Artificial Intelligence: How technology transforming the audit
Technology is changing the way business is conducted and data is analyzed. Since the environment is constantly changing, the principles and methods of audit needs to be changed, so as to produce efficient results which can be relied upon by all. An organization looks for three skills in an auditor which are in area of technology, communication and critical thinking.
How Artificial Intelligence leads to Improved Results
Previously, the feasible method of auditing was to analyze large quantities of data by taking smaller random samples. This approach is being followed year after year. Clients and auditors have accepted the fact that anomalies outside the sample set are potentially missed. This is called sampling risk, the risk of reaching a different conclusion based on examining a small set of data as compared to entire data set. Due to the limitations of auditing, the auditor cannot provide absolute and guaranteed assurance on the audit findings. These limitation can be rectified through the use of audit data analytics.
The nature of Artificial Intelligence is to learn about and identify patterns in data. It helps in analyzing secondary data and cross correlate hundreds of variables to establish the correct transaction. It is used to analyze large no. of transactions and put them in buckets: high risk, medium risk, low risk. It helps to learn more about client’s transaction through analysis of full population of data and to identify the exceptions, making it possible for auditor to work effectively, efficiently and smartly. Thus, improving the quality of audit.
Audit data analytics involves the analysis of complete sets of data to identify anomalies and trends for further investigation, as well as to provide audit evidence. This process usually involves an analysis of entire populations of data, rather than only examining a small sample of the data.
Key areas where Technology will bring major impact in Auditing:
- Enhancement of Audit Quality by using artificial intelligence
Artificial intelligence involves algorithms that enables software to absorb information and think like humans and mimic their actions. It can perform analysis on large set of data which is impossible by auditors today. It provides solutions and new strategies to correct the work for the problems that it come across.
2. The Power of Predictive Analytics
Predictive analysis uses advance techniques to make predictions about the future based on the probabilities. It may involve use of artificial intelligence and machine learning to rectify those predictions. In the context of the high-quality audit, auditors can employ digital tools to extract information from an organization’s systems, and then use predictive analytics for the purpose of identifying patterns that either align or don’t align with anticipated outcomes and trends. This type of analysis is conducted for various reasons, but it is especially useful in gaining deeper insight into a client’s business and financial risks.
This technological transition won’t happen overnight rather it will take years to go from traditional approach to data analytics. It is the organizations who should incorporate these new techniques in an effective manner as well as according to their need in order to gain the competitive advantage over other competing firms.
Use of Data Analytics by Audit Firms
The audit firms whether large or small use data analytics in order to reduce risk and to provide quality services to the client. There are no universal audit data packages available but bigger firms use their own resources in order to create their own data analytics platforms while smaller firms on the other hand are dependent on the readymade packages.
These data analytics packages help the auditors to audit large amounts of data effectively through the use of IT systems thereby increasing the audit quality as well as add value to the client. Auditors can extract and manipulate client data and analyze it. By doing so they can improve understanding of client’s information and identify the risks in an effective manner. These data analytics techniques help in understanding large amounts of data in simplified and pre structured forms and help in developing audit programs according to client specific risks, helping auditors to arrive at the results more efficiently and accurately.
Benefits of Audit Data Analytics
Some of the key benefits auditors can expect to see after adopting data analytics are as follows:
- Enhanced audit quality – Data analytic techniques and methods enable audit teams to have:
- More relevant audit
- Identifying issues earlier
- Larger populations tested
- More relevant evidence gathered
- Higher quality audit evidence
- Improved client service – Audit data analytics help auditors to gain a better understanding of their clients’ business and to provide further insight into risk and control assessments resulting in:
- Greater insight
- Raising issues earlier
- Improved communication
- Possibility to visualize results
- Increased effectiveness – Data Analytics can be used to:
- Assess large volumes of data quickly
- Make better informed risk assessments
- Increased auditors’ focus
- More frequent testing
- More timely reporting
How Audit Data Analytics benefits the businesses organization
Audit data analytics benefit the businesses by delivering higher quality, enhanced transparency and efficiently executed audit. It also leads to better communication between the auditors and management. The auditor gets more clear understanding about the client’s internal controls, control gaps and deficiency, causes of the exceptions etc. Thus, management might get to know about various frauds, misappropriation made by the employees / staff which the management is unaware of, for which appropriate actions can be taken at very early stages.
The future of audit is going to be different than what it is today. Better business understanding, enhanced quality services and improved business value are some examples of what the future will look like. Artificial Intelligence will however not displace the role of an auditor rather it will be a helping hand to automate large data analysis task. Auditors will no longer need to select a random sample from a data set rather the entire data set can be looked into thereby decreasing the sampling risk and providing absolute assurance instead of reasonable assurance. The use of Artificial Intelligence gives a competitive advantage over firms that use the traditional techniques.
It is not enough to have latest technology – auditors must be able to mine data for information that is important to clients, such as that affecting relevant risks, internal controls and important processes, and be able to communicate it clearly and candidly.
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