Using big data to identify tax risk: Introduce data analytics to the tax curriculum through a case study that requires students to explore the IRS' Statistics of Income database while reviewing an individual tax return.

AuthorBrink, William

Technology allows for the capture of immense amounts of data, as well as various tools for analyzing them. To harness the power of this phenomenon, accountants need to know what data exist and where and how to use them to improve their audit, tax, and business consulting work. Accounting students need to gain familiarity and practice with big data in their accounting, audit, and tax studies. This column provides background on usable data readily available from the IRS and a case study in which students can use the IRS data to assess audit risk.

Big data and tax

The increased use of technology has generated tremendous amounts of electronic information. This information, often referred to as big data, provides significant opportunities for those able to identify and use it. Because the amount of information collected is extensive, companies need help analyzing and interpreting the captured data, as well as assistance in finding ways to use the information in those data to improve business processes. As business advisers, accountants are strategically placed to capitalize on this opportunity. Public accounting firms also have the opportunity to use big data to improve their own business processes and provide more efficient and effective client services. All of the Big Four accounting firms and many other large public accounting firms have specialized teams dedicated to using data analytics and big data to solve complex business problems.

To take advantage of these opportunities, accountants need to develop the skills to work with big data. Professional accounting organizations, such as the AICPA and the American Accounting Association, have taken steps to inform and provide their members with numerous learning opportunities, such as by hosting annual big data conferences, webinars, and seminars on working with and analyzing big data, and creating numerous big data and data analytic continuing education courses.

At the university level, data analytics courses and degrees have been created. In addition, big data and data analytics have been incorporated into accounting curricula. While audit courses have found ways to incorporate analytics and big data into their courses, finding ways to incorporate big data into the tax classroom curriculum has been more challenging.

A review of accounting education journals shows zero data analytics case studies dedicated to tax-specific topics. One challenge tax professors face when attempting to incorporate data analytics into their courses is time constraints. Therefore, it is important for class projects to complement the curriculum rather than detract from it.

From a practical standpoint, one easy way to illustrate to students how big data is used in a tax setting is to discuss how the IRS and state tax agencies use data from millions of tax returns to statistically create discriminant analysis functions that assess a likelihood of noncompliance. This allows tax authorities to more efficiently conduct audit selections. Unfortunately, professors do not have access to the microdata that are used for this complex statistical analysis, but it is possible to introduce students to these data in macro aggregate form.

The IRS maintains and publishes statistical information gathered from various tax filings. This information is freely accessible on the IRS Statistics of Income (SOI) webpage (available at irs. gov/statistics/soi-tax-stats-statistics-of-income). Tax professionals can use these free statistical data to add value to client engagements by using them to assess a client's tax audit risk (the risk of being audited). The SOI database provides a plethora of data related to many types of tax returns (e.g., individual, business, and estate) in Microsoft Excel format that can easily be used by the public. Introducing students to the SOI database will give them a greater appreciation for big data and allow them to see how client risk can be analyzed. These data can also be used to obtain an understanding of the size and number of types of taxpayer entities, and various elements of taxable income.

The accompanying case study is designed to give accounting students and entry-level accounting staff experience using statistical information to assess tax audit risk, reviewing individual tax returns, and working with Excel. The comprehensive nature of the case study allows the user to look beyond the impact of income and expense items on overall tax liability to understanding how positions taken on a tax return may impact tax audit risk. Users must verify the accuracy of tax return amounts, prepare review notes, calculate corrected amounts, use the SOI data to analyze audit risk, and answer questions by working with the data.

The audit risk assessment portion of the case requires the user to prepare an analysis using Excel, thus reinforcing spreadsheet skills. Using Excel in this case provides two benefits. First, incorporating Excel into the class is consistent with the AICPA's Model Tax...

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