The FRC’s 2026 Annual Review of Audit Quality (ARAQ) shows there is value in data analytics platforms for carrying out risk assessment, testing, including but not limited to revenue or journals testing, and even in supporting practical aspects of engagement management, such as planning, allocating staff and other resources, and audit file management. Data analytics can help auditors visualise and analyse large datasets – tasks where there may be synergy with AI tools – delivering verifiable, actionable intelligence in real-time.

Registered uptick in overall audit quality

The FRC is ramping up its activities around the use of technology in audit and continues to monitor and encourage adoption, particularly beyond the largest firms that by their nature tend to be early adopters. Initiatives such as its Innovation and Improvement hub, and its guides to generative and agentic AI support this.

In this year’s ARAQ, , the FRC also identifies firms’ deployment of technology in particular as being central to its assessment of Systems of Quality Management (SoQM) which was elevated to “the heart of supervision activity” from April. 

ICAEW’s recent research into the use of analytics in external audits revealed that “audit regulators and auditing standard setters are looking to encourage greater innovation and adoption of data analytics,” having already seen steady improvements in auditing quality across the board.

Investment in data analytics specialists

In a bid to increase audit quality across the board, firms are bringing in tech and data analytics specialism to support sustained improvements in audit quality. The highest quality audits involved early and sustained use of specialists – where the engagement calls for them – and independent reviewers along with strong leadership, project management and effective management challenge.

Expanding advanced analytics capabilities to support data-led, risk-focused auditing

The use of analytics allows auditors to go beyond testing relatively small samples of the data. Some tools now have the capacity to test 100% of populations in their client’s financial records and may allow them to be assessed more frequently during the accounting period, rather than at one point in time during the audit.

Upholding ISA 540: challenging management’s impairments model

With data analytics skills and platforms, auditors can back-test previous accounts for patterns of bias in any impairment calculations. This has improved auditors’ ability to scrutinise bias and levels of subjectivity when looking at management’s impairment reviews, goodwill calculations, or bad debt provisions.

Enhanced admin planning and project management

Firms can also use analytics on their own engagement management processes and admin tasks to ensure timely submissions and deliveries. The ability of data analytics to securely process enormous volumes of documents, ordering them, tracking changes over time, is powerful and familiar to most users.

But in addition to filing audit reports as part of the firm's deliverables, data analytics platforms can also audit their own workflow against optimal metrics, and with the requisite text and graphical presentation map out where bottlenecks or disruptions occur. 

Analytics adoption challenges

Data analytics remains a crucial skill set for auditors. Regulators and standard setters recognise the ability of auditors to make sound judgements about the use of analytics, but barriers to adoption remain. These include data quality and consistency, how analytics fit into firms’ audit methodology, regulator’s questions around how analytics is applied and skills gaps. While auditors are not expected to become data science experts, they need to know how, why and when analytics should be used, how to configure tools and how to interpret outputs.

ICAEW’s Analytics in external audit: A survey of current practice and trends, points out how much auditing firms “stand to gain by investing in upskilling their workforce, in tools, and by making bolder decisions about when to use analytics.