Let Big Data help you and your company make more intelligent decisions!
Big data is an evolving term used to describe large volumes of both structured and unstructured data, originating from a variety of sources. Big data includes information collected from social media, video and emails, and encompasses any and all data that is gathered in order to provide real-time business insights.
As big data grows exponentially, it is frequently utilised for the benefit of ongoing business analytics; helping individuals and companies make faster and more intelligent short and long-term decisions. However, as big data is frequently comprised of large and disparate volumes of data, it requires advanced and innovative technology in order to collate the wealth of information available, into actionable and meaningful insights.
The Big Data Difference
The rapid development in technology and data-processing has transformed the way that businesses generate and process the data and information required to remain competitive. As the exponential growth and availability of data-mining opportunities for businesses shows no sign of slowing, organisations are demanding more from their analytical services.
The auditing profession is one such service and profession that has been shaped by increased expectations as a result of the availability of big data. Technology has enabled the use of analytics in auditing to become both streamlined and readily accessible. With a wealth of readily accessible data available to be analysed and utilised and with businesses making the transition to cloud-based technologies to store their data; big data is transforming what is required and expected of auditing services to remain competitive within the industry.
Leveraging Big Data in Auditing Processes
The explosion of technology in the recent decade has transformed the nature of competition in the business world. The wealth of data available for businesses to utilise and store, has led to significant changes in corporate risk governance and controls. For this reason, recent years have seen the rise of big data being utilised in corporate governance and being embraced by leading businesses, enabling companies to remain competitive and profitable in the volatile global marketplace.
Risk management and corporate governance have become increasingly complicated and modernised by technological changes and the exponential growth of actionable data. Individuals and businesses are increasingly in need of progressive and advanced data analysis functions, in order to better identify and manage the changing risks of the modern corporate climate. The insights required to protect an individual or business now extend well beyond the traditional financial statements audit. The Australian Auditing Standards, which outline the scope of an external audit, do not provide much guidance on whole of data testing and as such, the scope of an external audit is limited.
Business owners and Directors should consider special purpose engagements beyond the scope of the statutory financial statements audit to delve deeper into their organisations’ data trends.
Companies have been transformed by utilising big data in their business, marketing and management operations.The transformation of business management operations in this ‘Age of Digital’, provides auditors with a volume and speed of data collection that has never before been offered. It is therefore imperative for Audit Standard setters to evolve and adapt the Auditing Standards to cater to the changing environment. There is also an increased expectation from businesses that their auditors make use of big data analytics, in order to provide valuable and actionable insights.
The Future of the Audit Industry
Big data is likely to expand the scope of analytics from sample-based testing to the availability of a range of relevant data from both structured and unstructured sources. Whilst the ‘traditional audit’ involves the analysis of samples of data taken from a particular period, it is expected that the future of audit analytics will see data monitored on a continuous and constant timescale.