Virtual auditing agents: the EDGAR Agent challenge

This study investigates the impact of Artificial Intelligence (AI) in auditing quality and assurance. As AI technologies become increasingly embedded in audit processes, understanding their influence on audit outcomes is critical for practitioners, regulators, and stakeholders. The study focuses on three key components of AI integration: AI-based data analytics, AI-assisted risk assessment, and AI-driven fraud detection, examining their individual and collective effects on audit quality. Grounded in the Technology Acceptance Model (TAM), the research employs a quantitative approach using survey data and multiple regression analysis to test hypotheses and evaluate relationships among variables. Findings reveal that all three AI components have a statistically significant positive impact on audit quality, with AI-based data analytics exerting the strongest influence. These results align with prior studies emphasizing AI's ability to enhance audit efficiency, reduce human error, and improve anomaly detection. However, the study also recognizes challenges such as regulatory uncertainty, ethical concerns, and limited adoption in small and medium-sized firms due to cost and skill constraints. The study contributes to existing literature by providing empirical evidence on AI's role in auditing, especially within diverse organizational contexts. It highlights the need for updated audit standards, greater investment in AI training, and stronger ethical frameworks to support responsible AI adoption. Practical recommendations are offered to guide audit firms, regulators, and educational institutions in navigating the transition to AI-enhanced audit environments. Ultimately, the study underscores that while AI cannot replace professional judgment, it serves as a powerful tool to augment audit quality and assurance effectiveness.

2019

The research aims to evaluate the impact of artificial intelligence (AI) and automation on the audit profession, focusing on improvements in efficiency, accuracy, and cost-effectiveness. A literature review methodology was employed, synthesizing insights from studies and industry reports on AI’s influence on auditing processes, ethical implications, and the evolving skill sets required for auditors. Key findings reveal that AI-powered methods achieve an 89% accuracy in fraud detection, outperforming traditional methods at 72%, and reduce false positives from 15% to 8% and false negatives from 13% to 3%. These findings underscore AI’s ability to minimize audit time, enhance fraud detection, and reduce operational costs. The study recommends ongoing auditor training in AI and data analytics, scalable AI tools for smaller firms, and stringent ethical and regulatory frameworks to guide AI use in auditing. Monitoring AI misclassification rates remains critical to sustaining effectiveness and precision in fraud detection. Key Words: Artificial Intelligence, Auditing, Automation, Fraud Detection, Regulatory Compliance

Journal of Accounting, Business and Finance Research, 2021

The purpose of this study is to examine the use of artificial intelligence to improve audit quality, combined with the competence and skepticism of auditors on client satisfaction. The unit of analysis in this study was selected as a sample based on the purposive sampling method which was chosen deliberately with certain criteria that have been determined by the researcher. The main source of data used in this study comes from primary data, namely questionnaires distributed directly via email to each respondent. Respondents in this study were middle level management, who were directly related to auditors at the time of the audit of companies listed on the Jakarta Stock Exchange. The sample in this study numbered 229 respondents who were processed and analyzed using SEM PLS. This research is based on the Society 5.0 era where data connects and moves everything; a system that connects the virtual world and the real world. The era of the fourth industrial revolution, where the discovery of the internet of things allows the interconnection between machines, big data, acquisition, machine learning, smart factories and others, and financial reports to be made using a computerized system. The global Covid-19 pandemic has had an impact on almost all sectors and restrictions on activities. As a result of the corona virus, most activities or work are carried out from home. The results of this study prove that the effect of the application of artificial intelligence combined with auditor competence and auditor professional skepticism creates client satisfaction.

Journal of Emerging Technologies in Accounting, 2016

After decades of frustration with long “AI Winters,” various business industries are witnessing the arrival of AI's “Spring,” with its massive and compelling benefits. Auditing will also evolve with the application of AI. Recently, there has been a progressive evolution of technology aimed at creating “artificially intelligent” devices. Although this evolution has been permeated with false starts and exaggerated claims, there is some convergence on the fact that substantive progress has been obtained in the last few years with the adoption of deep learning in conjunction with much faster machines and dimensionally larger storage spaces (and samples). The area of auditing has lagged business adoption in the past (Oldhouser 2016), but is prime for partial automation due to its labor intensiveness and range of decision structures. Several accounting firms have disclosed substantive investments in the AI fields. This paper proposes various areas of AI-related research to examine whe...

