Machine Learning-based Decision-Making Systems, Cloud Computing and Blockchain Technologies, and Big Data Analytics Algorithms in Accounting and Auditing.

• Author: Ionescu, Luminita

1. Introduction

   Deep neural network-based prediction systems and machine learning techniques assist accounting and audit professionals in relation to emotional intelligence skills and ethical decision-making. The purpose of my systematic review is to examine the recently published literature on accounting and auditing and integrate the insights it configures on machine learning-based decision-making systems, cloud computing and blockchain technologies, and big data analytics algorithms. By analyzing the most recent (2020-2022) and significant (Web of Science, Scopus, and ProQuest) sources, my paper has attempted to prove that machine learning algorithms and blockchain technologies can optimize corporate internal control, analyst tracking, and accounting qualities in terms of information disclosure, performance data, and fraud detection, leading to higher-profile advisory roles and decreased level of earnings management. The actuality and novelty of this study are articulated by addressing artificial intelligence applications optimizing quality, efficiency, transparency, and interpretability in the accounting and auditing tasks, that is an emerging topic involving much interest. My research problem is whether artificial intelligence applications further financial and managerial accounting and accounting information systems in relation to automation-based repetitive tasks and updated skills.

   In this review, prior findings have been cumulated indicating that cognitive modeling technology and deep learning of neural networks are decisive in improving accounting statements and combating corporate tax evasion by collecting and processing data. The identified gaps advance the issue of accounting and auditing firms deploying blockchain technology, business data analytics, and machine learning algorithms. My main objective is to indicate that accounting technologies, predictive modeling algorithms, and artificial intelligence-based chatbots (massive data language models) shape organizational competitiveness and professional skills by integrating big data in terms of targeted support and lifelong learning. This systematic review contributes to the literature on machine learning algorithms, data mining and analytics, and robotic process automation (Andronie et al, 2021; Nagy and Lazaroiu, 2022) assisting in the large-scale strategic management accounting development and informatization by clarifying that blockchain technologies and Internet of Things (Andronie et al., 2023a, b; Nagy et al., 2023) are pivotal in auditing financial statements in terms of accounting information reliability, competencies, and skills.

2. Theoretical Overview of the Main Concepts

   Data management and cleansing skills as regards inaccurate or incomplete correction configure ethical machine learning-based decision-making in the accounting environment, throughout internal and external auditing processes, and across artificial intelligence-based accounting systems, improving job performance by decreasing repetitive tasks and human error risks through autonomous learning and adaptive routines. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), deep neural network-based prediction systems and machine learning techniques assisting accounting and audit professionals (section 4), blockchain technology, business data analytics, and machine learning algorithms in accounting and auditing firms (section 5), robotic process automation, blockchain technology, machine learning algorithms, and big data analytics in accounting and auditing practices and environments (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10).

3. Methodology

   Throughout July 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including "accounting and auditing" + "machine learning-based decision-making systems," "cloud computing and blockchain technologies," and "big data analytics algorithms." As research published between 2020 and 2022 was inspected, only 193 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, I selected 54 mainly empirical sources (Tables 1 and 2). Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR (Figures 1-6).

4. Deep Neural Network-based Prediction Systems and Machine Learning Techniques Assisting Accounting and Audit Professionals

   Artificial intelligence, cloud computing, data analytics, blockchain, and automation can negatively impact the professional expertise development in accounting and auditing (Ardichvili, 2022; Commerford et al., 2022; Everaert et al., 2022; Fang et al., 2023; Garanina et al., 2022; Moore and Felo, 2022) due to diminished practice and technical skills as regards complex tasks and decreased interaction with experienced colleagues, in addition to discounting computer-based advice (algorithm aversion). Machine learning algorithms and blockchain technologies can optimize corporate internal control, analyst tracking, and accounting qualities in terms of information disclosure, performance data, and fraud detection, leading to higher-profile advisory roles and decreased level of earnings management.

   Machine learning algorithms, data mining and analytics, and robotic process automation (Aldredge et al., 2021; Bakarich and O'Brien, 2021; Gao and Han, 2021; Mancini et al., 2021; Ping, 2021; Scott Showalter and Krawczyk, 2022) can assist in the large-scale strategic management accounting development and informatization. Blockchain technologies and Internet of Things are pivotal in auditing financial statements in terms of accounting information reliability, competencies, and skills.

   Machine learning algorithms and big data analytics (Aboagye-Otchere et al., 2021; Alderman, 2021; Bertomeu et al., 2021; Eachempati et al., 2021; Goto, 2021; Zhang et al., 2021) can impact efficiency and performance of financial accounting systems as regards narrative accounting disclosures, accounting practices, managerial accounting and taxation, corporate tax behavior, and accounting misstatements. Deep neural network-based prediction systems and machine learning techniques assist accounting and audit professionals in relation to emotional intelligence skills and ethical decision-making. (Table 3)

5. Blockchain Technology, Business Data analytics, and Machine Learning Algorithms in Accounting and Auditing Firms

   Artificial intelligence applications can optimize quality, efficiency, transparency, and interpretability in the accounting and auditing tasks (Almufadda and Ahmed Almezeini, 2022; Fedyk et al., 2022; Jackson et al., 2022; O'Leary, 2022; Krupa and Minutti-Meza, 2022; Zhang et al., 2022) in relation to documentation and evidence standards, reducing fees and material misstatement risk, and displacing human experts. Accounting technologies, predictive modeling algorithms, and artificial intelligence-based chatbots (massive data language models) shape organizational competitiveness and professional skills by integrating big data in terms of targeted support and lifelong learning.

   Blockchain technology, machine learning algorithms, and big data analytics (Ashta and Herrmann, 2021; Liu et al., 2021; Maiti et al., 2021; Petkov, 2020; Shaffer et al., 2020; Zhang et al., 2020) assist artificial intelligence-based fintech firms as regards accounting and auditing practices, while optimizing business operations and fraud detection, and increasing productivity...