Fad or Future?:Automated Analysis of Financial Text and its Implications for Corporate Reporting

Lewis, Craig and Young, Steven (2019) Fad or Future?:Automated Analysis of Financial Text and its Implications for Corporate Reporting. Accounting and Business Research, 49 (5). pp. 587-615. ISSN 0001-4788

[thumbnail of Lewis_Young_PD_Leake_Lecture_Nov2018_v12_final]
PDF (Lewis_Young_PD_Leake_Lecture_Nov2018_v12_final)
Lewis_Young_PD_Leake_Lecture_Nov2018_v12_final.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (1MB)


This paper describes the current state of natural language processing (NLP) as it applies to corporate reporting. We document dramatic increases in the quantity of verbal content that are an integral part of company reporting packages as well as the evolution of text analytic approaches that are being employed to analyse this content. We provide intuitive descriptions of the leading analytic approaches that are applied in the academic accounting and finance literatures. This discussion includes key word searches and counts, attribute dictionaries, naïve Bayesian classification, cosine similarity, and latent Dirichlet allocation. We also discuss how increasing interest in NLP processing of the corporate reporting package could and should influence financial reporting regulation and note that textual analysis is currently more of an afterthought, if it is even considered. Opportunities for improving the usefulness of NLP processing are discussed as well as possible impediments.

Item Type:
Journal Article
Journal or Publication Title:
Accounting and Business Research
Additional Information:
This is an Accepted Manuscript of an article published by Taylor & Francis in Accounting and Business Research on 01 Jun 2019, available online: https://www.tandfonline.com/doi/full/10.1080/00014788.2019.1611730
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
07 May 2019 14:20
Last Modified:
05 Nov 2023 01:10