Artificial Intelligence Impact on Auditing Essay Example

📌Category: Artificial Intelligence, Business, Science
📌Words: 1013
📌Pages: 4
📌Published: 07 June 2022

Auditors are under increasing pressure to increase the value they contribute to their firms and reducing the number of errors that can occur while doing an audit. One of the solutions for these problems involves the increasing use of AI. Internal auditors can use artificial intelligence, which uses algorithms to discover and interpret patterns and anomalies in data sets, to more quickly identify areas of risk and do a variety of other jobs. Artificial intelligence systems can consider both internal and external data, allowing businesses to spot growing hazards and threats they hadn't considered before. 

In the 1980s, artificial intelligence began to gain traction in the financial industry. This was the point at which expert systems became a viable commercial product in the field of finance. Until the 1980s, the financial industry relied on the Expert System which was a knowledge-based intelligence system to forecast market trends and create tailored financial strategies. To limit the danger of human error, the banking and financial industries began to deploy expert systems more frequently. Once these expert systems started to become part of the normal business operations of many jobs that involve financial analysis, market analysis, business development, international business, currency exchange, and bank management.  

AI has been around for many years, but many do not know about the exact origins of how the idea had come about to become a part of our society. The origins of AI may be traced back to the period of classical thinkers who attempted to equate human thought to a symbolic system. AI, on the other hand, did not obtain official acknowledgment until the 1950s. The term "artificial intelligence" was developed in 1956 at the Dartmouth Summer Research Project on Artificial Intelligence. Though there were some disagreements with standard approaches, the meeting had a positive response overall. 

One of the types of AIs that auditors use involves machine learning. Machine learning is a branch of artificial intelligence that automates the development of analytical models. These models are used in machine learning to undertake data analysis in order to recognize trends and generate predictions. The machines are programmed to learn from the studied data and when the machine is exposed to more data, patterns emerge, and the feedback is used to adjust actions. Machine learning is designed to find the best combination of mathematical equations that best predict an outcome. It is designed to find the best combination of mathematical equations that best predict an outcome. Machine learning is well adapted to a wide range of classification whether it be linear regression or a cluster of analysis tasks.  

Machine learning in audits is already being tested and explored by audit firms. Deloitte, for example, employs Argus, a machine learning platform that can interpret leases, derivatives contracts, and sales contracts. Argus is equipped with algorithms that enable it to recognize essential contract phrases, trends, and outliers. Auditors can then concentrate on interpreting the documents' important elements. This can be interpreted as a machine that reads a lease contract, identifies the essential phrases, and determines whether the lease is capital or operating. Machine learning algorithms might potentially detect trends and outliers, such as nonstandard leases with large judgments. This would allow auditors to concentrate their efforts on contracts with the highest inherent risk, which can boost the audit's speed and quality.  

The introduction of data analytics has been the most significant development in auditing techniques. The user can evaluate small transactions, download proof, and optimize a variety of other audit operations using automated software solutions. The chiefs of KPMG and other such executives have welcomed the change in audit technology since it will reduce human labor and make the audit process more efficient. The software systems are more than capable of detecting minor transactions and confirming them against financial records, as well as doing more analytical tasks such as comparing financial data across time and forecasting current year statistics to determine their reasonableness. 

One of the controversies that come with integrating more AI into certain jobs is the ethical issues that may occur. This is a problem because the definition of ethical has not been officially decided upon. The fact that there is little agreement on what "ethical" should imply in the context of AI is reflected in the diversity of techniques offered by a new business. The emergence of formal and standard AI ethics guidelines would be extremely beneficial to the AI auditing business. However, the development of these principles is hindered by the fact that engineers and social scientists have quite different perspectives on the subject. This discrepancy has been thoroughly investigated by academics at the Oxford Internet Institute and the Alan Turing Institute. They discovered that technical work on AI ethics rarely corresponds to legal or philosophical ethical concepts. Because of this, there may need to be more research done to make definitive ethical principles for Ai in auditing.  

Another controversy of AI is the risk of automation when it comes to the jobs of auditors. Companies that cater to multinationals with millions or billions of dollars in assets cannot afford to focus on cheap costs. Therefore, artificial intelligence and machine learning must be integrated into accounting and auditing. After a bot has been fed enough information to build a solid knowledge foundation, it can gradually increase its abilities to improve performance. There has been some speculation about AI taking over the jobs of auditors. For a variety of reasons, auditors do not need to be very concerned at this time. First, the world's legislature is not probably ready for AI to completely take over jobs such as auditors. Second, given that increased reliance on technological solutions hasn't slowed the number of auditors hired in recent years which can mean that even with cutting-edge AI solutions, human auditors will still be required for the professional judgment and risk assessment skills they can bring to the table, as well as overseeing the technology itself.  

AI is always going to keep being evolved and applied to many aspects of our lives. The use of AI has not only helped to increase the efficiency and accuracy of certain jobs such as auditing. Even with a fear of automation decreasing the amount of jobs that are available for future auditors, it does not mean that AI will take over jobs altogether. It is the job of these auditors to be able to keep up with evolving business practices that involve the increasing use of AI. It has not only helped business with running more efficiently, but also has helped the business keep up with an evolving industry.

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