Emerging technologies such as artificial intelligence (AI), machine learning (ML), predictive analytics, and sophisticated mobile devices can potentially improve the quality of audits. And they couldn’t be arriving at a better time. The Big Four accounting firms and their smaller competitors have come under attack for failures to catch fraud or signs of imminent financial distress.

The Financial Reporting Council (FRC), which regulates auditors, accountants, and actuaries in the United Kingdom, issued a report in July 2019 strongly criticizing firms’ auditing quality. The FRC assessed 75% of the FTSE 350 audits for December 2017 year-ends as good or requiring limited improvements. The council’s target is 90%, and no firms examined achieved that level.

Overall there was no improvement from the previous year, FRC says, and 25% of assessed audits were below an acceptable standard. “Poor quality audit work remains unacceptably common,” the report opined.

Globally, the story is the same. The International Forum of Independent Audit Regulators (IFIAR) had at least one “finding” in 37% of the 921 listed public-interest-entity audits it inspected in 2018. (A finding generally is a significant deficiency in satisfying the requirements of auditing standards.) That’s down from 40% in 2017, but “demonstrates that significant improvement in audit quality is still required,” said the IFIAR.  

Some experts are much more positive about the state of audits. Still, they view technology as a means of achieving even better performance. “In the United States, the state of audit quality is strong, as reflected by robust levels of investor confidence and declining trends in financial restatements,” says Julie Bell Lindsay, executive director of the Center for Audit Quality.

Public accounting firms are investing in audit quality and leveraging the strengths of multi-disciplinary teams at a time when transformational technology has the potential to exponentially increase the confidence-building power of the audit, Lindsay says.

Digging Deeper

Better access to more data, cloud storage, and technologies such as AI in particular bring tremendous potential to support deeper analytics and greater insights for the benefit of financial statement audits, says Amy Pawlicki, vice president, assurance and advisory innovation, at the American Institute of Certified Public Accountants (AICPA). These advancements serve as enablers that support the audit process, Pawlicki says, driving a more rewarding experience for auditors, clients, and users.

 “When we think about transforming audit methodology to better leverage technology, a big part of it is moving toward a data-driven audit,” Pawlicki says. “This means moving in the direction of analyzing entire populations of data—versus sampling—where practical, and emphasizing the use of audit data analytics to transform risk assessment across all the phases of the audit.”

Big Four firms are banking on technology as a way to enhance audit quality. PricewaterhouseCoopers (PwC), for example, has created a number of tools designed to improve the auditing process by automating tasks and providing real-time information-sharing among client audit teams and its own personnel.

“Our clients want more value, higher quality, and a more technology-enabled experience — all at a managed cost,” says Pierre-Alain Sur, U.S. technology-enabled audit leader at PwC. 

Says Matt Bishop, audit chief technology officer at KPMG: “Recognizing that all clients are on different points of the technology spectrum, it’s crucial that we’re able to provide a toolkit of scalable technology-enabled solutions for the audit that deliver value and efficiency today but that can also be enhanced as the client evolves their own technology. This requires a deep understanding of a client’s finance operations to deliver the right technology, at the right time, and continually enhance audit quality and efficiency.”

Power Boost

One of the PwC tools is a bot, GL.ai. It uses artificial intelligence and machine learning to “X-ray” a business, examining every uploaded transaction, user, amount, and account to detect unusual transactions that might indicate potential error or fraud in the general ledger.

The tool was developed in partnership with H20.ai, an open source ML and AI platform. It has been successfully trialed on 20 audits in 12 countries including Canada, Germany, Sweden, and the United Kingdom, PwC says. The bot is the first module of PwC’s Audit.ai software, with the next modules still in development. 

The other Big Four firms have developed impressive technology tools as well.

For example, Deloitte’s award-winning Argus, part of the firm’s cloud-based audit platform, innovates document interrogation and analysis by adding the power of hundreds of “virtual eyes” to the audit team. The tool uses AI, advanced ML techniques, and natural language processing, says Deloitte. “Audit teams are able to provide greater assurance by efficiently analyzing large populations of documents rather than only a handful of samples,” according to a Deloitte spokesperson.

Similarly, EY’s Helix gives auditors the ability to analyze larger volumes of audit-relevant data and derive a more in-depth understanding of the client’s financial close and business operations. The EY Helix library of analyzers supports the audit from risk assessment to execution. For example, audit teams can use analytics to look at sales invoicing activity throughout the year, the impact of credit memos, and, ultimately, how the invoices are settled.

Other tools developed by the Big Four address real-time monitoring of engagement information, audit workflows, client portals, predictive modeling, accounting and financial reporting research, and audit confirmations. (See table below.)

With time saved on manual audit tasks made digital, audit teams can focus on digging deeper into important audit matters, PwC’s Sur says. “They’ll bring deeper analysis, smarter anomaly detection, and an enhanced ability to spot audit-related trends,” he adds.

Beyond the Scope

Will advanced technologies be the silver bullet that restores confidence in audits? Clearly, that’s TBD. Would better software and analytics have spotted a medical device firm’s unusual pricing and payment terms, quarter-end sales spikes, and funding of a distributor’s purchases? Would it have stopped a Big Four auditor from giving a squeaky-clean audit to a bank whose loans to a mortgage originator were secured by nonexistent assets? Would it have prevented mistakes like deploying engagement personnel that had no knowledge of software license accounting on a software company audit?

Clearly, technology is not going to solve some of the controversies confronting the audit profession: conflicts of interest between firms’ auditing and consulting businesses and the resulting strain in objectivity that can cloud an auditor’s judgement; a long-tenured auditor becoming too chummy with a corporate client; or the ethical lapses that have occurred at some audit firms the past two years.

While the Big Four’s tools increase by leaps and bounds the client financial information and data that auditors can dig into, what the auditor does with that information is sometimes more important. Does he or she challenge a dubious judgment or estimation by management, or let it slide?

Still, that technology should boost audit quality is a reasonable expectation. And CFOs would welcome the change. Of particular benefit are future tools that enable the auditor to determine (without an inordinate amount of help from finance) which things an audit should focus on: the high-risk areas and the business units with complex structures and revenue streams.

Undoubtedly, if deployed right, technology can also help solve a problem that plagues audits and impairs quality: the human element. 

Overworked engagement team members are one cause of faulty audits, research has shown. Auditors of the largest U.S. companies have to finalize the work for an entire audit within 60 days after the end of the fiscal year. “The timeframe can create time pressure to finish an audit, particularly for issuers with global or complex operations,” said J. Robert Brown, a member of the Public Company Accounting Oversight Board, in a September speech. Research has shown that time pressures cause auditors to skip procedures, pay less attention to matters discovered during the audit, or otherwise fail to sufficiently exercise professional skepticism.

Any software that can automate audit workflows, eliminate manual tasks, and reduce the potential for human error should be a boon to the auditing profession. The true measure of success, however, will be this: whether the tools eventually, even in a small way, help auditors close the expectation gap between what the investing public wants from an audit and what an audit can actually deliver.

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