IDEAS home Printed from https://ideas.repec.org/a/bla/acctfi/v63y2023i4p3781-3795.html
   My bibliography  Save this article

From natural language to accounting entries using a natural language processing method

Author

Listed:
  • Yasheng Chen
  • Xian Huang
  • Zhuojun Wu

Abstract

Bookkeeping is crucial in both accounting and auditing. However, a substantial quantity of accounting information initially recorded using unstructured natural language, which restricts the efficiency and accuracy of bookkeeping. In this study, we exploit proprietary transaction data from three firms to demonstrate the capacity of a word embedding approach based on a neural network model (i.e., Word2vec) for processing transaction‐related natural language and automating bookkeeping practice. Our study contributes to accounting practice and literature by demonstrating a practical application of Word2vec to the construction of an automated bookkeeping system.

Suggested Citation

  • Yasheng Chen & Xian Huang & Zhuojun Wu, 2023. "From natural language to accounting entries using a natural language processing method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 3781-3795, December.
    • Handle: RePEc:bla:acctfi:v:63:y:2023:i:4:p:3781-3795
    DOI: 10.1111/acfi.13067
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/acfi.13067
    Download Restriction: no
    File URL: https://libkey.io/10.1111/acfi.13067?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
    ---><---

    References listed on IDEAS

    as
    1. Aishah Sheikh Abu Bakar & Rashid Ameer, 2011. "Readability of Corporate Social Responsibility communication in Malaysia," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 18(1), pages 50-60, January.
    2. Beakcheol Jang & Inhwan Kim & Jong Wook Kim, 2019. "Word2vec convolutional neural networks for classification of news articles and tweets," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-20, August.
    3. Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2020. "Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 199-235, March.
    4. Kai Li & Feng Mai & Rui Shen & Xinyan Yan, 2021. "Measuring Corporate Culture Using Machine Learning [Machine learning methods that economists should know about]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3265-3315.
    5. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    6. Yanjian Zhu & Zhaoying Wu & Hua Zhang & Jing Yu, 2017. "Media sentiment, institutional investors and probability of stock price crash: evidence from Chinese stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1635-1670, December.
    7. Xiong Xiong & Chunchun Luo & Ye Zhang & Shen Lin, 2019. "Do stock bulletin board systems (BBS) contain useful information? A viewpoint of interaction between BBS quality and predicting ability," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1385-1411, March.
    8. Angela K. Davis & Jeremy M. Piger & Lisa M. Sedor, 2012. "Beyond the Numbers: Measuring the Information Content of Earnings Press Release Language," Contemporary Accounting Research, John Wiley & Sons, vol. 29(3), pages 845-868, September.
    9. Lynnette Purda & David Skillicorn, 2015. "Accounting Variables, Deception, and a Bag of Words: Assessing the Tools of Fraud Detection," Contemporary Accounting Research, John Wiley & Sons, vol. 32(3), pages 1193-1223, September.
    10. Lu Jiao & Graeme Harrison & Jinhua Chen & Kym Butcher, 2021. "Does emotional intelligence matter to academic work performance? Evidence from business faculties in Australia," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 1181-1204, March.
    11. Tom Marty & Bruce Vanstone & Tobias Hahn, 2020. "News media analytics in finance: a survey," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1385-1434, June.
    12. Gibbins, M, 1984. "Propositions About The Psychology Of Professional Judgment In Public Accounting," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 103-125.
    13. Huang, Feiqi & Vasarhelyi, Miklos A., 2019. "Applying robotic process automation (RPA) in auditing: A framework," International Journal of Accounting Information Systems, Elsevier, vol. 35(C).
    14. 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.
    15. Angela K. Davis & Isho Tama†Sweet, 2012. "Managers’ Use of Language Across Alternative Disclosure Outlets: Earnings Press Releases versus MD&A," Contemporary Accounting Research, John Wiley & Sons, vol. 29(3), pages 804-837, September.
    16. Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 237-291, March.
    17. 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.
