Changing world of Audit: AI, Robotics & Machine learning

With emerging advances in technology day by day, every industry is seen to adapt to the technological trend to benefit their businesses. It’s a competition on delivering better quality goods and services to the market and this is only possible through analyzing business carefully. Such technologies include Artificial intelligence(AI), Robotic process automation (RPA) and Machine learning (ML) ,which is seen to be changing the game in every industry but there are challenges when technology is to be relied on industries which work on very crucial data. Technology and auditing are two sides of the same coin and their collaboration is already shaping global strategies. The application of above technologies into the field of audit is currently at an infancy stage but with this paper the extent of application has been understood along with the future implications and benefits to the organizations as well the Auditing industry. The results were in favour of the technology and the possible benefits out stand the cost behind implementation of the same.

Before coming on application & impact of such technologies in the audit field; Let us first understand, what is the term Artificial intelligence (AI), Robotic process automation (RPA) and Machine learning (ML) is? 

Artificial intelligence (AI):

 Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by humans.

Artificial intelligence (AI) applications include advanced web search engines (e.g., Google Assistant), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as iphone’s Siri and Amazon’s Alexa), self-driving cars (e.g., Tesla) etc

Artificial Intelligence is the intelligence possessed by a software program which is installed in a machines, through which they can perform various functions same as human can perform like speak, walk, able to learn, solve problems, think, make decision etc.

Robotic Process Automation (RPA):

RPA (Robotics Process Automation) entails a bot or software application that can be programmed to perform basic human tasks that are typically manual in nature. Such task is repetitive, time consuming and, when done by individuals, prone to error. A robot precisely mimics the actions of the chair-swiveling person shifting between systems.

RPA offer benefits like the robots work non-stop with faster speed, more accurate and scalable. Also robot can take care of repetitive manual tasks, freeing up time for employees to perform more value added activities.

Machine learning (ML):

Machine learning is a key subset of artificial intelligence (AI), which originated with the idea that machines could be taught to learn in ways similar to how humans learn. Common examples of machine learning can be found in e-mail spam filters and credit monitoring software, as well as the news feed and targeted advertising functions of technology companies such as Facebook and Google

Employing an audit firm who haven’t embraced machine learning is increasingly like brining a knife to a gun fight. Not only will the audit process be slower, it will almost certainly be lower quality. 

Traditional Auditing vis-à-vis AI Enable Auditing:

 Traditional auditing techniques involved starting the audit process through a meeting conducted with the auditee and therefore involved most of information being gathered through the source of the client. This also involved a lot of document screening and inspection of documents but only through sample basis. This resulted to reasonable assurance from the auditors and had high chances of conflicting documents being hidden by the client.

With the development of technology, auditors now have the access to the database of the client which gives them access to 100% of the data relating to the finance and operations of the business. This enables the auditors to expand their horizons and reach all the data of the organization and with the application of analytical tools and artificial intelligence can enable the auditors to set the risky areas of the business. This involves auto identification of the risk prone areas, setting of outliers, conducting quick analytical review of the past data and to an extent enables the auditors to inspect the compliance with the Accounting & Auditing Standards.

Application of artificial intelligence into auditing industry:

 AI-based auditing model will reduce the dependency of the current system on human intervention and bring more transparency in the system.

We need to understand that Auditing is not limited to check the true and fair position of the internal and external affairs but to work as a predictive model to alert the system about the gap in the foreseeable future. When an AI based auditing model will be developed the same machine learning tool will be the prime server of identification of gaps and forceable danger from the current business practices.

In the past decade, we have tightened stringent norms of auditing and its standards to improve the efficiency but gaps keep erupting as the fraud perpetrators are smarter than the highly educated auditors. All the auditors can create a model of AI-based auditing model were through the Machine learning (which is a continuous process) but accumulated at one centre will help the auditing to be more efficient and less harmful form individual /firms malpractice.

With the help of block chain, verifiable audit trails can be set and with the help of artificial intelligence, auditors can easily identify gaps in the chain and highlight it through reporting to the organizations. Auditors usually in their audit procedures form audit trails in order to analyse the root cause of the issue which requires extensive verification. But with artificial intelligence, data analytical techniques and block chain technology, this can be conducted easily in few clicks which shall improve the efficiency of the auditors.

Artificial Intelligence is more of a process which includes Data Analytics, Machine learning and Data processing into its umbrella. Applications of artificial intelligence in audit process is as follows –

During the planning stage of the audit, AI acquires initial knowledge of the client and their industry. AI can collect, aggregate, and examine data from the financial statements, operational methods and organization structure.

To determine materiality and scope of audit, Robotic process automation (RPA) and Data analytics can be used for a wide range of tasks, including extracting data from prior periods or interim financial statements, based on a range of benchmarks.

Next, AI assesses the internal control, and risk factors of the audit client. Flowcharts, narratives, and questionnaires will be examined to identity anomalies and then reported. AI depends on pattern recognition and visualization method at this stage. For substantive testing and details balance stage, data quality and provenance from the entire population is checked. Lastly, a conclusion is reached based on the findings of AI.

