What does the future hold for AI in accounting and automation?
Data analytics is becoming a more prominent feature in audits at present. The large firms have been using their own Data Analytics tools for journals testing for some time, however the last few audit seasons have seen many of the Top 100 firms begin to use Data Analytics as part of their audit approach.
Analytics tools are able to score for the auditor the risk involved with individual transactions, determined by a set of parameters written by the auditor. This allows the user to then easily sample the riskiest transactions with the Analytics tools to efficiently suggest to the auditor where the riskiest transactions are.
Where is this being used?
Data analytics is now being used in a number of different financial statement areas with the technology driven approaches that are evolving in the market:
• Journals testing – this is currently the most developed area of the Data Analytics tools and has been the area where the technology can assist the user in the most effective way. Tools are producing the riskiest journals and taking factors such as the time of the month the journal is posted, or whether that journal has been approved or not.
• Planning – The scores from each transaction enable the auditor to pick up any early trends in the dataset and this can be used at planning where risks may not be as obvious. For example, if the tool suggested a number of suspicious journals in the payroll process at month end, this may indicate there is a higher risk over Wages and Salaries.
• Sampling – The entire ledger is being used by Data Analytics tools to allow samples to be chosen rapidly for all of the different financial statement areas. Sales invoice samples are now being chosen at the click of the button which allows the auditor to request samples or conduct tests.
What does the future hold?
The long-term discussions on the future of AI have already begun. With the vast amounts of ‘big data’ available data scientists are able to pick up trends across industries rather than individual entities which could allow the auditor more scope to assess whether transactions are within the industry norms or outliers, enabling auditors to dig into issues and trends that are affecting their clients.
Therefore the scope of the audit can have an additional added value to clients with the ability to give suggestions to board meetings after the audit has concluded.
Other areas of development include the levels of testing in each ledger to go deeper into the sales or purchases. This would allow the auditor to select individual sales invoices that were not in line with the trends of that dataset and flag areas that the auditor may need to dig deeper.
The challenges that exist
With any new technology there is a period where the challenges of implementing the systems can outweigh the benefits. Some audit clients are reluctant to give their auditors complete datasets due to the complexity of some ERPs and even bad experiences with data analytics in its early days where specialist IT technicians had to come in to retrieve such data.
There is also the issue of training staff how to use such techniques. The ICAEW is now including Data Analytics in the course of the ACA studies, but staff members that are not used to these tools may be hesitant in learning to use them.
Once these challenges are overcome though, data analytics is a part of the audit process that will allow much more efficiency for the auditors and their clients alike, and could be integrated into other systems. At the moment this technology might be in the early stages, but in the future due to the competitive nature of audit tenders and the drive for the market to become more efficient, Data Analytics tools will become a requirement rather than a luxury.
This blog was originally posted to our website: www.CaseWare.co.uk