Technological advances and new software solutions enable auditors to engage in audit data analytics in a variety of new ways, such as exploration of large sets of audit relevant data from internal and external sources that may produce audit evidence used in risk assessment, analytical procedures, substantive procedures and control testing.
There are many benefits that may be gained for audits, including:
- Enhanced audit quality. By using data analysis techniques and methods, audit teams can start analyzing client data early in the audit process, enabling the teams to tailor the audit approach and deliver a higher-quality audit with more relevant audit evidence. These more advanced methods also support a forward looking, dynamic process of identification of anomalies, trends, correlations and fluctuations, pointing auditors to items where risks can be present. Further, performing transaction tests on entire populations rather than limiting testing to samples allows auditors to consider broader sets of audit relevant data and, therefore, produce higher-quality audit evidence.
- Increased audit effectiveness. Data analytics can be used to evaluate and assess large volumes of information quickly and can result in a better understanding of the entity and its systems. These methods allow auditors to perform more frequent testing at shorter intervals, rather than concentrating audit work around the year end. Engaging in continuous testing and monitoring of data leads to better informed risk identification, more accurate control assessments, and more timely and relevant audit reporting.
- Improved client service. Auditors always need to first comply with professional ethics and independence requirements when engaging with clients. Provided these requirements are considered appropriately, the use of data analytics can add value over and above the traditional audit of historical financial statements. Audit data analytics can provide unique opportunities to provide further insight into risk and control assessment. Communication with clients is enhanced as identified issues are raised earlier in the audit process and clients can see their everyday data analyzed in new ways, providing the possibility for a fresh look and the opportunity to understand their own information from a different perspective.
Given the significance of these benefits for practitioners, small- and medium-sized practices (SMPs), and professional accountancy organizations (PAOs) supporting their members, an Audit Training of Trainers (Audit ToT) Community exchanged ideas on this topic, as well as discussed some related tips which can be useful for practitioners when engaging in audit data analytics. The Audit ToT Community is part of the EU REPARIS Program (The Road to Europe: Program of Accounting Reform and Institutional Strengthening (REPARIS) facilitated by the World Bank Centre for Financial Reporting Reform (CFRR) and includes trainers from Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Estonia, Kosovo, Macedonia, Montenegro, Romania, and Serbia. Audit ToT is a training program with a practical focus that develops the capacity of audit trainers to deliver high-quality training and continuing professional development (CPD) programs, with a particular focus on meeting the needs and challenges of SMPs in implementing the International Standards on Auditing (ISAs).
These discussions have been summarized and published in a CFRR-related publication, Audit Data Analytics: Opportunities and Tips. Key messages include:
- Large accounting firms are already making significant investments in developing home grown tools and methodologies surrounding audit data analytics. Many SMPs have yet to introduce these advances and reap the benefits. Major investments are required, such as human capital, hardware, and software, as well as development of implementation capabilities.
On the other hand, expectations of investors, audit committees, regulators, and other stakeholders regarding the use of technology advances in the audit are evolving rapidly. Clients, even small ones, are becoming better equipped technologically themselves, and as they come to appreciate the benefits offered by data analytics, they will undoubtedly expect data analytics and technology to be used in the audit process.
It is becoming necessary for SMPs to start embracing the use of technology in the audit process. PAOs can support practitioners and SMPs in a variety of ways, including: providing education opportunities; raising awareness among clients and members of the key benefits; developing toolkits and guidance; researching and recommending software and hardware options, including generic data analysis tools; and providing members with support to convey their views, comments, and input to national and international standard setters.
- Many challenges and questions arise with data analytics in the audit context of today that may need further guidance, including: ability to test entire populations and how to deal with exceptions; fitting audit evidence derived from audit data analytics within the current requirements; clarifying what kind of audit procedures they are; and how to address the issue of the integrity of underlining data used and the need to validate data from non-traditional external sources.
Audit standards will likely evolve. Standard setters do not want audit standards to inhibit ongoing innovations in this area but also recognize the need for careful consideration before the process of amending audit standards can take place.
In September 2016, the International Auditing and Assurance Standards Board Data Analytics Working Group issued a Request for Input, Exploring the Growing Use of Technology in the Audit, with a Focus on Data Analytics. The paper informs stakeholders about the ongoing work in this area and gathers their input on whether all relevant considerations regarding audit data analytics have addressed before any revisions to the ISAs on Auditing are attempted. Comments are requested by February 15, 2017.
- Auditors will always need to have a good foundation in traditional technical competences, which are already a core body of knowledge studied in university and professional educational programs. However, a new set of skills will be required in the technologically advanced audit. Education is required in information technology, statistics, and modeling and this body of knowledge will need to be integrated in university and professional education programs for current and future accountants.
PAOs can play an instrumental role in this process by offering practicing members opportunities to engage in a learning process via training and CPD programs or other focused learning to develop the newly acquired skills.
- Many SMPs cannot afford to develop customized data analytical tools as the pioneering investments in hardware and software are a costly matter and simply beyond their resource availability.
There are several good alternatives that SMPs can employ. These include using third party vendors to process and analyze data and using simple but powerful generic database tools with functionalities designed for auditors, such as the ability to access a variety of data sources and perform source data tests that are automated, traceable, and repeatable.
- The potential of using technology, and especially data analytics, can extend beyond the scope of traditional audits. It provides practitioners and SMPs with an opportunity to engage with clients across a variety of service lines and in innovative new ways.
Auditors work with data on a daily basis and exploring new ways to analyze data is a natural evolutionary process for the accountancy profession. Provided auditors’ independence is not impaired, data analytics can be used to provide greater insights, offer consulting and advisory services, or engage via specialized assignments offering some targeted level of assurance in certain areas that provide clients with reduced risk and improved security.
The accountant’s role from report writer to business partner is also gradually changing because accountants spend more time analyzing the company’s results. Analyzing patterns or potential issues, as well as pulling data from different sources into one view where data can be overlapped and patterns can be recognized faster, may be especially beneficial for small- and medium-sized enterprises (SMEs), which lack in-house monitoring and controlling departments and rely on external auditors and/or accountants to provide a greater insight into operational and compliance risks.