Shodh Sari-An International Multidisciplinary Journal

The rapid evolution of artificial intelligence (AI) technologies has brought about transformative changes in various industries, and the field of auditing is no exception. This research paper presents a comprehensive review of the integration of AI in auditing practices, highlighting its applications, benefits, and associated challenges. Auditing, a critical process for ensuring the accuracy and reliability of financial information, has traditionally been a labor-intensive and time-consuming endeavor. The emergence of AI technologies, such as machine learning, natural language processing, and data analytics, has revolutionized the way audits are conducted. AI-powered auditing tools offer advanced capabilities for data analysis, pattern recognition, anomaly detection, and risk assessment. These capabilities enhance the effectiveness and efficiency of audits by allowing auditors to focus on high-risk areas and perform more in-depth analysis. The paper explores various applications of ...

INTERNAL AUDITING & RISC MANAGEMENT - No 67 - Supplement May 2023 - Athenaeum University - ISSN-L 2065 – 8168; ISSN (e) 2068 – 2077; ISSN (p) 2065 - 8168, 2023

The technological evolution in the last decade has led to the extensive integration of Artificial Intelligence (AI) into various fields, including audit and accounting. This research addresses the profound transformation of audit and accounting methodologies through the integration of AI-based technologies. Focusing on the application of linear regression in financial data analysis, this study explores the efficiency and accuracy of AI in interpreting, analyzing, and predicting financial models. Using simulated data sets and implementing the model in Python, the results show a strong correlation between the level of AI implementation and audit efficiency. Our vision for the future suggests a deep collaboration between human capability and artificial intelligence, allowing for a more accurate and efficient audit. This transformation will require ongoing adaptation from professionals and industry regulations.

International Journal of Science and Research Archive, 2025

The role of AI in auditing is quickly changing the world of business assurance. Traditional audit is limited in terms of scope, speed, and accuracy as business operates in more complex financial ecosystems. AI tools from machine learning algorithms to natural language processing and robotics process automation have the ability to enable auditors to analyse large data sets and detect anomalies leading to a continuous real-time audit. This article discusses how AI is changing the auditor's toolbox and by extension, transforming auditor role in providing value-added insights to companies. Based on a thorough literature review and an empirical analysis with practicing audit professionals and financial professionals, this work examines the current use of AI in the context of audit, as well as the beliefs about its potential and risks, and the emerging role it is expected to have in the work of auditors. Results show that AI can significantly improve audit quality, fraud detection, and/or enterprise risk and introduces some important challenges in data governance, transparency, and ethical oversight. The paper finds that AI does not substitute auditors but complements them by reallocating their focus from manual checking to strategic thinking and analysis. This development will require upskilling, adaptation of regulation, and a nuanced approach to combining the possibilities offered by technologies with professional norms. The paper provides actionable suggestions for auditors and audit firms and policy makers interested in leveraging AI for better business assurance.

This paper presents some problems concerning the intelligent agents and their use in accounting. There are a lot of viewpoints for using this new technology in various fields of the economy, in finance and accounting.

Journal IJETRM, 2024

Accounting and auditing face a complete transformation because of the fast-moving developments in technology, which include artificial intelligence (AI), blockchain, and the metaverse. The speed at which digital transformation continues to progress causes traditional accounting processes to merge with automation predictive analytics and decentralized ledgers, and that provides enhanced accuracy together with transparency and efficiency (Smith & Johnson, 2023). The metaverse as a virtual-reality-centric digital space needs new financial audit frameworks. It creates financial environments that make it necessary to establish auditing regulations for virtual assets, smart contracts, and decentralized finance (DeFi) frameworks (Brown et al., 2024). Identifying potential fraud and evaluating risks in auditing becomes more effective through the implementation of AI algorithms yet prevents human errors and supports companies to fulfill current financial rules (Williams & Carter 2024). Anticipated governance frameworks should address the current cyber security threats, ethical issues, and regulatory gaps stemming from technological advancement (Davis, 2023). The paper studies the convergence of accounting with auditing and emerging tech by analyzing transformative chances and developmental obstacles alongside potential business directions for financial experts moving into a digitalized immersive market

1986

This paper describes the design of a knowledge-based system to assist auditors in the evaluatation of internal accounting controls and focusses on the logic-based language AL that has been developed as a knowledge representation formalism. Interesting features of AL include a declarative approach to modeling accounting systems and the means to explicitly describe authority structures typically used to enforce internal controls. KASS: A Knowledge-Based Language for Auditor Support 1.0 Introduction Internal controls evaluation of an accounting system is a complex task that has received growing interest in recent years. Past approaches that met with some success include those drawn from the Artificial Intelligence (AI) literature. Examples include TICOM, developed by Bailey et al (1985) and EDP-XPERT developed by Hansen and Messier (1986) Seminal work in the application of AI to the domain of financial diagnosis is reported in Bouwman (1986). Bouwman analyzed protocols of an expert and...