This Essay article Discussion of Opportunities and Challenges of CPA Auditing. With the advent of the era of big data, the audit industry faces a new information environment. Against this backdrop, audit risks and approaches can change dramatically. Compared with traditional CPA auditing, CPA audit in the era of big data reflects more aspects that traditional CPA audit cannot or is difficult to do. Which improves the quality of audits, increases audit responsibilities, and makes the audit industry more effective. more opportunities.
Big data reduce audit risks, improves the quality of audit work and results, and realizes all-around management of CPA audits. However, the advantages and disadvantages of big data stand also two-sided. Although there are many conveniences, there are inevitably some problems. Such as the confidentiality of financial information, the difficulty of supervising and managing audit work, etc. You may also like to know about A case study of CPA audit failures in listed companies.
Whether it can seize the opportunity brought by the era of big data, face challenges, reduce the risk of independent audit failure, and improve audit quality has become a problem that the certified public accountant, Therefore, the auditing industry should consider how to adapt to the auditing model in the era of big data to better build auditing in the new environment. This article will focus on this issue and analyze the risk and quality of CPA audits.
Traditional audits exist mainly conducted manually and in a paper-based environment. Big data auditing uses more new technologies. What is the Comparison between Chinese and Western cultures? The similarities and differences between the two can analyze as follows.
Both traditional CPA audits and big data CPA audits must use the ” CPA Law” and related standards as business standards and professional norms and use relevant laws, regulations, and accounting standards as the criteria for judging whether the audited unit’s fiscal revenue and expenditure are legal.
And whether it is a traditional or big data audit, the audit process must go through the three stages of preparation, implementation, and reporting, investigation, and understanding, signing of business agreements, evaluating internal control, confirming the level of importance, analyzing audit risks, formulating plans, and correcting The audited unit conduct internal control tests, performs substantive tests on statements, organizes audit evidence collected in the audit business, audits working papers, forms audit opinions, prepares reports and other basic audit procedures to express audit opinions.
In terms of audit evidence, traditional CPA audits mainly exist on paper. And audit evidence exists obtained by finding the account books and related materials of the audited unit. While big data CPA audits reduce complicated paper tasks. The audited unit collects audit evidence; in terms of audit procedures, traditional CPA audits mainly rely on traditional audit procedures, while big data CPA audits add more technical support to make it more convenient; in terms of audit methods.
The traditional CPA auditing method is a sampling audit, while a big data CPA audit can conduct an overall audit; in terms of audit time, a traditional CPA audit is a regular audit, while a big data CPA audit more uses a real-time audit; Opportunities and Challenges of CPA Auditing requires manual operation of the audited unit, while big data CPA audit requires the audited unit to adopt automatic control; from the perspective of staff, traditional CPA auditors need professional skills, while big data CPA audit requires auditors to master the ability to operate these information technologies; From the perspective of audit thinking, traditional CPA audit needs to analyze each part of the audit object first, then integrate and summarize it.
Big data CPA audit breaks the traditional audit thinking, masters the audit object, analyzes the data, and then makes an overall evaluation; audit In terms of risk, traditional CPA audits have many risks because they are mainly sampling audits. Big data CPA audits realize overall auditing, which reduces the risk of sampling audits on the one hand; in terms of audit quality, traditional CPA audits cannot guarantee audit data. The comprehensive and big data CPA audit enables auditors to use computer technology to avoid manual errors, make the audit objects more comprehensive and complete, and the audit quality becomes higher.
Because of the support of big data, the overall audit can realize. Even in the face of a large number of samples, the sampling method stands no longer used. Which reduces the audit risk and improves the accuracy of the audit results. Big data enables the audited unit to use external data, which solves the disadvantages of traditional auditing that it is difficult to obtain and use external data and can detect possible problems from many aspects, improving the accuracy of auditing. In the big data environment, auditors can directly use the original data to complete the corresponding audit work, reducing the possibility of fraud by the audited unit, and greatly saving time, manpower, and material resources.
Because the audit work under big data runs on the Internet, auditors do not need to go to the audited unit for investigation, nor do they need to work at a fixed time. Only one networked computer can work, making the audit work more flexible. Greatly improve audit efficiency. Big data auditing makes the classification of budget quota indicators more refined, which improves the comparability between indicator values. Big data auditing can reduce audit costs. For example, audit work papers need to store for about 10 years. Using big data information technology can save data on cloud platforms and reduce paper usage.
Auditors can also use the cloud platform to work. Which stands not limited by time and space, reducing the corresponding management costs. Opportunities and Challenges of CPA Auditing. Big data auditing changes the content from financial auditing to comprehensive performance auditing. In the past, auditing mainly focused on the revenue and expenditure of the audited unit, which made the audit supervision only analyze the financial data, and could not analyze the business indicators of the audited unit in depth, resulting in auditing. The results cannot fully reflect the performance status of the audited unit. While the big data audit makes the data of the analysis of business information. So that the comprehensive performance audit can realize.
