A Big Data-Driven Financial Auditing Method Using Convolution Neural Network

Abstract

In the big data era, traditional auditing methods are facing challenge such as limited audit scope, uneven distribution of audit power, and insufficient audit analysis. To pursue high efficiency, the utilization of big data analysis technique in financial auditing has been a novel tendency in this area. The deep learning has been popular in many areas due to its high freedom degree. Thus, this paper employs a typical deep learning model convolution neural network (CNN), and proposes a big data-driven financial auditing method using CNN. Specifically, the strong ability of feature abstraction of CNN is leveraged to extract multi-level features in materials, such as visual features, textual features, etc. Then, the multi-source features from auditing materials can be well fused for final discrimination. Some simulation experiments are conducted on real-world financial auditing scenes for assessment. And the results show that the designed the proposed financial auditing method possesses relatively high auditing accuracy.

The Correlation Between the Size, Independence and Experience of Internal Audit and its Impact on Reducing Financial Corruption: Evidence from the Public Sector in Iraq

“…Conventional auditing techniques encounter obstacles in the age of big data, such as restricted audit coverage, unequal allocation of internal auditors in quantity and authority, and inadequate audit analysis. To achieve high efficiency, the use of big data analytics technology in financial auditing has been a new trend in this field (Zhao & Wang, 2023), and today the impact of artificial intelligence on internal auditing has become broad and multifaceted, and artificial intelligence models such as ChatGPT are not just tools, but an effective means for internal and external auditors, and help them detect and assess risks, generate reliable information (Alarcon et al, 2023) and assist in decisionmaking, and through operational auditing, internal controls and efficiencies can also be evaluated as it includes some areas of organizational structure, processes and procedures, data accuracy, asset management and security, employment and productivity (KASSAYE, 2023), and government internal auditing seeks to ensure the quality and suitability of the systems followed by the government institution, and the extent of its commitment to legal requirements regarding contractual obligations, and regulatory compliance is also considered the most influential determinant of the quality of internal auditing, followed by independence and time pressure (Samagaio & Felício, 2023) In order to accomplish its objectives, the government must enforce compliance among internal auditors in the public sector with the ethical standards of the auditing profession. These standards encompass confidentiality, honesty, objectivity, independence, impartiality, and professional competence (Ibrahim & Al-Maini, 2023).…”

The Assessment of Audit Evidence in Big Data Environment A Field Study

“…Overall, the study concludes that BD has the potential to revolutionize the auditing profession. Moreover, Zhao & Wang (2023) aimed to develop a new financial auditing method based on BD and neural networks. The basic idea is to use neural networks to detect patterns in financial data that may indicate fraud or manipulation.…”