Improve Audit Efficiency Research Articles

USE OF ARTIFICIAL INTELLIGENCE IN ACCOUNTING AND ANALYTICAL PROCESSES

The beginning of a new era has led to the emergence of new factors that impede the effective operation of enterprises. One of these factors is the exponential growth of the amount of data that needs to be processed and analyzed in order to make effective management decisions. This leads to the need to develop or search for a software product aimed at collecting, analyzing and systematizing a large amount of data, as well as performing relevant tasks based on them that artificial intelligence is capable of. The article is aimed at researching and revealing the potential of using artificial intelligence (AI) in the field of accounting. The main focus is on improving the efficiency of the enterprise, which is achieved by automating and optimizing various aspects of accounting work. On the basis of a thorough analysis of the works of foreign and domestic specialists, the theoretical aspects of the concept of artificial intelligence are distinguished on the basis of systemic, functional and information approaches. The directions of compliance of the accountant, which can be artificial intelligence, are identified, namely: processing of invoices, cost management, analysis of financial statements, management of payables and receivables, compliance with tax legislation and detection of fraud and risk management. Ways of using AI in processes of automation and optimization of processes, such as invoice processing, cost management, financial reporting analysis, control of accounts payable and receivable, ensuring compliance with tax legislation and fraud detection and risk management, have been identified. The artificial intelligence technologies for their purpose, which are the most used in the world, are presented. The sequence of actions in the identified needs in artificial intelligence and its outstanding volume is structured. The results of the study confirm the potential of AI to automate operations, increase productivity and accuracy in accounting, as well as reduce risks and improve audit efficiency. Key words: Artificial intelligence, accounting, analysis, accounting automation, accounting information systems, information systematization, management efficiency.

Risk assessment in performance auditing: a review of approaches and methods

Performance auditing has evolved over time from a focus on error and fraud detection to a more comprehensive and strategic approach. The main objective of this study was to analyze and compare traditional and modern approaches to performance auditing. A non-experimental and qualitative methodological approach was used, based on a documentary review of indexed academic sources. The results revealed a significant transition in auditing practices, with the modern approach oriented towards continuous improvement and risk anticipation. The importance of adopting advanced technologies, such as artificial intelligence, to improve audit efficiency and effectiveness was highlighted. In conclusion, performance auditing plays a conclusive role in process improvement and informed decision making, contributing to the achievement of organizational objectives and the maintenance of high standards of performance and transparency.

Can fintech improve audit efficiency? Empirical evidence from audit fees and corporate governance

ABSTRACT Based on China’s city-level data and the panel data of A-share listed companies, this study examines the impact of fintech development on corporate audit efficiency. The empirical results indicate that fintech development accelerates enterprise digitization, thereby resulting in decreased audit fees. Additionally, this development yields positive effects on corporate governance, such as improving the quality of financial statement audits, reducing the probability of enterprise violations, and improving internal controls.

Do auditors value social trust? Evidence from China

ABSTRACT Using a sample of Chinese listed companies between 2007 and 2021, we investigate the association between social trust and audit outcomes. Results suggest that regional level of social trust can improve audit efficiency and reduce audit fees. We further find client firms reside in high-trust regions are less likely to engage with Big10 auditors in China. Both audit efficiency and auditor choice play partial mediating roles in lowering audit fees. The negative effect of social trust on audit fees is more pronounced in firms located in strong legal enforcement region, with state ownership, or in firms audited by non-Big10 auditors. By documenting the reduced audit fees and the lower likelihood of hiring Big10 auditors do not lead to deterioration in audit quality, our study has important social and policy implications for strengthening informal norms in regions with low social trust.

Can corporate ESG performance improve audit efficiency?: Empirical evidence based on audit latency perspective.

