As workplaces change and undergo digital transformation, the skills needed to add value to a business are changing.

Hard skills require adaptation, while softer skills are increasingly more in demand to manage a shifting landscape of responsibilities.

Robotic processes, automation and artificial intelligence (AI) are changing both management accounting and auditing, freeing up resources for more applied work while demanding updated skills.

Systemic tasks are being revised by natural process language technologies like robotic process automation and cognitive tech, reflecting the move to self-help driven technologies in wider finance and banking.

The drive for data and real-time information for better decision-making can also be automated by AI technologies, meaning management can get granularity on how these businesses and lines are doing.

“We’re increasingly seeing digital trends that enable us to have some predictions on how finance skills are being transformed,” says Jonathan Levy, Director, Product Development, ICAEW.

Data is key

Businesses are collecting increasing amounts of data and using it intelligently through software analytics to drive better business performance. Accountants working in the management function will need an advancing set of skills to manage both the data and advancing processes.

“Automation will increasingly streamline transaction processing, with finance increasing focus on business insight and service. New service delivery models are emerging, with work completed by a combination of humans, robots and algorithms,” says Levy.

IT-based coding skills will move into relevance for data science roles, and the traditional domain accounting skills of technical knowledge, process knowledge and business performance management, like planning, budgeting, accounting and reporting, will still remain at the heart of the finance function.

Skills that are also becoming important in the digital era are softer, such as innovation, creativity, strategic thinking, curiosity, adaptability, resilience and more collaborative behaviours.

Core skills in the management area for data include storytelling through data, commercial awareness, visualisation and statistical techniques, which allow finance functions to better support the business with predictive analytics.

Fundamentally, businesses want better decisions on data, which will become increasingly important in dictating the set of skills accountants need, and there is a drive for upskilling as a result.

“The democratisation of data creates new uncertainties for finance, which will need to focus on addressing the data challenge and opportunity. Data analytics will enable finance to move up the value chain to better support the business, manage risk and identify future opportunities,” says Levy.

“There’s a need for finance to reassess the talent and skills needed in response to the impact of digital, new career models and the changing role of finance.”

ICAEW has multiple resources to help those looking to upskill, either with its e-learning certificate developed with Kaplan or its e-learning programme developed in association with Deloitte. 

Auditing challenge

Auditors need to be able to manipulate large data sets in the way that management accounting does, with the additional ability to audit the manipulation of data and follow what the financial reporting business has done.

Franki Hackett, Head of Audit and Ethics, Engine B, says that digital skills for auditors include understanding software, its output and the output of any algorithm used in the accounts or in the client business.

“If figures on the account are being put together through an algorithm, the auditor now needs the skill or access to the expert skill to assess if it has been used correctly, and to confirm if it has been appropriately reviewed,” she says.

With robotic process automation, many finance functions post invoices directly to the ledger, by scanning the invoice or taking an e-copy and passing it through software.

“Does the auditor want to check the invoice, or would they prefer to check that the software is used appropriately and the controls are appropriate and it’s been assessed by the client?” asks Hackett.

Firms that cannot perform that assessment of technology are increasingly going to find that their ability to perform an audit is very reduced, where old-fashioned methods of manual testing are used.

“It can be very expensive and firms will be looking at these systems and what comes out of them at the other end,” she adds.

Auditors, like management accountants, need to be able to understand large data sets as evidence. This includes being able to analyse, assess and read a large data population, to understand the changes in data over time, and identify changes and trends.

“There’s an expectation from shareholders and stakeholders that the audit will give them insight into how the business is run and whether it’s working through data. Combining data with softer information, such as the culture and ethics of the business; how management leads; and combining the evidence from software, is a new skill-set,” Hackett says.

It is increasingly important for auditors to be able to read data visualisations too.

“A lot of people were not formally trained. Sometimes it’s possible to miss the nuance of what’s contained inside a visualisation,” she says.

There is a set of softer skills around judgement, as data puts accountants in contact with the statistical nature of audit more closely and more intuitively. But one of the biggest gaps coming in is the gap between the junior and the reviewer.

“The biggest barrier is review. There are a large number of older auditors who have been doing this for decades; they didn’t train on data analytics and haven’t been provided with training. But they’re supposed to assess the work done by trainees and data-based skill-sets,” Hackett says.

A lot of firms are getting to grips with ISQM 1, and how they manage the approach to technology.

“Maturity of judgement will be a real change in the profession – how [to ask] the right questions and make decisions given the assumptions and confidence in decisions of juniors based on extra AI or machine learning software. It’s quite a change for skills.”