Leveraging on big data analytics will enable the audit function to shift from sample testing to testing larger populations in real time. This gives clients more agility and time to respond to risks early and quickly. Blockchain technology also ensures that the data collected, stored and managed are immutable and helps to prevent fraud while maintaining client privacy.

Cloud technologies enables information to be updated, shared and accessed instantly across multiple teams. This reduces confusion and eliminates errors, which are important in an increasingly fast paced environment. These potential gains however, need to be carefully traversed as capitalising on such technologies pose cybersecurity risks. By using Robotic Process Automation (RPA) and data extraction tools, manual processes such as preparing paper confirmations and notifications can be reduced.

Shareholders, employees and suppliers are demanding for easy-to-read insights that cover more than just annual financial reports. Shareholders are demanding for a clearer signalling of risk, which may include providing risk assessments beyond the standard 3-years and non-international financial reporting standards such as cybersecurity risks, employee engagement levels and environmental impact.

Current adoption rates of technology tools among external auditors are relatively low as compared to counterparts in finance teams. An area of great discrepency was in the use of cloud technologies, where auditors cited data privacy and cybersecurity risks as their main concern. Communication tools also need further development to prevent lag times and miscommunications, especially with remote working.

The ever-evolving complexity and diversity of IT systems requires auditors to improve their digital literacy. The role of an audit associate requires continuous education on analytics and automation tools to enable focus on providing professional judgement and to develop deeper insights in existing and new areas of reporting. This is especially important for audit associates as technologies would raise the bar in defining “reasonable assurance”.

Given the nature of audit, technologies such as data analytics would likely play an exploratory function rather than a confirmatory one, as these tools are not programmed to identify emerging trends that it has not been trained in and scripted for. Professional judgement would be required to identify irregularities outside of the usual operations.

Auditors need to use professional judgement to synthesise information from AI inputs and other sources of information. Audit associates dealing directly with these technologies will need to acquire data science knowledge, data management and machine learning techniques. Consider upskilling your workforce using the training roadmap found here.

Technology raises the standards for “reasonable assurance” because of the ability to analyse large amounts of data. Practices that still rely on sample testing may be questioned and will have to be managed according to clients’ expectations. Clients may also expect faster turnarounds as many parts of audit can be automated or run in parallel.

Digitalisation of the client’s finance team would provide more opportunities for assurance reporting such as reporting biases in AI tools, controls and processes. It is important for these tools to be used in compliance with regulatory or ethical requirements.