Applying Large Language Models in Accounting: A Comparative Analysis of Different Methodologies and Off-the-Shelf Examples

Forthcoming in the Journal of Emerging Technologies in Accounting

44 Pages Posted: 1 Jan 2024 Last revised: 12 Apr 2024

See all articles by Huaxia Li

Huaxia Li

University of Michigan at Dearborn

Miklos A. Vasarhelyi

Rutgers Business School

Date Written: November 30, 2023

Abstract

The emergence of Large Language Model (LLM) presents significant opportunities in accounting, including optimizing current processes, extracting new information, and updating accounting measurements. However, factors such as skill gaps, perceived complexity of integration, and cost constraints have limited its implementation in accounting. This study provides an overview of mainstream LLM utilization methods, including user interface and application programming interface, and introduces a novel approach via robotic process automation (RPA) integration. The advantages and limitations of each method are discussed, accompanied by a current analysis of the time, labor, and monetary costs involved in employing LLM for an accounting task. To facilitate practical applications, three off-the-shelf examples are provided. This study contributes to the literature and practice by summarizing and comparing LLM implementation methods, responding to the challenges raised by researchers and stakeholders, and bridging the gap between technology innovation and its practical application in accounting.

Keywords: ChatGPT, Robotic Process Automation (RPA), User interface (UI), Application programming interface (API), Pros and cons, Cost analysis, Large Language Model (LLM)

JEL Classification: M41, O14, O33, D61

Suggested Citation

Li, Huaxia and Vasarhelyi, Miklos A., Applying Large Language Models in Accounting: A Comparative Analysis of Different Methodologies and Off-the-Shelf Examples (November 30, 2023). Forthcoming in the Journal of Emerging Technologies in Accounting, Available at SSRN: https://ssrn.com/abstract=4650476 or http://dx.doi.org/10.2139/ssrn.4650476

Huaxia Li (Contact Author)

University of Michigan at Dearborn ( email )

19000 Hubbard Dr.
110 FCS
Dearborn, MI 48126
United States

Miklos A. Vasarhelyi

Rutgers Business School ( email )

180 University Avenue
Ackerson Hall, Room 315
Newark, NJ 07102
United States
973-353-5002 (Phone)
973-353-1283 (Fax)

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