Technology has brought about significant changes in the lives of human beings. Human intelligence has been influenced by emerging technologies like Artificial Intelligence, Big Data Analytics, Application Programming Interfaces (APIs), Blockchain, Cloud Computing and Connected devices as in the Internet of Things (IoT). We can now operate like one global village enabled by the one big engine; technology. The paradigm shift has also affected major auditing firms and businesses at large. This challenge has shaken businesses in developing countries where manual processes are still prevalent. Digitalisation is an enabler for innovation and investment to improved services, and auditing firms have not been spared. What will then drive the audit process in today’s world? Value, efficiency, accuracy, completeness, and predictability. This article is purposed to look at digitalisation and its value to the audit industry, audit trends, data analytics and limitation to digital appreciation.
Digitalisation – what is it?
To discuss the expedition to digitalisation and what it implies to the human mind, I will take a look at the trends in Zambia, particularly in the financial sector. Previously, all processes involving money transactions required someone to make a physical appearance into a bank in order to be attended to.
With digital transformation, quick service delivery from service providers is no longer a privilege but an expectation. It is now possible to transact from the comfort of one’s home or anywhere, provided one owns a Mobile phone with a SIM card.
The adoption of digitalization taking place in banks and other sectors is encouraging audit firms to enhance their auditing tools and methodologies. Customers no longer need to walk into a bank to open an account or apply for a loan as these processes are now enabled via mobile and internet banking. Banks, such as Standard Chartered Bank, Stanbic Bank, and Barclays Bank have introduced online platforms to enable customers to conduct online transactions.
In summary, digitalisation is the process of automating manual processes into online platforms. Evans (2018), defined digitalisation as “a natural progression from traditional business transformation, to one more suited to the modern world.”
The definition above has further linked digitalisation as a distinct feature that has become part of the mix in opportunities for innovation, scalability, and agility that are enabling the possibility of any transformation process.
You will agree with me that, one of the benefits and reasons why most businesses have disrupted is that, digital transformation is not a one-off program. Once adopted, it opens up an organisation to a continuous and more effective evolution.
What will become of the auditor in the digital era?
It appears, there’s a contention as to who will remain relevant in this field, between the physical auditor (human factor) and the digital auditor now commonly known as ‘artificial intelligence’ (AI). Artificial Intelligence is the practice of engaging advanced algorithmic techniques that train computers on how to be intelligent and perform cognitive functions in a bid to accelerate, automate, and augment decisions that drive growth and profitability.
From my perspective as an IT auditor, there will be no clear separation between the two. The main factor to appreciate is that there will be less dependence on the human factor. Most processes will be automated, thereby eliminating the need for junior auditors. However, processes will still be needing factual verification before financial statements or reports can be accepted.
Value of digitalisation in the Audit Industry
The value that digitalisation brings to the audit profession is enormous. The advancement has enabled auditing firms to enhance the audit approach and capabilities in order to remain viable in the industry. The power of technology disruptions has brought businesses closer to the user. There is reduced travel cost to access facilities due to the interconnectedness of the global world enabled by the vast IoT. Easy and quick access to data via Cloud has enabled auditing to become more efficient and effective.
Audit Industry Trends
Auditing is a result of an approach which is determined by a number of factors such as:
– Type of industry;
– The agreed-upon procedures;
– Sufficiency of available internal controls;
– The complexity of the IT environment; and
– Client commitment.
The above factors determine how much time will be spent on an audit engagement. It also aids in rating the client from a risk perspective.
Therefore, risk identification can be enhanced when automated audit tools like Data Analytics techniques are used.
Data Analytics Overview
Caseware International, (2019) defined Data Analytics as a process of examining and modeling data to draw out useful information, discern relationships, make connections and draw conclusions. The benefit of which includes the ability to Measure, Predict, Monitor, Optimise, Prevent, Prescribe and Compare.
Limitation to digital data analytics
Through experience gained from auditing IT platforms in Zambia, the following factors limit the value of big data analytics:
Data retention policies –some major organisations have been found to operate without proper data retention policies. Without historical data, past trends analysis to improve business operations and efficiency is not possible.
Central repository – lack of storage media, with the emerging cloud platforms, organisation still face challenges to retain data over the years. Such challenges are a result of not having digitalised document management systems.
System integration gaps – most organisation are maintaining standalone systems with no defined interfaces. This leaves such organisation susceptible to error as the manual interfaces remain the order of the day.
Unskilled technical resources – most organisation have not invested in their local resources with the knowledge to supporting core business systems. As such these fail to meet the changing audit approach and demands such as big data analytics.
Over dependency on vender skills – in most instances, venders have held on to the source code with no succession plan for continuity. Businesses need to retain technical knowledge of the data structures of their systems.
Unstructured vendor service level agreement – system and application vendors are getting it easy in manipulating local businesses in Zambia. There is a need for comprehensive reviews on service level agreement to avoid signing documents that become expenses to the business.
Conclusion
The paradigm shift in the audit approach is driving efficiency in audits of financial systems. Digital transformation is not aimed at demeaning the ancient audit process but a mere shift in the mindset of an ordinary auditor through process transformation. Businesses are, therefore, expected to continue transforming their processes using new edge technology to circumvent disruption. The ‘disrupt or get disrupted’ saying is a reality and has seen businesses shut down because they did not embrace digital transformation.
The author is Senior Manager, Technology Advisory at KPMG Zambia. The views expressed in this article are my own and not necessarily those of KPMG
Resource sourcing:
Budnik, el al (2018). Digital Transformation; How advanced technologies are impacting financial reporting and auditing. Page. 3- 7.
Caseware International, (2019). Caseware Idea Inc. ‘Introduces Smart analyser’. [Online]: https://promo.caseware.com/about-us/news-reviews/caseware-idea-inc.-introduces-smart-analyzer Evans. P (2018). Becoming Truly Digital; Rethinking business models for a digital world; ‘The Strategic Imperative – Beyond Technology’. Page. 4 -6
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GDPR, (2020). Complete guide to GDPR compliance ‘ [Online:] https://gdpr.eu/
KPMG, (2018). About KAM International for Financial Statement Audits: Analytical Procedures and Methods. Page. 13-20.
KPMG, (2018). About KAM International for Financial Statement Audits: Audit strategy and Audit Plan. Page. 76 – 96. Katinamichael, (2019). Social Implications of Big Data. [Online:] http://www.katinamichael.com/big-data-implications
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