These AI technologies facilitate auditors to automate tasks that have been conducted manually by humans for decades, and thus enabling them to fragment what was once a tradeoff between speed, cost, and quality.  Auditors can plan their focus on improving quality by evaluating advanced analytics, spending additional time providing insight and applying better professional judgment. Today, manual vouching and clerical tasks have been replaced by software, along with the development of data analytics for easier access to data. Machine learning can be used to automatically code accounting entries. Another example of AI in the audit field is review of large number of contracts in a shorter period of time. Important information from an agreement usually a lease contract is extracted using pre-selected criteria, and summarized information is conferred. All the former mentioned effects of AI generate more efficient and systematic audit procedures, and thus, a higher quality audit is achieved.

How does AI impact the audit procedures?

Auditors can use AI to –

• Automate manual tasks of auditors such as documentation
• Analyze the complete volume of structured and unstructured data that come from financial records by parsing data
• Identify anomalies such as unusual payments or activities that would not be caught by manual auditing,
• Make predictions about future risks and events by reviewing and analyzing historical transaction data

With these AI and machine learning capabilities, auditors do more advisory type of work such as understanding the entirety of ledgers and reporting on risk to executives and clients while enhancing their audit service.

Though AI may not be the right choice for some of the complex analysis of financial data, it can be suitable for counting items, spotting patterns, and flagging anomalies to a level that meets and exceeds the requirements of an organization.

The first most basic area where AI audits are already having an impact on auditing is with regard to automated entries. Robotic Process Automation (RPA) is able to simplify the process of data entry for accountants and auditors. Robotic Process Automation tasks could be used to perform testing like data analytics to add efficiency and accuracy to our work.

Along with RPA, machine learning is arguably the biggest new technology already at play in the audit. On top of RPA processes, we are also applying machine-learning techniques where, through complex algorithms, the technology can scan information, model it against thousands of assumptions drawn from external scenarios and highlight risks and insights.

The fundamentals of an audit will not change as the need for human judgment and professional skepticism will always be necessary. The real-use case for new technologies is that they will enable us to obtain more easily, quickly, accurately and extensively than ever before the corroborating evidence that is needed in an audit.

How can AI improve audit?

Machine learning has the potential to increase the speed and quality of audits. By using AI for the tedious ticking and tying tasks that are an inevitable part of the auditing process, auditors have more time for review and analysis, and are more able to focus on the more difficult, higher risk areas. The extra time and mental energy gained provides auditors the ability to step back and see the big picture. Audit firms that leverage AI along with data analytics to take a data-driven approach to audit will have a competitive advantage because they can provide valuable insights to their clients beyond the audit report.

Some tools use AI to test journal entries to find questionable entries. Others correlate financial data with unstructured nonfinancial data to confirm that business performance is consistent with its operating environment and business model. These tools aren’t a substitute for an auditor’s understanding of businesses and industries, but can augment that auditor’s human intelligence to provide valuable insights to clients that will help them achieve their goals.

Audit in Future:

The audit of the future is likely to have much less human-to-human interaction related to highly repetitive and rules-based tasks. Interface tools could be used to automatically share information in real time with the external auditor’s AI tool(s), which in turn could analyze, test and flag anomalies or issues that require the auditor’s attention. This would focus the human interaction on high-risk transactions as opposed to routine inquiries.

Under this scenario, AI tools could identify unusual transactions while also providing insights on relevant considerations the auditor might take into account, including the applicable standards (accounting, disclosure, auditing or regulatory standards), similar historical situations, or outcomes from publicly available sources. The AI tool could also analyze board meeting minutes or key communications in order to assist the auditor in identifying additional risks and requesting relevant supporting information, as well as scheduling meetings with the appro­priate individuals to discuss audit matters. This is all in addition to being able to process large amounts of data (such as reading bank statements and legal contracts) and reconcile accounts many times faster than a human auditor and with fewer errors. Auditors are constrained to work jointly with AI because ultimately Artificial intelligence is the future. Thus auditors will need to be more adaptable to changes in future.

Will AI replace Auditor?

The answer is yes but also no.

When machines make decisions and not just help to make decisions, eyebrows will be raised. The fear in finance professionals is natural. But in my opinion, there is no need to worry as yet. The use of AI in India is relatively limited right now as compared to the Western world, but it is growing. Further, once few things are taken up by the machines, the professionals will be free to take on more challenging or creative tasks. We have witnessed the fear for computers in the past. When computers started doing most of the work, many employees felt redundant except those embraced the change.

AI will not replace the need for professional judgment in auditing and financial processes. Regardless of the impact of AI on the accounting industry, firms will always need human-powered critical thinking.

Despite fears that AI will take away jobs, research supports the opposite. Instead, AI is a tool that helps auditors do their jobs better and more efficiently. However, AI and auditors can work together to enhance workflow and efficiency. AI does not replace an auditor’s decision making, judgment, or assessment skill. It does enhance their effectiveness by giving them more tools and potential findings to work with. It is to be noted that human relationship between client and auditor remains important; not everything can be replaced by technology.

Conclusion:

AI and robotics will improve the way we think, the way we explore new horizons, whether space or the ocean. As the age-old saying goes, “necessity is the mother of all innovations,” so same is the case with AI.

The current situation of the Audit with the application of AI, data analytics and tools are under the infancy period and to transform the audit field with the 100% application of the technology stated is going to take little more time. While it is true that AI, machine learning, and robotic process automation have the potential to take over many of the tasks that accountants and auditors perform, they won’t replace the professional judgment, insight, and guidance that only a human can provide, at least for the foreseeable future.

Change is the rule of nature