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Textual Analysis for Risk Profiles from 10-K Filings: Evidence from Audit Opinions

The CPA journal (1975), 2020-06, Vol.90 (6), p.36-41

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Title:
Textual Analysis for Risk Profiles from 10-K Filings: Evidence from Audit Opinions
Author: Liu, Manlu ; Wu, Kean ; Yang, Rong ; Yu, Yang
Subjects: Annual reports ; Assurance services ; Audited financial statements ; Auditors ; Auditors opinions ; Audits ; Evaluation ; Financial reporting ; Financial risk ; Financial statements ; Form 10-K ; Internal control (Accounting) ; Keywords ; Litigation ; Natural language processing ; Qualitative research ; R&D ; Research & development ; State taxes ; Technology application ; Text analysis
Is Part Of: The CPA journal (1975), 2020-06, Vol.90 (6), p.36-41
Description: Technology can be used by auditors to evaluate the risks presented by engagements. This article Introduces a Natural Language Processing (NLP) approach to conduct textual analysis of unstructured data from financial reports. Using NLP, corporate annual risk profiles are generated from 10-K filings and validated. The results indicate that auditors are more likely to issue modified audit opinions and internal control material weaknesses for clients with higher self-identified risks.
Publisher: New York: New York State Society of Certified Public Accountants
Language: English
Identifier: ISSN: 0732-8435
Source: ProQuest Central

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