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Data in audit: How firms are becoming more ambitious with their use of data

Author: ICAEW Insights

Published: 28 Sep 2021

Better data processing and management opens up new opportunities for auditors and could even help rebuild trust. But there needs to be a clear framework for how it is used.

Alongside the rise of digital, the use of data analytics within audit has accelerated over the past few years. But, over the past year in particular, the Covid-19 pandemic has heightened this trend, which is fast becoming essential to the auditing process. 

Stuart Cobbe, global head of analytics and industry insights at risk discovery platform MindBridge, says the company is experiencing a period of ‘exponential growth’.

“The uptake is accelerating,” says Cobbe. “We’re touching more workflows and auditors than we ever have before. The willingness of accounting firms to invest in technology seems to have taken a big uptick during the pandemic, particularly as firms left the first lockdown.” 

He believes this came after firms transitioned to remote collaboration platforms to ensure a largely digital, remote audit. 

“Once all that change happened and firms realised that actually, there’s a lot of value from these more technology-driven approaches, they immediately started asking questions about the other parts of their audit process,” says Cobbe. 

As well as using technology in more areas, firms are also beginning to go deeper in their use of data analytics. “We’re seeing much more ambitious use of our technology in the actual audit process,” he says. 

In the past 12 months, firms have started to seriously ask how they can really change the work they’re doing based on data-driven, machine learning-based, risk assessment procedures, Cobb explains. ”That’s really exciting for us, because it puts us at the core of the audit process, and it makes our tools integral to the decisions auditors are making.”

Accountancy firm Moore Kingston Smith is using MindBridge for their auditing process and risk analysis. Becky Shields, who is head of digital transformation at the firm, believes the primary advantage of using data in audit is the confidence it brings to the process. 

Not only does it instil confidence in the client who can see the evidence being presented more clearly, but it enables auditors to get to the root of risks quicker, ensures better accuracy, and greater engagement with the raw data. 

“Data gives you that ability to get to the root of the risks a lot quicker than purely based on your gut feeling and experience,” says Shields. “It just gives you a bit more confidence in your understanding of what's going on and it's a powerful facilitator of conversations with clients.”

This is really important, she explains, given the future of accountancy and how more day-to-day tasks are being automated. It’s quite hard for teams to build the experience, to get to a stage where they can look at something intuitively and know what’s going on. “What data analytics does is give them a set of outputs, tools and visualisations that help them and support them as they develop that intuition.”

Shields believes the increase in confidence when using data also applies to trusting the profession as a whole. “Confidence in our profession has taken a bit of a dent,” she says. “At the moment, we have some work to do on improving some people’s opinions of the audit, and the value of an audit.

‘People probably wouldn’t realise that some of what we do is still on a good old fashioned random sample basis. They would probably assume there are areas we’ve got a bit cleverer at. So, as the technology progresses and it’s more widely talked about, then the expectation gap should decrease and confidence – not only in the output but in the profession as a whole – should return.”

Moore Kingston Smith has plans to go deeper into data analytics, just as Cobbe hinted. Plans for the future include analysing other sources of information to verify transactions. 

“They're working on taking those external data sources to verify the finance function at the moment and definitely, we will jump on these updates as they progress because they're all really important developments,” says Shields. “Rather than doing a forecast for business, based on some old modelling, we want to start using more prescriptive and predictive analytics and machine learning.”

However, one element that’s missing in the field of utilising data in audit is framework and regulation, according to Shields. There needs to be more framework put in place in terms of issues, how we communicate its use to their clients, and benchmarking. She recommends there being an agreement on who has ownership of the data, who is responsible and ultimately that the data is used for good. 

“At the moment, we easily have the capability to put a large section of our client data within one database and I can very quickly analyse which of my clients has a relationship with other supplier clients.”

That information is great for benchmarking, she explains, but could also be used for harm, for example, tipping off a client that another client that they have a relationship with is struggling. Once the regulation and framework catches up, Shields believes it will open up some ‘valuable’ capabilities and allow for real time ‘amazing’ audit analysis. 

“There are lots of possibilities of some really valuable stuff we can do,” she says. “But everybody needs to be mindful of the ethics and transparency around it. We’re just waiting for the profession to catch up.”

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