Environmental, Social and Governance (ESG) is closely related to the "dual carbon" objective and the concept of sustainable development. The impact of ESG performance on audit efficiency, especially on audit delays, is still an issue to be studied in depth. Drawing on stakeholder theory, sustainable development theory, shared value concept and corporate social responsibility theory, this study adopts regression analysis and structural equation modeling (SEM) to investigate the impact of ESG on audit efficiency based on the data of A-share listed companies in the period of 2015-2022, with a focus on audit delay. The results of regression analysis show that ESG performance has a significant effect on reducing audit delay, and audit delay is reduced by 0.007 on average for each unit increase in ESG performance. In structural equation modeling, the effect of ESG performance on audit delay is more significant, with an estimated value of -0.555 and a standard error of 0.097. In addition, the study shows that the corporate ESG performance on audit efficiency has a positive impact is more pronounced among firms with stronger ESG practices, especially among non-state-owned firms with lower institutional investor ownership and firms audited by "Big Four" firms. These results not only demonstrate the importance of ESG performance in improving audit efficiency, but also provide important guidance for corporate management and policy making. This study enriches the existing literature on corporate ESG performance and audit efficiency and provides new perspectives and directions for future research.

A secure dynamic cross-chain decentralized data consistency verification model

The continuous increase in the number of transactions is exerting significant pressure on the storage capacity of blockchains. By storing data on multiple blockchains and interacting with each other with cross-chain technology, the storage pressure can be relieved to a large degree. Nevertheless, the feature of immutability may impede the further development of blockchains, e.g., some expired identity information cannot be updated due to immutability. The decentralized chameleon hash function can resolve the issue while ensuring the feature of decentralization. Unfortunately, how to ensure the consistency of dynamic data updating in cross-chain interaction is still a question worth considering. In this paper, we propose a dynamic cross-chain decentralized data consistency verification (DCCV) model, in which we adopt an audit chain and design a dynamic Merkle hash tree to guarantee the consistency of dynamic data updating between the source chain and the target chain. In addition, in order to enhance the relevance of calculations across different smart contracts and improve audit efficiency, we propose a way to develop cross-chain smart contracts collaboratively. Moreover, Cosi protocol and multi-signcryption are utilized to ensure the security and privacy of cross-chain data transmission. Finally, theoretical and experimental analysis demonstrates that DCCV can achieve dynamic data consistency verification in the process of cross-chain interaction.

Audit Data and Management Platform Based on Intelligent Algorithm

Due to the uncertainty of the external economic environment and the changes caused by new technologies in the new era, there are still many deficiencies in the current financial statement audit. The use of new technology can optimize the audit process, reduce audit practice risks and improve audit efficiency. Therefore, it is necessary to study the intelligent audit of financial statements. The purpose of this paper is to study the audit data analysis and management platform based on intelligent algorithms. This paper focuses on the construction purpose and content of the audit data analysis and management platform, and analyzes the specific requirements of some functional modules in the platform according to the audit workflow and business requirements. At the same time, this paper also describes the overall design architecture of the platform, which mainly uses the isolated point mining method for enterprise intelligent audit. This paper takes it as an effective method to analyze the problems existing in the internal audit of enterprises, and constructs the audit model of benefit-cost matching, and verifies the effectiveness of the algorithm through an example. There are four isolated points in the gross profit rate of catering of an enterprise.

Does external auditor coordination influence internal auditor effort?

The purpose of this study is to investigate how the level of controls testing coordination with the external auditor affects internal auditors' effort. The internal auditor's planned substantive testing audit hours are the measure of effort in this study. Regulators and stakeholder organizations have encouraged more collaboration between external and internal auditors to improve audit efficiency. The effect of external auditor coordination on internal auditors' planned audit hours has important implications for audit efficiency and effectiveness. An experiment is conducted with 112 internal auditors to examine the hypothesized effect. The study uses a 2 × 2 between-subjects design and manipulates fraud risk and external auditor coordination. Consistent with my prediction, I find that coordination moderates the relationship between fraud risk and planned audit hours. The results illustrate that although high external auditor controls testing coordination decreases internal auditors' planned substantive testing audit hours, internal auditors are more sensitive to responding to fraud risk when external auditor controls testing coordination is high.

Study on the Impact of Digital Transformation on Audit Risks of Accounting Firms: The Case of Grant Thornton

