Data is something that an organisation hold and it can be presented in multiple formats. However,?rapid advances in technology have caused many changes in the data definition. Today, analyst and data scientist termed data as unstructured and machine-generated and something that is beyond corporate boundaries. Big data is the term used to describe a huge collection of data which is growing exponentially. For an organisation, the general view is that big data is going to make a huge impact on their productivity, profits, and organisation management. But the problem is big data has very limited value until it is processed and optimised for further discovery.
Analytics is the process of analysing, scrutinising and optimising data with the objective of drawing meaningful patterns. The business organisation have recognised this opportunity that big data possess all the capacity to make huge impacts on their business. There are different areas where the impacts of big data are seen and one of these areas is an audit.
Transforming the audit
As we continue to operate in one of the wonderful periods of technology, the role and the importance of financial auditors in the financial markets is more important then it was earlier a few decades ago. Audit firms must continue to invest and operate in audits to serve the customers by increasing quality on a continuous basis and by delivering deeper knowledge of financial statements. Meanwhile, companies are making a long conversation with their auditors and more relevant pictures. While the professionals have earlier recognised the impact of data analysis on audits, mainstream use of big data and analytics have been hampered due to lack of proper machine and technology. Today, the problems arise with data captured and concern about privacy. However, modern science and technology are making big advancements in big data and analytics to rethink about how an audit can be improved in a better way.
The improved and transformed audit will grow beyond the prediction to include better analysis of every people for audit-relevant data, using artificial intelligence and machine learning. Big data and analytics are helping auditors to identify better financial reporting, frauds, and operational business to deliver better results. While we are still exploring the benefits of big data and analytics in the audit, we observe that we have to a long way to complete this journey. One of the best is Netflix. When Netflix was first started in 1997, they first adopted DVD by mail order means sending movies to its customers. Netflix was aware that the future is in online streaming but it has a long way to go.
Problems faced during integration by Analytics and Big Data
There are large numbers of problems faced during successful integration:
The first problem is data cauterisation when auditors are unable to collect and manage company data from the various sources. Hence they will not be able to use analytics in the audit. Customers want to keep their data safe. And the company spend a huge amount of saving customer data.
Hence, it becomes quite complicated to obtain customer data after customer approval. In some cases, it is observed that the company has refused to provide data because of privacy reasons. Moreover, it is observed that auditors have to encounter multiple systems for data extraction. Data extraction is the biggest problem for the auditors and hence companies avoid such competency. These create multiple problems for the companies and for the auditors on data capture.
Today, the extraction of data is highly dependent on general ledger data. However, applying big data and analytics in audits means extracting sub-ledger information such as revenue and general information essential for business purpose. This increases the complexity to process huge amount of data extraction and the volume to be processed. It is easy to use descriptive analytics to understand the business and calculate the essential risk associated with them but using analytics in audits is a very difficult and complicated task.
The value of assembling dig data and analytics into audits will only be useful when auditors can easily understand the scope, nature and extent of the audit. This requires them to understand the new technology used to explore data and use of analytics to draw audit conclusion, produce audit evidence and derive meaningful patterns from business insights.
Analyst and data scientist are working on how to use data analytics and big data for auditing standard, working and regulations. In general, auditing is governed by the methods and technique that were adopted a few decades ago and this does not include the importance of big data and analytics. Here are a few points that require further considerations:
Validating the data used for analytics:
As auditors receive information from the customers, they apply their basics and expertise to derive some conclusions, but they are not aware whether this information is appropriate as audit evidence. This includes data in the paper as well as in the digital format. But audit analytics does not use or depend upon the reports processed and generated from the system, instead they directly access underlying data stored in the system. Then different tools are exacted and applied to validate the accuracy and complete information from the data and then it is reconciled with the system generated reports. This process makes auditor confident about its analysis based on the same data which the company uses to report its financial information.
But there are some limitations. Big data and analytics can provide some standard information from these data but they can not evaluate the type and volume of data that are being processed or used by the auditors.
Defining audit evidence:
The data provide the bulk of evidence, with third party evidence at the top and management evidence at the bottom. However, they do not display what type of evidence analytics provides. Although some of the evidence can b displayed it is impossible to display all of them at once. Without the proper description of the types of evidence provided by the big data and analytics, auditors are very confused to claim the type of evidence hence they lose big opportunity to display evidence benefits.
Accuracy and precision:
The main function of the audit is to detect a different misstatement. While company records revenues amounting to billions and billions of dollars, they expect these records to be free from multiple misstatements. Thus, auditors are required to do financial reporting with high precisions and accuracy.
Ultimately, an audit of the future looks completely different from the audit of today. Auditors will be able to use tools and technology for better understanding of business, identifying crucial risks and delivering good quality of information which will be more valuable for the business work. But to achieve this, business needs to work and monitor the auditing and the technology