Why accountants should lean more into their business intelligence skills

I have looked at the technologies that are being built in research laboratories at the moment. When they mature – and it is always a bit of a guessing game on time frames – many of the routine decisions and routine reporting around historical transaction data will be delegated to machines.

This is not necessarily bad news for accountants. Tasks like manual data entry or reconciliations are not the best part of the job. Machines can also take the pressure from the intense surges in workload that characterise accountancy work at month end or year end. And there will be a creative aspect to the changes, with new services needed to support the accountancy field.

What might be some of the chain demands that might emerge that accountants are ideally suited to?

New financial services

Imagine a world where the CEO of an organisation is able to test out the impact of changes in fiscal markers before taking a decision. You can start to maintain records on your client’s activities to predict the impact of known risks, such as predictable fluctuations in inflation or interest rates.

You can also model less common risks, a little like the impact of a hurricane or earthquake – you don’t know when and where they might hit, but if you’re in a typical hurricane path or across a faultline, then it makes sense to have a risk mitigation and management plan in place. Was it really surprising, for example, that the bubble on the Crypto currencies market burst eventually?

A shift to predictive analytics makes you a valuable partner in the turbulent years ahead.

Enhanced predictive analytics  are often enhanced by switching out the software that you are using for a tool that uses a time series algorithm with a powerful sorting algorithm behind some of the fields on your data set.

New methods of accounting

There are too many skills in the auditing process for machines to take over the whole thing. However, auditing is currently heavily reliant on determination and good fortune in the sampling phase.

We have seen the whole global economy brought down by mathematicians who created Triple A investment innovations back in 2006, which later turned into the toxic subprime markets. Bernie Madoff was running a ponzi scheme, Enron hid debts, Worldcom inflated their assets … the list goes on.

Regulators do not need any further evidence to convince them that mechanisms to introduce stability have been abused. Enter the possibility of whole-data auditing. Machines can identify anomalies quickly and reconcile data efficiently, meaning that the number of audits that is reasonable to carry out will increase.

Companies not run by corrupt leaders may also want to request stronger internal audit checks. AI based auditing solutions can quickly identify anomalies like duplicate payments and fraud indicators to improve and streamline the audit process.

This semi-automation leaves the human auditors to focus on higher-value tasks like interpretation of the context of the data, understanding or speculating why a situation may have arisen, and most importantly recommending next courses of action.

Anomaly detection algorithms are one of the entry level machine learning processes.

Load judgement work will be more in demand

With more data being produced and cleaned up or moved around in the back end of accountancy processes, it is natural that there will be an increase in demand for load judgement work, or the evaluation of a new stimulus. A machine can produce insights but it cannot give the data meaning or context.

Accountants may need to lean more into their business intelligence skills, and their understanding of decision making in strategic systems. They may need to lean into their understanding of regulatory environments, helping clients to navigate the increasingly complex regulatory landscape of data analytics. They may need to support AI auditing, helping clients to understand if the data processes that they are introducing meet minimum requirements of trustworthy AI.

Many of the switches to navigate through the coming changes require a redefinition of what an accountant is. There have always been many interpretations of the role in this vast field and Every new industry creates a chain of new supporting industries which it needs to function. There may have been growing concern over the past year around the destructive impact of AI on roles and jobs, but it will also have a creative impact.

This article was written by Clare Walsh, director of education at the Institute of Analytics