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

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  • 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
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