THE ROLE OF BIG DATA IN AUDITING AND ANALYTICS
Big data is the new wave that’s taking over company operations by storm. Businesses that are able to leverage the volume, variety and velocity of big data can make better decisions, reduce operational costs, and keep up with evolving customer demands. Big data is being used in many different sectors. From manufacturing to banking and supply chain management, the ability of companies to collect and analyze data in real-time is a valuable asset that drives growth.
Unfortunately, the auditing industry has been left behind when it comes to big data and analytics. Both internal and external auditors haven’t fully leveraged real-time data insights to manage compliance and ensure that businesses are harnessing the full value of their potential. There are multiple uses cases for big data in auditing. By collecting information regarding past events, predictive and prescriptive analytics can be used to estimate the likelihood of future outcomes. Furthermore, auditors and other stakeholders will have a higher level of confidence when it comes to analyzing the effectiveness of specific company operations.
The role and applications of big data in auditing can be challenging to visualize. This piece will explore how big data can be applied to streamline the auditing process.
The Benefits of Using Big Data In Auditing
Many stakeholders don’t view the auditing process as applicable during big data analytics. However, real-time data analysis can be applied in many different ways to benefit auditors. Auditors can use big data to expand the scope of their projects and draw comparisons over larger populations of data.
Because big data involves the use of automation and artificial intelligence, data can be processed in larger volumes and higher velocity to uncover valuable insights for auditors. For example, previous cases of non-compliance, current policy changes, and fraud can be identified and used to guide the focus of both internal and external auditors.
Big data is also helping financial auditors to streamline the reporting process and detect fraud. These professionals can identify business risks in time and conduct more relevant and accurate audits.
Even before you can take advantage of analytics during auditing, you need adequate data management and aggregation processes in place. All data sets being analyzed for the purpose of auditing first need to be checked for accuracy, timeliness, and capacity. In this way, the downstream decisions that auditors make are based on reliable and high-quality information. This is particularly important when it comes to auditing because decisions regarding compliance, risk, and investment are typically made after audit reports are prepared.
Big data also allows you to automate multiple portions of the auditing process. Human error is a common reason why businesses fall out of compliance or spend too much on audit-related requirements. By automating manual and repetitive tasks, auditors can set up various controls in advance and monitor how well a company is adhering to established guidelines.
How Big Data Can Be Used To Streamline Auditing And Analytics
The applications of big data in auditing are widespread. However, many companies haven’t figured out how to fully leverage the power of big data to make auditing more accurate, more reliable, and less costly.
The best way of taking the next step in big data is by starting on the right foot. You need to be able to collect, aggregate, and analyze data in a manner that provides valuable insights. You also need to devote adequate resources to the support of internal auditing tasks. For example, providing access to critical data and collaborating with multiple departments will help auditors prepare more accurate, dependable, and timely reports.
If leveraging big data for auditing is your primary objective, consider following these steps.
• Start with an end goal
Even before setting up algorithms or statistical models for analyzing audit data, you should first determine what your end goals are. Senior management and internal auditing staff should be involved when making decisions regarding an internal audit.
• Develop teams with adequate resources and technical skills
The next step is to identify any gaps in infrastructure and manpower. You may need to hire talent that can analyze data in real-time and help manage large information silos. You should be prepared to provide adequate support, including training and robust methodologies that can be repeated multiple times down the road.
The benefit of having a reliable method in place is that you can strategically implement analytics into each step of the process. In this way, you can automate mundane tasks and use artificial intelligence to make more informed business decisions.