Business Advisory Automation

Accountants also serve in various business advisory roles outside statutory accounting, audit, and tax. Indeed, many accountants advise or work in functions such as managerial accounting, financial planning and analysis, internal audit, compliance, forensic accounting, or information systems (IS) audit. These functions also have been significantly impacted by Al and machine learning technologies, involving data mining of both textual and non-textual data.

For example, corporate documents combined with social media and other textual data sources can be a rich source of information for assessing an organization’s adherence to regulatory requirements such as privacy and security, compliance with labor laws, or compliance with industry-specific regulations (e.g., “Know Your Customer" laws in financial services).

Functions such as internal/operational audit, IS audits, or enterprise risk management require internal auditors to review copious amounts of written documentation from various sources. As Daniel Torpey, CPA, and Vincent Walden, CFE, CPA of Ernst & Young stated in their 2009 article:

To address the full spectrum of data sources surrounding enterprise risk more efficiently, internal auditors can now incorporate unstructured data or text analytics tools into their work plans.

... Text analytics tools can be used in the context of a risk-based internal audit, as part of a forensic review of controls or business practices, or during an actual investigation (p. 42).

The authors explain that most business transactions or events are likely to have email communication associated with them. Emails contain rich metadata (information stored about the data such as origin, version, and date accessed). This metadata is a promising source of information for internal auditors.

The authors cite examples of using text analytics technologies and point out that these tools can also be used proactively within an enterprise to understand risks and identify anomalies.

They mention the example of an internal audit director at a global technology firm. This firm used text analytics tools to assess compliance risk and help prevent regulatory violations for three acquisitions in the context of a recent increase in regulatory enforcement activity associated with the US Foreign Corrupt Practices Act (FCPA).

They conclude their article by stating, “By incorporating internal audit methodologies around text analytics, auditors can also enhance their proactive risk efforts and potentially improve business performance for the clients they serve” (p. 44).

In conclusion, text mining combined with Al and machine learning approaches provides significant opportunities for automating the work of accountants and auditors to a much greater extent than it is today. Although the use of these technologies is only developing in the accounting profession, we expect that they will dramatically change the way the work of accountants and auditors is performed, including:

• • More robotization of accounting tasks: meaning significant efficiency gains and more time spent on analyzing data versus collecting and recording data
• • More information analyzed: meaning greater accuracy, better insights, and improved decision making; and
• • More proactive and continuous monitoring of internal controls and audits: meaning more timely detection of anomalies or risks and improved business performance