 2023. "Essays on incentive contracts, M&As, and firm risk," Other publications TiSEM dd97d2f5-1c9d-47c5-ba62-f, Tilburg University, School of Economics and Management.
    19. Renato Camodeca & Alex Almici & Umberto Sagliaschi, 2018. "Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach," Sustainability, MDPI, vol. 10(12), pages 1-34, November.
    20. Berkin, Anil & Aerts, Walter & Van Caneghem, Tom, 2023. "Feasibility analysis of machine learning for performance-related attributional statements," International Journal of Accounting Information Systems, Elsevier, vol. 48(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:75:y:2025:i:c:s1544612325000443. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.