As the external environment changes, digital transformation is becoming increasingly necessary for accounting firms. Firstly the '14th Five-Year Plan' for the development of the digital economy emphasizes the importance of accelerating the digitalization of the industry. Secondly audit plays an important third-party supervisory role in the capital market and the volume of audit engagements has been growing in recent years, but the corresponding increase in audit risk due to manpower shortage, lack of time and limited resources. Finally the outbreak of the new crown epidemic reveals the problem of unenforceable on-site audits, which affects investor effectiveness and capital market efficiency. Therefore, it is important to study the impact of audit risk in accounting firms from the perspective of digital transformation to promote the digital transformation of accounting firms. In this paper, we take the example of Grant Thornton, which has a long history of development, comprehensive business lines, and is a pioneer and leader in promoting digital reform among domestic accounting firm, and is representative in digital reform. This paper firstly reveals the advantages of digital audit in the digital economy by comparing traditional audit and digital audit; secondly, it analyzes the impact mechanism of digital transformation on audit risk in accounting firms; then it examines what measures accounting firms can take to reduce audit risk, improve audit efficiency and save audit cost in the context of digital transformation. Finally, the problems of digital transformation of accounting firms are explored, and corresponding suggestions and measures are proposed. This has important guiding significance for promoting digital reform in the audit industry.

Financial Fraud Detection of Listed Companies in China: A Machine Learning Approach

As the focus of capital market supervision, financial report fraud has shown a development trend of enormous numbers, complex transactions, and hidden means in recent years. To improve audit efficiency and reduce the dependence on non-financial data, the study only uses the structured original data in the financial report to constructs a new fraud identification model, which can quickly detect fraud in China. This study takes the listed companies in China from 1998 to 2016 as research samples and selects 28 sets of raw data from financial reports. Then, this study compares the detection effectiveness of two single classification machine learning algorithms and five ensemble learning algorithms on fraud detection. Compared with single classification machine learning algorithms, the results show that ensemble learning algorithms are generally better at detecting fraud for Chinese listed companies, and the stacking algorithm performs the best. The study results provide direct evidence for rapid fraud detection using financial report raw data and ensemble learning algorithms. The study first proposes a stacking algorithm-based financial reporting fraud identification model for listed companies in China, which provides a simple and effective approach for investors, regulators, and management. It can also provide a reference for the detection of other fraud scenarios.

Ciphertext Database Audit Technology Under Searchable Encryption Algorithm and Blockchain Technology

The study aims to solve the problems in auditing ciphertext data, improve audit efficiency, and increase the security of audit data in the audit server. First, the existing encryption algorithms are analyzed. Second, the searchable encryption algorithm is proposed to audit the ciphertext data, and an audit server scheme is made based on blockchain technology (BT). Finally, the two schemes are compared with the traditional audit technology. The results show that the server's inspection efficiency of the searchable encryption algorithm is higher.

Improved Efficient Privacy-Preserving Certificateless Provable Data Possession Scheme for Cloud Storage

Cloud storage technology is evolving at a high speed; effectively auditing the cloud data’s integrity has become a focal point. Recently, Ming and Shi proposed a certificateless integrity auditing scheme with a privacy protection function. The scheme used the certificateless cryptosystem to solve the certificate management problem of the auditing schemes based on public key infrastructure and the key escrow problem of the identity-based auditing schemes. Although their scheme is novel and efficient, we found that their scheme was not secure and could not achieve integrity auditing of cloud data. The malicious cloud server can generate the proof through the blocks and tags sent by the user. On the basis of the original scheme, we propose an improved auditing scheme; our new scheme is more secure and effective. In addition, for the problem of idle tags in the existing cloud data integrity auditing scheme, we propose the idea of intermediate tags and we applied the idea to the improved scheme to improve audit efficiency.

Does human resource investment in internal controls and information technology improve audit efficiency?

This study examines the effect of client human resource investment in internal controls (ICs) and information technology (IT) on audit efficiency. Accordingly, we propose a novel approach to modify the measurement of audit efficiency by directly measuring the length of time from the fiscal year end to the last day of fieldwork of an audit firm—fieldwork lags (FWLs)—rather than audit report lags (ARLs). We investigate the relationship between FWLs and the number of IC personnel and their average work experience at the department level: accounting and finance, IT and others. We find that FWLs are negatively related to the number of IC personnel in the accounting and finance departments and other related areas. Furthermore, FWLs decrease when IC personnel in the IT department have more average work experience. This finding indicates that experienced IC personnel in the IT department are critical to reducing the fieldwork time taken by auditors. Overall results suggest that a client's investment in IC personnel in accounting/finance and IT departments enhances audit efficiency.

