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Growing business needs to process thousands of transactions on a daily basis. Evaluating and reconciling these transactions may take many hours of the auditor's time. Traditionally, any auditor would adopt a sampling method to ensure the authenticity of these transactions. Even in the traditional approach, categorizing and analysing these transactions would take minimum of 30 minutes of time. In the case of regular monthly audit, the time taken to perform the basic authentication & review of transactions would take around 15 days for a large organization after the month ends. In case of limited review for the listed entities the analytical procedures would take around 1 week to 15 days. Which means that the authentic financial data will be available 15 days after the month ends. At that point of time, it may be too late to rectify the transactions in the month in which it has incurred and may result in the cash flow problems.

In contrast, when you use artificial intelligence / machine learning to automate the auditing tasks, it will generate reports and anomalies in the data almost instantly. Artificial intelligent powered audit tool will authenticate the data every day, providing you the real time reports, identify and address any concerning trends before they become serious issues. It is high time that auditors become smart and use smart technologies to identify the anomalies in huge data of the client. A combination of high-tech solutions and seasoned financial experts can accurately and efficiently handle the regular audit work carried by any auditor. By embracing artificial intelligence as a tool, auditor can shift where we're spending our time from performing menial data preparation and analyses to the drawing of insights from those analyses.

It's time for the auditing fraternity to get out of their comfort zone of using Excel & MS office and adopt and experiment with newer technologies and scale up their business.

Adopting Artificial Intelligence By Auditors - Need Of The Hour

Meaning & Definition

Broadly speaking, definition of artificial intelligence involves machines or computers that can simulate human intelligence. In practice, Artificial Intelligence is a software that - using super-fast, repetitive processing and intelligent algorithms - can learn from large amounts of data, so that it can adapt and carry out decision-based tasks usually associated with human beings.

Artificial Intelligence involves using computers that can simulate human intelligence. AI software uses fast, repetitive processing and algorithms to "learn" from large amounts of data and complete decision-based tasks.

Following are the challenges which the artificial intelligence embedded software can address:

1. Identification of data anomalies

Artificial intelligence is capable of discovering hidden patterns, trends and insights helping the auditors with effective decision making. The data-based decisions can be delivered on real-time basis.

 

2. Prediction of future outcomes and trends

Artificial intelligence has the power to predict future scenario by analysing past behaviour. The behaviour helps to identify fraud, detect anti-money laundering in banks. With its power of Machine Learning and Cognition, AI identifies these hidden actions and helps the auditor to unearth the data entry mistakes. Similarly, AI is able to detect suspicious data patterns among humungous volumes of data to carry out fraud management.

3. Effective decision-making process

Cognitive systems that think and respond like experts, provide optimal solutions based on available data in real-time to the auditors. These systems keep a repository of expert information in its database called a knowledge database. Auditors can use this functionality to make important decisions.

4. Robotic automation of process

Artificial intelligence reviews the processes by applying Robotic Process Automation (RPA). This technology enables the automation of 80% of the repetitive work. Some of the regular operations of auditors like reconciliation, verification etc can be automated allowing the knowledge workers to dedicate their time in the value-added operations which requires high level of human interventions.

5. Data input automation

Most of the internal auditors deals with data input and review. Artificial intelligence can be help in reading of data, analyse and process all documentation. Artificial intelligence generally does not do any mistake. Even more, it can ask for data completion, and provide red flag issues for further inspection.

6. Audit closing procedures

Artificial intelligence can support or even replace human in monthly or quarterly closing procedures. It can the capability of simultaneously prepare the close procedure throughout the period.

 

7. Better audit

Artificial intelligence can audit 100% of company's documents instead of checking sample which traditional auditors would do. It makes audit more efficient and accurate. It creates a situation where the auditor exactly knows what is happening in a company rather than statistically analysing it.

How artificial intelligence can be adopted by auditors

There is a high potential for machine learning to provide augmented analyses to the auditors. It would not replace the CAAT which are generally used by the auditors. The CAAT tools have the capability of performing variety of analyses and then provide list of exceptions for the auditor to evaluate from a particular data set. Machine learning comes into play as the auditor confirms the exception or invalidates that exception and the machine learns to 'look' at the auditor's conclusions and try to identify additional data points about the positives or negatives to apply to additional exceptions it identifies. In this way it learns to better identify exceptions. In a more advanced application, a set of transactions could be provided to an AI tool and machine learning would identify the patters in the transactions and be able to identify what 'normal transactions' look like. Using this method, it would then identify those exceptions that don't match the norm as exceptions.

Conclusion

It is a myth that artificial intelligence would replace the need of regular auditor in an organization. Instead, increased use of artificial intelligence will allow auditors to focus on providing better decision making rather than wasting time on data gathering and manual analysis of data. Increased use of artificial intelligence will require auditors to step up and address associated risks through effective governance and internal controls. It is important for auditors to understand how they can leverage artificial intelligence to facilitate their role as an auditor.Auditor expertise in controls design and understanding data biases can also be used to serve other departments in the organization as the departments seek to embrace machine learning. Audit.Tech.Ai. Ai software helps to address the above challenges faced by the auditors to deal with complex financial requirements. Machine learning provides an unprecedented opportunity for auditors and we must embrace it to enhance both careers and the competitive advantage it can provide to the organizations that we serve.

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