AI Chatbot as IFRS Advisory Tool: GPT-4 Experimental Design

IF 3.7 Q1 Economics, Econometrics and Finance
Todor Tocev, Atanasko Atanasovski
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引用次数: 0

Abstract

The complexity of International Financial Reporting Standards (IFRS) challenges accounting professionals to navigate intricate judgment calls and estimations. This paper tackles a pressing question: Can OpenAI's ChatGPT (Version GPT-4) serve as a reliable artificial intelligence (AI) advisory tool to interpret and apply IFRS standards in real-world scenarios? The importance of this inquiry lies in the potential of generative AI to revolutionize financial reporting by enhancing accuracy, efficiency, and decision-making speed, which are critical demands in today's globalized financial environment. Through an experimental design employing practical case studies, this research evaluates GPT-4's performance under three prompting strategies: zero shot (ZS), few shot (FS), and chain of thought (CoT). This research examines the ability of AI to address judgment-driven, complex IFRS problems, expanding the scope of prior studies that primarily relied on theoretical exams or professional certification tests. Our findings reveal that GPT-4 can consistently identify the correct IFRS standard and produce professionally usable guidance, exhibiting strong potential. ZS proved fastest and most practical for a first advisory pass, FS delivered more structured and accounting-like answers but required greater preparation, and CoT generated the richest explanations at the expense of efficiency. Across all strategies, expert review remained necessary in areas involving item and measurement choices, contract integration, or business-model interpretation. This study efforts to advance the dialogue on AI's role in accounting and lays a foundation for future research exploring its broader implications in accounting decision-making. With insights into GPT-4's strengths and constraints, this study emphasizes its role as a transformative, yet supplementary, tool in advancing IFRS compliance and reporting standards.

AI聊天机器人作为IFRS咨询工具:GPT-4实验设计
国际财务报告准则(IFRS)的复杂性挑战会计专业人士导航复杂的判断电话和估计。本文解决了一个紧迫的问题:OpenAI的ChatGPT(版本GPT-4)能否作为可靠的人工智能(AI)咨询工具,在现实场景中解释和应用国际财务报告准则?这项调查的重要性在于,生成式人工智能有可能通过提高准确性、效率和决策速度来彻底改变财务报告,这些都是当今全球化金融环境中的关键需求。本研究通过采用实际案例研究的实验设计,评估了GPT-4在三种提示策略下的表现:零提示(ZS)、少提示(FS)和思维链提示(CoT)。本研究考察了人工智能解决判断驱动的复杂国际财务报告准则问题的能力,扩大了先前主要依赖理论考试或专业认证测试的研究范围。我们的研究结果表明,GPT-4能够始终如一地识别正确的国际财务报告准则,并提供专业可用的指导,显示出强大的潜力。对于第一次咨询,ZS被证明是最快和最实用的,FS提供了更结构化和类似会计的答案,但需要更多的准备,而CoT以牺牲效率为代价产生了最丰富的解释。在所有的战略中,专家审查在涉及项目和度量选择、合同集成或商业模式解释的领域仍然是必要的。本研究旨在推动关于人工智能在会计中的作用的对话,并为探索其在会计决策中的更广泛影响的未来研究奠定基础。通过深入了解GPT-4的优势和制约因素,本研究强调了其在推进国际财务报告准则合规和报告标准方面作为一种变革性的补充工具的作用。
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来源期刊
Intelligent Systems in Accounting, Finance and Management
Intelligent Systems in Accounting, Finance and Management Economics, Econometrics and Finance-Finance
CiteScore
6.00
自引率
0.00%
发文量
0
期刊介绍: Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.
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