Audit data analytics generate a lot of value for organisations, both public and private. While most companies are using software for auditing purposes, there is still much to gain from data analytics. The explosion of big data, IoT and AI mean that information is power, and organisations need to integrate big data into their processes. By integrating specialised software into auditing, organisations achieve new levels of operational efficiency that lower costs, raise revenue and diagnose problems they didn’t know existed. Investigating business operations is a cornerstone for success and improving it reaps tremendous benefits in the future.
Audit analytics software expands the capabilities of an organisation’s accounting team by allowing them to integrate larger data sets.
When an accounting department compiles financial statements or when marketing wants to analyse the market position, they often use data sampling. Sampling has been integral to auditing for several years, but there is one significant shortcoming: It only provides a small view of the organisation’s overall health. Samples construe a small portion of the entire dataset, and it is impossible to get a 100% accurate view of the company’s financial position using only a sample. So why do organisations use them? Simple. It is easier to analyse smaller datasets than an entire data lake. However, with companies generating petabytes of data, smaller sample sizes are no longer sufficient for meaningful findings. This is where audit data analytics is useful for organisations.
Auditing big data is possible with audit data analytics. Analytics software possesses the architecture to handle an organisation’s entire dataset, instead of just a small sample. Accounting and marketing departments can analyse every byte of data collected and even integrate external data sources for a more comprehensive analysis. Audit data analytics can analyse vast amounts of data by using automation, making it easier to generate high-quality reports. By auditing the entire dataset, instead of just a sample, organisations can create detailed, yet accurate audit records for analysis.
With the option to analyse entire datasets using audit data analytics, it is easier for organisations to discover anomalies in operations. No organisation runs perfectly. There are inefficiencies in processes, some of which are obvious to employees and ones that are not as clear but hurt the organisation. Audit data analytics software exposes anomalies in processes harming productivity. With thorough analysis, organisations will discover the areas where they are struggling and will have an easier time devising solutions that improve productivity. Analysing entire datasets makes it easier to expose anomalies and shortcomings in work processes.
Audit data analytics can do more than just analyse operations in context, they can also anticipate the future. Audit data software uses predictive analytics to predict the state of the organisation in a specific period. To predict the future, data analytics draws on company archives to compare the information, against several microeconomic and macroeconomic indicators. Auditors can anticipate future risks for the organisation, and minimise its impact using analytics tools. The predictive capacity of audit analytics can be used in future projects during a cost-benefit analysis, making it the best way to minimise risks and maximise rewards.
The analytical capabilities of the auditing team expand thanks to the right software. Not only can the team assess the company’s current financial standing, but auditors can also assess the company’s market position. Audit data analytics draws information from specific sources and data models to identify unique benchmarks and patterns. Auditors can also use the information to compare company performance against industry standards. As a result, managers and executives can then use these performance indicators to set new KPIs for the future. The new information provides greater context, which helps when setting new goals for company operation.
Audit data analytics generate value for organisations by expanding the auditing capabilities of the organisation. The option to incorporate the entire dataset, as opposed to a small sample improves the accuracy of findings by a considerable margin. Furthermore, several platforms come with other benefits beyond better audit capabilities, including better cybersecurity and visual representation of complex datasets. Incorporating audit data analytics into company processes provide tremendous benefits for organisations.