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Preparing for the Next Generation of Auditing

Author: Grace Johnson, CPA

Increasing the need for data analysis is increasingly needed in conducting audits, especially in the face of rapid changes in an organization by executing developing audit technology

Programming Language

The South African chairman of the International Integrated Reporting Council wrote:

The megatrends the world is facing, including climate change, the fourth industrial revolution, globalization and artificial intelligence, demand a modern audit profession capable of attracting the skilled professionals to provide the assurances services needed by 21st century businesses. The risks and opportunities facing the global economy 20 years from today will require a profession that is flexible, agile and responsive to remain relevant and avoid the risk of extinction.

Professional leaders in the fields of accounting and finance, industry and government have benefited and brought data analytics to fields, such as compliance and risk management, internal and external auditing, financial statement preparation, and fraud identification.

There are several environmental factors contributing to the more widespread adoption of data analytics in business, accounting and auditing. It is important to identify competencies needed by auditors to ready themselves for work with data analytics tools and techniques.

The Data Analytics Explosion

What has created the business case for data analytics? There are three reasons why data analytics has garnered increased attention and use:

First, tools used in analytics are more powerful and sophisticated. Second, the unstructured and structured data used in data analytics have grown in volume. Finally, businesspeople have become more focused on basing decisions on quantifiable data. It has been observed that in a “data-driven decision making culture, there is opportunity for accountants to move beyond optimizing the accounting function to transforming the enterprise.”

More Powerful and Sophisticated Data Analytics Tools

Based on a survey conducted, there are three aspects of data analytics technology have led to its more widespread use: data visualization, social media analytics and statistical analysis. The use of data analytics has become common in large organizations, especially in the areas of risk management and compliance, data analysis techniques such as preventing fraud on all transactions carried out in real-time or comparing any unusual transactions with typical data patterns.

Growth in Data Volume

The term "big data" refers to data characterized by their tremendous volume, velocity and variety (called the three Vs). These three characteristics have not changed in the years since big data and data analytics rose in prominence, but the extent to which such data are available has. There are more data coming at business users faster and in formats and from sources that were not considered mainstream even several years ago. Managing ever-expanding volumes of information is a strategic problem identified by 300 C-suite executives from 16 countries interviewed in 2015.5

One of the panelists on a March 2018 webcast shared comments from C-suite executives, saying, “All of a sudden, data that was buried in a grave somewhere is coming to life. We have to make sense of it and use it as an asset.”

Data-Driven Perspective

Changing habits of the mind can be difficult and demand a shift in how the corporate culture values decision-making driven by data. In business environments characterized by emergent situations, complexity, randomness and experimentation, an analytic mind-set is required to make the most of the data to which employees have access. Challenging managers and employees alike is the increased use of predictive analytics and its capacity to alter how organizations undertake forecasting tasks that range from creating annual budgets to determining strategic merger and acquisition activity.

A partner at PricewaterhouseCoopers, Singapore, comments that data analytics has the capability to transform auditing from a profession working with data from the past to one that adds value and helps enterprises anticipate the future. Although his comments specifically focus on the internal audit function, they can be extended to audit and accounting practitioners generally. He suggests that:

"those that can adjust in more real-time and establish an end to end data driven Internal Audit model, will elevate their relevancy and allow them to move from simply auditing around historic risks to monitoring and pivoting based upon prospective risks."

Many of these skills can be gained through self study, while others, such as identifying key data trends, can be gained through work experience. Accounting professionals can participate in data analytics-related webinars provided by public accounting firms or IT consultancies. For more casual learning approaches, there are online videos prepared and uploaded by individuals or organizations.

Data-Analytics-Related Competencies for Auditors

Effective work with data analytics demands that auditors have a broad range of competencies that cut across liberal arts, business, information technology and communication fields. These competencies vary in importance and frequency of use depending on employment setting, position and career stage.



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