Auditing in the times of big data

Auditing in the times of big data

In technology, Moore's law observes that computing power doubles exponentially over time as transistors get smaller and more densely packed on integrated circuits. Conceptually, this concept holds equally good for the audit profession, given the dynamic changes in recent years.

Despite weathering relentless transformation in the face of rising complexity of globalization, increased digitization and rise of digital businesses regulations, recessions and corporate failures, the speed, shape and form of the profession has transformed exponentially, particularly in the decade. From transaction verification to relying on systems, assessing internal controls, and embracing risk-based auditing, it has today stepped into digital assurance, and environmental and sustainability reporting.

Amidst a heavily digitized landscape, audit professionals grapple with complex business models, IT systems, non-availability of quality talent and dynamic laws and regulations. Striving to fulfil their duties of maintaining public trust, enhance transparency and deliver high-quality audits, auditors of the 21^st century are navigating an era, where big data reigns supreme, making it the backbone of audit.

Navigating through data

Gone are the days of sample testing and ledger scrutiny. Today’s auditor deals with an unprecedented level of financial and non-financial data, applying available and bespoke data driven techniques, requiring understanding and working with vast amounts of unstructured data and complex IT systems. Combined with increasing stakeholder expectations around professional scepticism and improved audit documentation, delivering an audit today requires significant technical knowledge, skill and effort.

To provide meaningful results and insights, auditors today need to mine large volumes of data from their source, validate it for accuracy and completeness, and analyse and interpret it properly. A company’s internal data also needs to be correlated with external information – think stock exchange filings, press and analyst reports, etc.

To discharge their responsibilities in this complex environment, audit firms are beginning to invest heavily in technology and tools that can both talk to organizations’ IT systems directly, and comprehensively integrate it with external information sources.

Establishing guardrails to maintain audit quality while continuing to be compliant with the increased regulatory requirements around data privacy laws, handling price-sensitive information, and professional ethics, also becomes imperative.

Today’s auditor is therefore operating as a data miner and data scientist, while continuing to balance the requirements of regulation, audit quality, transparency, and commercial viability.

Sharper focus on risk

Dynamic changes in the business environment globally, requires auditors to constantly reassess and address the impact on their role. Higher complexity begets the need for greater consistency, accuracy and audit quality without diluting efficiency. Auditors need to rapidly embrace digital approaches, data analytics, Robotic Process Automation (RPA) and even AI/ML, to identify audit risks through trends, patterns and exceptions, providing more meaningful risk assessments, and strategize audit execution accordingly.

AI, including Generative AI, has the potential to significantly contribute to consolidating the collective knowledge of auditors worldwide, and enhance audit quality in general. Using AI solutions, auditors can analyse voluminous and complex datasets such as from e-commerce and digital payments. In finance, AI is already being used in accounts payable and invoicing, to extract data and perform quality checks. In corporate reporting, AI can source information from the company’s public statements and facilitate fraud analytics and analysis of balance sheets and performance.

Such use of technology will significantly enable the auditor to target a wider data set and focus on higher risk and judgmental areas. Thanks to data analytics, they can gain better insights from the data, resolve challenges, and provide assurance that makes the audit more valuable and builds trust and credibility to financial reporting.

Adapting to the new paradigm

This shift in audit approach from the traditional to being technology- and data-driven, has differing implications for stakeholders.

For auditors, it demands a significant mindset shift not only from an operations, technology and infrastructure standpoint, but also in hiring and upskilling a large number of audit professionals. To meet this, auditors are increasingly working with or hiring STEM professionals to complement their audit teams. Till such time the professional education curriculum comes up to speed, the onus will be on audit firms to train people at scale, invest in tech infra deployment, comply with data privacy, etc.  

Organisations, on the other hand, need to work effectively with their auditors. CFOs will need to provide the auditors with more and fit-for-purpose financial and operational data in a digital format.  They need to adapt to newer ways of working as they likely will have to answer new and better questions related to the data underlying the financial reporting. Organisations’ IT teams also need to provide the auditor with relevant information and systems access.

For regulators, the need to upskill and staying relevant amidst technology disruption will become paramount. More engagement with organisations and auditors themselves will be needed to better focus their efforts on auditors’ use of big data in audits.

Emerging technologies have created a data-rich environment, rapidly transforming the financial reporting scene. In such an environment, trust and reliability in financial reporting requires every stakeholder – professional membership bodies, audit firms, corporates and regulators – to play their part to continue to stay relevant.