Virtual auditing agents: the EDGAR Agent challenge

Nelson, Kay M.; Kogan, Alexander; Srivastava, Rajendra P.; Vasarhelyi, Miklos A.; Lu, Hai T

doi:10.1016/s0167-9236(99)00088-3

Cited by 24 publications

(16 citation statements)

References 12 publications

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“…Extracting useful information from these reports is a challenge, especially for academic researchers and professional analysts who examine large numbers of firms. Various researchers ͑Tanaka 1982; Mui and McCarthy 1987;O'Leary and Munakata 1988;O'Leary and Eis 1991;O'Leary and Kandelin 1992;Steier 1995;Ferguson 1997;Steier et al 1997;Nelson et al 2000͒ have worked on building intelligent software to handle unstructured reports. Adding to these prior studies, accounting researchers have recently made new progress in this area.…”

Section: Retrieval Of Accounting Quantities From Textmentioning

confidence: 99%

The Role of Text Analytics and Information Retrieval in the Accounting Domain

Fisher

Garnsey

Goel

et al. 2010

Journal of Emerging Technologies in Accounting

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Textual documents proliferate throughout accounting practice, and a wide variety of groups make financial decisions based on written guidance. The Generally Accepted Accounting Principles (GAAP), along with annual corporate financial statements and other reporting narratives, are important sources of such guidance and information. This paper examines the literature in two major areas relevant to text analytics and information retrieval in the accounting domain: (1) the manual and computational content analysis of accounting narratives, accounting readability studies, and related text-mining work, and (2) the information retrieval literature stream that addresses the extraction of both text elements as well as quantities imbedded in text from accounting documents, and includes the impact of understanding the accounting lexicon upon retrieval from digital accounting documents. We use the goals in developing the GAAP Codification, as expressed by the Financial Accounting Standards Board (FASB) in their Notice to Constituents (FASB 2009), as a starting point for reviewing the literature. The paper concludes with a map for suggested future research in accounting text analytics and information retrieval.

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Section: Retrieval Of Accounting Quantities From Textmentioning

confidence: 99%

The Role of Text Analytics and Information Retrieval in the Accounting Domain

Fisher

Garnsey

Goel

et al. 2010

Journal of Emerging Technologies in Accounting

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“…Bailey and Bakos (1997) point out that intermediaries will become the trust providers in electronic commerce. Other authors such as Nelson et al (2000) have introduced new intermediary roles such as continuous online auditing agents. Intermediaries are seen to provide third party assurance services and this trust provision encompasses most industries.…”

Section: Intermediaries In Online Marketsmentioning

confidence: 99%

Online consumer market inefficiencies and intermediation

Datta

Chatterjee

2011

SIGMIS Database

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This paper seeks to empirically unravel why consumers sometimes need to trust intermediaries in online markets. Notwithstanding assertions that online markets will eventually eliminate the need for intermediaries, intermediaries remain an active part of the online market landscape. This paper tries to understand this phenomenon from a view of a consumer lack of trust in online markets and seeks to unearth what ultimately causes a lack of consumer trust in online markets and the role played by intermediaries in the mix. The paper proposes a model and empirically validates it. Findings suggest that inherent inefficiencies in online markets lead to consumer uncertainty. Perceptions of uncertainty lead to a lack of consumer trust in online markets. Consumer trust in online markets is restored only by placing trust in intermediaries.

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“…Edgar is the main subagent of FRAANK, since it is responsible for obtaining and processing the richest source of information -SEC filings of publicly traded companies available in the SEC EDGAR repository on the Web. The predecessor of the Edgar subagent, the original Edgar agent, was described in detail in Nelson et al (2000). The current version of the Edgar subagent is completely redesigned, significantly more robust, and has much greater capabilities, which include:…”

Section: Edgar Subagentmentioning

confidence: 99%

“…After a particular financial statement is extracted, it is parsed by the Edgar subagent to identify all the line items, their balances, and their aggregation structure. Line-item na mes can exhibit even greater variability than the table captions, as described in detail in Nelson et al (2000). The intelligent parsing procedure in Edgar utilizes tables of line-item synonyms stored in a relational database (see Section IV for a more detailed description).…”

Section: Edgar Subagentmentioning

confidence: 99%

“…A generic tool for semantic parsing of the SEC filings has been developed by Gerdes (2003). The predecessor of FRAANK, the so-called original Edgar agent (Nelson et al 2000), was capable of retrieving quarterly filings (10-Q's) from the SEC EDGAR repository and parsing them to identify the most important accounting numbers. As compared with the new Edgar subagent of FRAANK, the original Edgar agent was much more limited in its capabilities and had a much simpler design.…”

Section: Introductionmentioning

confidence: 99%

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Financial Reporting and Auditing Agent with Net Knowledge (FRAANK) and eXtensible Business Reporting Language (XBRL)

Bovee

Kogan

Nelson

et al. 2005

Journal of Information Systems

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This paper describes the development and applications of FRAANK—Financial Reporting and Auditing Agent with Net Knowledge. The prototype of FRAANK presented here provides automated access to, and understanding and integration of, rapidly changing financial information available from various sources on the Internet. In particular, FRAANK implements intelligent parsing to extract accounting numbers from natural-text financial statements available from the SEC EDGAR repository. FRAANK develops an “understanding” of the accounting numbers by means of matching the line-item labels to synonyms of tags in an XBRL taxonomy. As a result, FRAANK converts the consolidated balance sheet, income statement, and statement of cash flows into XBRL-tagged format. Based on FRAANK, we propose an empirical approach toward the evaluation and improvement of XBRL taxonomies and for identifying and justifying needs for specialized taxonomies by assessing a taxonomy fit to the historical data, i.e., the quarterly and annual EDGAR filings. Using a test set of 10-K SEC filings, we evaluate FRAANK's performance by estimating its success rate in extracting and tagging the line items using the year 2000 C&I XBRL Taxonomy, Version 1. The evaluation results show that FRAANK is an advanced research prototype that can be useful in various practical applications. FRAANK also integrates the accounting numbers with other financial information publicly available on the Internet, such as timely stock quotes and analysts' forecasts of earnings, and calculates important financial ratios and other financial-analysis indicators.

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Virtual auditing agents: the EDGAR Agent challenge

Cited by 24 publications

References 12 publications

The Role of Text Analytics and Information Retrieval in the Accounting Domain

The Role of Text Analytics and Information Retrieval in the Accounting Domain

Online consumer market inefficiencies and intermediation

Financial Reporting and Auditing Agent with Net Knowledge (FRAANK) and eXtensible Business Reporting Language (XBRL)

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