System, Data, and AI: The Future of Audit!

Introduction

Today\'s era, the 21st century, has evolved with major changes in the way we deal with any issue. Technological advancements are transforming our world, and we now have Artificial Intelligence backed with Data and System. Data was there earlier as well, and audit revolves around analyzing them through the application of Standards on Auditing, thereby identifying audit evidence to express the auditor\'s opinion in an Independent Auditor\'s Report. But in the present scenario, the volume and frequency of data production have increased multifold compared to earlier times, marking a paradigm shift in the way business is conducted.

System and DATA

As defined in Cambridge Dictionary, a System concerning technology means \"a set of computer equipment and programs used together for a particular purpose\". Data is the information produced by the system that can be used to make various decisions. The rate at which data is generated has accelerated, producing a large volume of data called \'big data\'. They may be in heterogeneous formats, unstructured or structured, whose analysis through traditional tools is cumbersome. Big data is impacting every aspect of accounting, auditing, taxation, and advisory services. Therefore, the world is looking towards Artificial Intelligence (AI), which has more or less similar thinking capacity as that of human beings and is able to comprehend big data more effectively and efficiently.

DATA and Audit

Audit is defined as an independent examination of records so that audit evidence can be obtained to express an opinion on such records as to whether they are free from material misstatements caused due to fraud or error. The detailed procedure as to how audits are conducted along with guidelines for complex scenarios has been covered under Standards on Auditing (SAs). However, the reliance or completeness of audit depends upon the data or information that is provided by management and it indirectly relates to how management is handling such data and their internal control to generate/process them. If such data/information is not made available to the auditor, he will not be able to collect sufficient and appropriate audit evidence, which may cause him to express a Disclaimer Opinion in the Audit Report.

Understanding the Business Environment

In today\'s world, the dependency of majority of organizations on information systems has extended to 95%-99%. Right from customer acquisition, receiving their orders, to order processing and receiving payment, everything is done through digital methods. The system is everything in today\'s business.

Audit in Next-Generation

Auditing involves an examination of the data produced in financial statements on which reliance is drawn through the understanding of how data are being generated, stored, maintained, and accessed in a system. To perform an audit traditionally would require huge time and resources because transactions amount to a large volume by the end of the year.

Risk Assessment

Innovation in business fueled with AI is a new era evolving exponentially. To audit such a business environment, audit planning winged with technology would enable an Auditor for successful risk assessment. Risk assessment using predictive analysis, pattern recognition, real-time risk monitoring, scenario analysis, comparison, and benchmarking would enhance the efficiency as well as the quality of the audit.

Testing of Controls

Test of controls is a very crucial step in an audit process. Within an automated environment where human intervention is minimal, testing controls demand the usage of similar tools. The paradigm shift from auditing historical data to auditing algorithms and data used to train a developed model is the current demand of the Auditing profession. AI enables continuous testing of controls giving real-time protection and thereby allowing monitoring of controls and taking immediate actions for any failure or potential risks.

Use of innovative tools

Expanding data sample size by the usage of AI automated technology would be an easier task that would draw up the trend analysis and peer benchmarking. Natural Language Processing (NLP) is the technology developed to extract content from unstructured data like finance, contracts, loan documents, and agreements. The use of AI algorithms improves the trust in the audit result which checks out control in a business by generating test cases that differ from business to business. Other tools that may be inculcated in the audit process include ChatGPT, ICAI developed CA GPT, Machine learning, predictive analysis, etc.

Paradigm Shift in Audit

If the abovementioned tools are used for the purpose of audit, AI may be the cause of making a paradigm shift in Audit. Starting from gathering of test data and information, AI steps in for automatic gathering of information through ERP, other ancillary accounting systems, and also from unstructured contents through NLP technique. Converting year-end full audits to continuous audits using AI through data collection, verification, and analysis on a real-time basis would enable the auditor to detect issues promptly.

Need of New-Generation Auditors

It is a need of time to extend the audit procedure to the next-generation by introducing mandatory usage of AI tools which analyze data quickly and accurately. Scrutinizing the system policy and understanding internal control concerning the usage of the system through AI tools is necessary. Cross-checking of each transaction from a third party through the usage of blockchain technology would make audit more fruitful. Using drones loaded with AI for the physical verification of assets would enable stock counting quickly and accurately.

Conclusion and Recommendations

The future of audit lies with the usage of AI in Audits by new-generation Auditors. New-generation Auditors need to focus on new techniques like Predictive analysis, Natural Language Processing, Machine Learning, etc. Such AI tools would reflect the performance of a business very quickly as compared to traditional methods. They would provide a brief comparison of the performance of an entity along with horizontal analysis, vertical analysis, comparison with industry benchmarks, trend analysis, and how the industry is performing in the same sector. This would enable Auditors to focus more on high-risk areas and gain an understanding of the entity more quickly and accurately. Access control, security, confidentiality, integrity, and availability of data are very important to conclude a quality audit. Audit risk may be lowered by performing 100% checking using AI to check the financial statements on a continuous basis.