    18. Kai Li & Feng Mai & Rui Shen & Xinyan Yan, 2021. "Measuring Corporate Culture Using Machine Learning," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3265-3315, National Bureau of Economic Research, Inc.
    19. Vicky Arnold, 2018. "The changing technological environment and the future of behavioural research in accounting," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(2), pages 315-339, June.
    20. Malcolm Smith & Richard Taffler, 1992. "Readability and Understandability: Different Measures of the Textual Complexity of Accounting Narrative," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 5(4), pages 1-1, December.
    21. Gus De Franco & Ole†Kristian Hope & Dushyantkumar Vyas & Yibin Zhou, 2015. "Analyst Report Readability," Contemporary Accounting Research, John Wiley & Sons, vol. 32(1), pages 76-104, March.
    22. Mark Johnman & Bruce James Vanstone & Adrian Gepp, 2018. "Predicting FTSE 100 returns and volatility using sentiment analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 253-274, November.
    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. Xin Xu & Feng Xiong & Zhe An, 2023. "Using Machine Learning to Predict Corporate Fraud: Evidence Based on the GONE Framework," Journal of Business Ethics, Springer, vol. 186(1), pages 137-158, August.
    2. 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).
    3. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    4. Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.
    5. 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.
    6. Kothari, Pratik & Chance, Don M. & Ferris, Stephen P., 2021. "Bragging rights: Does corporate boasting imply value creation?," Journal of Corporate Finance, Elsevier, vol. 67(C).
    7. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
    8. Andrei Filip & Gerald J. Lobo & Luc Paugam & Hervé Stolowy, 2022. "Disclosures About Key Value Drivers in M&A Announcement Press Releases: An Exploratory Study," Abacus, Accounting Foundation, University of Sydney, vol. 58(1), pages 62-104, March.
    9. Liu, Qigui & Wang, Junyi & Chi, Wenqiang, 2022. "The spillover effects of innovation content disclosure in MD&A," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    10. Mather, Paul & Ranasinghe, Dinithi & Unda, Luisa A., 2021. "Are gender diverse boards more cautious? The impact of board gender diversity on sentiment in earnings press releases," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(3).
    11. Huimin (Amy) Chen & Bill B. Francis & Tahseen Hasan & Qiang Wu, 2022. "Does corporate culture impact audit pricing? Evidence from textual analysis," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(5-6), pages 778-806, May.
    12. 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).
    13. Christina Bannier & Thomas Pauls & Andreas Walter, 2019. "Content analysis of business communication: introducing a German dictionary," Journal of Business Economics, Springer, vol. 89(1), pages 79-123, February.
    14. Jason V. Chen & Itay Kama & Reuven Lehavy, 2019. "A contextual analysis of the impact of managerial expectations on asymmetric cost behavior," Review of Accounting Studies, Springer, vol. 24(2), pages 665-693, June.
    15. Bassyouny, Hesham & Abdelfattah, Tarek & Tao, Lei, 2022. "Narrative disclosure tone: A review and areas for future research," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 49(C).
    16. Peter M. Clarkson & Jordan Ponn & Gordon D. Richardson & Frank Rudzicz & Albert Tsang & Jingjing Wang, 2020. "A Textual Analysis of US Corporate Social Responsibility Reports," Abacus, Accounting Foundation, University of Sydney, vol. 56(1), pages 3-34, March.
    17. Kanagaretnam, Kiridaran & Mawani, Amin & Shi, Guifeng & Zhou, Zejiang, 2020. "Impact of social capital on tone ambiguity in banks’ 10-K filings," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    18. Bassyouny, Hesham & Abdelfattah, Tarek & Tao, Lei, 2020. "Beyond narrative disclosure tone: The upper echelons theory perspective," International Review of Financial Analysis, Elsevier, vol. 70(C).
    19. Bakarich, Kathleen M. & Hossain, Mahmud & Hossain, Mahmud & Weintrop, Joseph, 2019. "Different time, different tone: Company life cycle," Journal of Contemporary Accounting and Economics, Elsevier, vol. 15(1), pages 69-86.
    20. 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.

    More about this item

    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:bla:acctfi:v:63:y:2023:i:4:p:3781-3795. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaanzea.html .

    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.