Data Analytics in Auditing

While data analytics has tremendous potential to improve audit work, there are many challenges that must be addressed before widespread use of data analytics in auditing becomes a reality. It is food for thought intended to provide a relevant and specific research question. Despite the academic interest in data analytics, empirical academic research related to data analytics in final trials is still in its infancy.

Big data is defined as “large, fast, and diverse information resources that require cost-effective and innovative forms of information processing for advanced insight and decision making.” The characteristics of volume, velocity, and diversity describe the characteristics that make big data unique and are often referred to as the three verses of big data. 

There are four main advantages of using analytics in auditing.

  1. Auditors can test a greater number of transactions than they do now

  2. Audit quality can be increased by providing greater insights into clients processes

  3. Fraud will be easier to detect because auditors can leverage tools and technology that they already use

  4. auditors can provide services and solve problems for their clients that are beyond current capabilities by utilizing external data to inform audits

According to his Jim Liddy, KPMG's vice chair of audits and regional audit lead, the LLP's U.S. practice said: Ability to sort, filter and analyze tens of thousands or millions of transactions to identify anomalies, making it easier to focus on potential areas of concern and sort out the highest risk items.

Despite the promise of data analytics for improving audit quality, there are numerous challenges to widespread implementation of analytics on audits

  1. Training and expertise of auditors

  2. Data availability, relevance, and Integrity

  3. Expectations of the regulators and financial statement users

While there is great potential for improving the quality of audits using data analytics, there are significant hurdles to overcome. Academic research can inform the myriad of issues organizations face when developing these approaches, but with increasing pressure to apply data analytics to testing, time is of the essence.Organizations are investing in big data to improve their decision-making and expect auditors to be able to use big data to improve audit effectiveness and efficiency.Educating students for the public accounting profession and providing existing accountants with enhanced skills to effectively perform data analysis will help academics fill the skill gaps associated with DA in accounting and Another way to help you meet your professional challenges.


CE, Early. September–October 2015. Business Horizons Volume 58, Issue 5 Pages 493-50