Is integrated auditing superior to separate auditing? Evidence from China

ABSTRACT The purpose of this study is to compare audit effectiveness and audit efficiency between companies that have integrated auditing of internal control over financial reporting (ICFR) and financial statements and companies that have separate auditing. We analyse a sample of Chinese public companies that disclosed their ICFR audit reports from 2011 to 2015. Using the full sample, sub-samples, and a propensity score matching (PSM) sample, we consistently find that companies having integrated auditing exhibit higher financial reporting quality measured by excess non-operating income. The findings regarding audit efficiency are mixed, with limited evidence indicating that an integrated auditor is potentially able to complete two audits without further delay. Overall, our results seem to suggest that integrated auditing is superior to separate auditing in that it enhances audit effectiveness and might improve audit efficiency. Such superiority might be due to knowledge spillover when two related audit services are jointly provided.

TIIA: A blockchain-enabled Threat Intelligence Integrity Audit scheme for IIoT

With the widespread deployment of the Industrial Internet of Things technology (IIoT), the cyber security threats of IIoT systems are increasing. Threat intelligence sharing is an effective way to resist cyber security threats. However, there is a contradiction between information integrity and the requirement of building a complete attack chain in the threat intelligence sharing and utilization. Due to the limited capacity of block storage pattern, it can be found that threat intelligence is prone to fragmentation on blockchain. In this paper, a blockchain-enabled Threat Intelligence Integrity Audit (TIIA) scheme for IIoT is proposed. This scheme can audit the integrity of threat intelligence in ciphertext state to ensure the confidentiality protection requirements of threat intelligence on blockchain. A double chain structure is presented in the TIIA scheme. The storage-chain is used to store threat intelligence ciphertext, while the audit-chain is designed to achieve the integrity audit of the corresponding fragment on the storage-chain. In addition, Paillier homomorphic encryption and searchable encryption are used to realize the confidentiality and ciphertext retrieval of threat intelligence on the storage-chain. A redundant block deletion algorithm is designed to reduce the audit-chain load and improve audit efficiency. The performance analysis shows that the proposed scheme can effectively reduce the computational and communication costs, and has a high audit efficiency.

104. Improving Efficiency of Antimicrobial Stewardship Reviews Using Artificial Intelligence Modelling

BackgroundAntimicrobial stewardship programs (ASP) in hospitals improve antibiotic prescribing, slow antimicrobial resistance, reduce hospitalisation duration, mortality and readmission rates, and save costs. However, the strategy of prospective audit and feedback is laborious. In Singapore General Hospital (SGH), 10 reviews are required to identify 2 inappropriate cases. Limited manpower constraints ASP audits to only about 30% of antibiotics prescribed. This proof-of-concept study explored the feasibility of developing a predictive model to prioritise inappropriate antibiotic prescriptions for ASP review. MethodsASP-audited adult pneumonia patients from January 2016 to December 2018 in SGH were included. Patient data e.g., demographics, allergies, past medical history, and relevant laboratory investigations at each antibiotic use episode were extracted from electronic medical records and re-assembled through linking for analysis. Ground truth for model training was based on ASP-defined appropriateness for each encounter. The dataset was split into 80% and 20% for training and testing respectively. Three modelling techniques, XGBoost, decision tree and logistic regression, were assessed for their relative performance in terms of precision, sensitivity and specificity. ResultsThere were 12471 unique patient encounters. Training was done on 10459 encounters and 39 data elements were included. When tested on 2012 encounters, the logistic regression model performed the best (86.7% sensitivity, 71.4% specificity). The model correctly classified 1377 out of 1388 (99.2%) encounters as “appropriate” (do not require ASP intervention). 624 antibiotic use encounters were classified as “inappropriate”, of which only 72 were truly inappropriate (positive predictive value for ASP intervention, PPV 11.5%). The low PPV was likely due to inadequate representation of “inappropriate” cases in the training dataset (4.1%). Applying this model would prioritise the number of immediate ASP reviews needed to identify cases for intervention by two-thirds, from 2012 to 624 (Figure 1). Figure 1. Illustration of AI benefits in ASP ConclusionASPs can leverage on machine learning capabilities to improve audit efficiency. This can increase ASP’s productivity and staff’s job satisfaction as they are freed up to perform other work. Disclosures All Authors: No reported disclosures

Auditors' Perception on the Impact of Artificial Intelligence on Professional Skepticism and Judgment in Oman