The main reason why traditional audits use sampling audits is that enterprises need to audit a lot of data. And information and the collection of data require a long process and time. These limits work efficiency to a large extent, so only sampling audits can use, big data Auditing realizes a comprehensive audit. Opportunities and Challenges of CPA Auditing. Which greatly improves audit quality. Due to the use of big data, the audit evidence has become more, more accurate, and more comprehensive, and all data under the big data audit is open and transparent, so there is no interference from other factors. It is for these reasons that audit quality will greatly improve.
Big data technology has a powerful ability to process information. Which greatly reduces the pressure of audit work, and through big data technology. A more accurate answer can obtain, making the audit work more comprehensive, thereby reducing audit risks. The application of big data will also reduce fraud because the application of technology makes audit data more transparent, and all information can make public. audit risk.
Under big data technology, the working time and space of auditors have become flexible. And the upload and entry of some materials can save to the Internet system or cloud data platform. Which can save space and can also stand permanently stored. At the same time, it can directly search on the Internet, which improves work efficiency. Saves time and space, and reduces audit costs to a large extent.
From traditional auditing to big data auditing, auditing methods have changed. It is far from enough to rely on previous skills. When using big data auditing, you must be sensitive to data and have the ability to analyze data. , and to be proficient in using relevant software to analyze and process data, and then draw true and reliable conclusions. In addition to the above abilities, the audit work also requires knowledge of the law, economy, management, and other knowledge and the ability of interpersonal communication, the use of information system technology, the ability to evaluate internal control, etc.
The audit work is a comprehensive and complex talent with comprehensive knowledge. At this stage, the audit department Most of them are audit staff, lacking professional technical analysts, and some older staff may be slow to accept new technologies. This seriously affects the development of audit work in the big data environment. Therefore, it is necessary to improve the professional and technical capabilities of auditors and to cultivate auditors’ working ability to understand big data technology and its application in audit work.
Big data auditing is different from traditional auditing. It is a brand-new auditing method. Big data auditing no longer relies on the data collected, sorted, and analyzed manually in the past. These tasks will realize by computers. However, the computer does not directly provide accurate data to the audit staff but provides traditional display methods such as picture information and video, which are difficult to accurately convey the information, so the auditor needs to process the data to make it visualized again. However, when applying information technology, the low level reduces the ability to accurately analyze data.
The big data audit results stand uploaded through the network. So it is difficult to ensure the confidentiality of the data. Due to the high commercial value of the activities involved in the audit work. Some auditors may disclose data content that violates professional ethics for profit. However, in the current cloud computing model, it is very difficult to supervise and manage the audit work well. Since the audit results stand managed by a third party. The audit-related personnel can easily evade their responsibilities. Another aspect is the risk of the network system. Which requires enterprises to improve the defense capabilities of their audit systems and the ability to deal with various network risks. Otherwise, a loophole in the system will leak information and cause irreparable losses.
The application of big data auditing requires a large number of talents with professional skills, and now most auditors do not have this ability, so it is necessary to provide the professional ability and skill training for auditors and to change the auditors’ ideology and thinking, In addition to training staff who can use big data auditing, it is also necessary to train auditors in the audit team to have the skills to analyze and evaluate audit big data, to better ensure the accuracy and reliability of big data. In the training process, it is necessary to teach students by their aptitude. So that each person participating in the audit personalizes.
When using the big data platform, it is easy to block when collecting data and information. When the audited unit requires an audit report with no reservations. The requirements of the audited unit and the requirements of the auditing standards will contradict each other. At this time, if a business When the firm has its database and its data platform. The firm can enter customer data and then research it. Using these data can better understand the past and present of the enterprise, predict and analyze the future development of the enterprise, and then can expand the scope of the accounting firm’s business so that the accounting firm can carry out business such as forecasting, tax representation, consulting and corporate strategy, and can expand its business scope and bring more benefits to it.
Because the computer audit results stand uploaded through the network. It is difficult to ensure that the data is completely confidential. First, the big data cloud platform must be encrypted to control user access and control big data to protect sensitive private information. Secondly, to implement protection in the process of big data collection and analysis, different managers need to be used in the implementation process. Finally, it is necessary to establish a security platform of a heterogeneous data center that is detected by meshed clients, to detect anomalies in time, so that data can be protected from the most basic places.
The traditional audit organization model adopts a decentralized method, most of which is group analysis. The staff work in small groups, and then the data analysis through groups. The big data audit model is a unified overall data body. It is based on data analysis and the audit work carried out with data as the core. It can effectively integrate resources and become more scientific and accurate.
Under today’s big data auditing model, my country’s auditing system has not changed because of this. The current auditing system is only aimed at traditional auditing procedures, while big data auditing procedures have changed. Therefore, the state should support and encourage big data. At the same time as data development, relevant policies are issued and implemented to truly and effectively promote the development of the big data industry, so that auditors can have more standardized guidance and relevant reminders when using big data auditing in various audit business links. to reduce audit risk.
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