Technology is an inevitable part of businesses and human lives. It has brought about substantial changes in the way businesses and operations are conducted. A business organization has to perform auditing which involves analyzing and testing a large volume of financial transactions. In manual auditing, testing and analyzing the entire transactions in a business are not possible. The usage of artificial intelligence (AI) and Machine Learning (ML) not only allows testing the entire financial transactions in a business but also helps improve audit efficiency. Audit efficiency relates to the professional skepticism and professional judgment demonstrated by the auditors. The core purpose of the research is to understand the perception of auditors on the impact of such technologies on professional skepticism and the judgment of internal auditors in improving audit efficiency. To understand the impact of AI and ML, various factors influencing the use of AI and ML and the challenges were considered. Data were collected from 169 respondents spanning across all sectors in Oman using a structured questionnaire. The collected data were analyzed using correlation to determine the relationship between AI and ML-assisted auditing practices and professional skepticism and professional judgment. Results indicate that AI and ML-assisted auditing practices have a strong positive relationship with professional skepticism and professional judgment. This proves that AI and ML have an impact on professional skepticism and professional judgment. Moreover, it helps in improving the detection of errors and material misstatements. Even though the advantages of AI and ML outweigh manual auditing, the complete replacement of human beings with AI and ML should be considered with caution. Hence, auditing must be carried out with the help of AI and ML along with human intervention in improving auditing efficiency.

Proposed Analytical Framework to Assess Audit Risks

The risk-oriented audit approach has been being applied in China since 2006 when Chinese Certified Public Accountants Auditing Standards (CCPAAS) was issued by the Chinese Institute of Certified Public Accountants (CICPA). However, most small-and medium-sized CPA firms in China still have difficulty in assessing the audit risk in accordance with CCPAAS with efficient and effective analysis and analytical procedures. Also, there are few studies introducing how to apply analysis and the analytical procedures with the risk-oriented audit approach as it requires external assistance and complex computer procedures. Therefore, this study aims to establish an analytical framework on how to apply analysis and the analytical procedures efficiently and effectively for small-and medium-sized CPA firms in China. It is based on DuPont model assessing the rationality of indicators, which is familiar to the financial officers and auditors. It proves that such an analytical framework is simple to perform since it can easily combine the information based on strategic analysis, business analysis and the analysis of financial statement from personalized audit and audit staffs at all levels can work with it. Under the premise of ensuring the quality of audit, this analytical framework can improve audit efficiency and reduce audit costs that most small-and medium-sized CPA firms need badly when facing challenges.

The Association between Audit Partner Busyness, Audit Partner Tenure, and Audit Efficiency

The main purpose of this study is to provide evidence of how audit partner busyness and tenure are associated with audit efficiency. Based on a pooled OLS regression analysis of 232 observations from non-financial companies listed on the Omani capital market between 2013 and 2016, the results reveal no association between partner busyness and audit efficiency—although it does improve audit efficiency for clients of the Big 4 audit firms. Moreover, longer partner tenures are shown to significantly enhance audit efficiency. Given the lack of evidence currently available, this study reinforces the importance of examining audit outcomes at the level of audit partner, providing important insights into audit efficiency for regulators, companies, and auditors. Overall, this study is one of few presenting empirical evidence on the importance of the characteristics of partner incentives in the context of audit efficiency.

Edge-based auditing method for data security in resource-constrained Internet of Things

Abstract The explosive generation of Internet of Things (IoT) data calls for cloud service providers (CSP) to further provide more secure and reliable transmission, storage, and management services. This requirement, however, goes against the honest and curious nature of CSP, to the extent that existing methods introduce the third-party audit (TPA) to check data security in the cloud. TPA solves the problem of unreliable CSP but puts a heavy burden on lightweight users because of the sheer amount of the pre-audit data processing work. In this paper, we establish an audit model based on a designed binary tree assisted by edge computing, which provides computing capability for the resource-constrained terminals. The data pre-processing task is offloaded to the edge, which reduces computing load and improves the efficiency of task processing. We propose an improved correlation mechanism between data blocks and nodes on the binary tree so that all nodes on the binary tree can be fully utilized while existing methods use only leaf nodes and thus are required to establish multiple binary trees. Moreover, to improve audit efficiency, the binary tree in the audit process is designed to be self-balanced. In experiments, we compare our methods with the traditional method and experimental results show that the proposed mechanism is more effective to store and manage big data, which is conducive to providing users with more secure IoT services.