Technical Article - 2
Auditing by Data Analytics
There term data analytics is trending worldwide for all the right
reasons. You must have heard of data analytics but probably don’t
understand what the term means. Well, we will not only help you
understand the term better but look at how data analytics can help you
in the field of auditing.
What is Data Analytics?
Data analytics is the process of analysing data that is in raw form, to find useful
information within it and make conclusions regarding the information. Often,
data analytics is carried out through specialized systems and software. Through
the use of these systems and software, data is extracted and categorized to
identify and analyse any patterns or trends within the data.
Advantages of data analytics
Businesses use data analytics in many forms to their advantage. Data analytics
can be used to enhance the decision-making process of a business as it allows
businesses to analyse data much better in all fields of the business.
Similarly, data analytics can be used in the marketing process of a business to
analyse the data regarding the customers of the business. Because of data
analytics, businesses can enhance the quality of their products and tailor
specific marketing campaigns towards their customers.
Finally, through the application of data analytics, businesses can enhance their
processes and save costs by streamlining these processes. This is because
businesses obtain a better understanding of their processes through the use of
data analytics. Since the process of data analytics also allows businesses to
understand their customers better, it can help businesses forge their processes
according to the needs of their customers, thus saving time and costs.
Muhammed Jazeem ACCA, MCOM, PGDM
Uses and benefits of data analytics in audits
Now that you understand what data analytics is and why it is important for
businesses, let’s take a look at how data analytics can help in the process of
auditing.
Data analytics can be applied throughout the audit process to enhance the
process. Most larger audit firms already use data analytics within their audit
process while smaller audit firms have started to adopt it. They use data
analytics in different stages during the audit process such as risk assessment,
audit planning, test of controls, analytical procedures, etc.
Overall, data analytics can be used to gain an understanding of client’s business
by analysing the data, both financial and non-financial. Data analytics can be
used to structure this data into a visual output rather than numbers to allow the
auditor to identify any patterns or trends within the data. This also allows
auditors to easily identify any irregularities within the data, which would be
difficult to identify in an unorganized numerical data.
In assessing the risk of a business, auditors can use data analytics to obtain the
latest information regarding the business from social feeds, news feeds, market
feeds. This information can be stored in a structured manner to help the auditor
analyse the risks involved in the audit process. This can also help auditors
analyse any risk and control issues and adjust their audit procedures
accordingly.
Similarly, when testing the controls of business, data analytics can be used to
identify any instances of inefficiencies within the internal control of the
business. Data analytics can also be used to detect any trends in control issues.
This can help the auditor detect any frauds within the organization. Data
analytics can also be used to test data to assess whether the internal controls of
the business are effective or not.
Data analytics is also a great screening tool to detect any instances of fraud
within the business. This is because it can be used to detect any anomalies in
data and detect any manipulation in the financial statements, which can be an
indicator of fraud. Even if the irregularities are not caused by fraud, they still
need to be analysed by auditors to determine what caused them.
Due to the time restraint and the quantity of data that auditors must analyse,
manually going through all the data can take a lot of time. Data analytics can
easily take over the manual analyzation of data for the auditor and save time
during the process, thus, leaving the auditor to focus on other tasks. Similarly,
data analytics allows auditors to easily increase their sample size during the
audit without worrying about deadlines as all processing is done automatically.
Muhammed Jazeem ACCA, MCOM, PGDM
Data analytics also allows group auditors to apply consistency across group
audits by using the same technology and processes for all the companies within
the group. This allows group auditors to gain a better understanding of the
group and get an overall view of the group.
Examples in data analytics application in audits
While we saw how data analytics can be used and is beneficial for audit
purposes, we will now look at how auditors use data analytics practically in audit
assignments. Examples of application of data analysis within audits are as
follows:

Three-way matching. Comparing purchase order with the related
invoice and the invoice with the related goods received notes for
purchases, for instance.

Trend analysis. Analyzing revenues and expenses for any specific
trends and identifying any irregularities.

Variance analysis. Analyzing expenses and revenues against
standard processes for any irregularities.

Segregation of duties testing. Identifying combinations of
personnel involved in the processing and authorizing transactions.
These are some of the examples of the practical usage of data analytics within
the audit process.
Muhammed Jazeem ACCA, MCOM, PGDM
Challenges of using data analytics
If you are wondering why data analytics hasn’t been adopted by some audit
firms, then there are many reasons for it. There are many challenges that
auditors have to face to implement data analytics properly. Some of these
challenges are as below.
One of the challenges of data analytics is that it can be a threat to the
confidentiality of the private data of clients. Data analytics involves copying and
storing the auditee business’ data within the auditors’ systems. In the case of a
data breach, this data can be exposed. This may lead to legal issues for the audit
firm and the firm can lose its reputation as a result.
Similarly, the auditee business may not agree to provide the auditors with all the
data due to various reasons. Therefore, data analytics may not be used
throughout the audit process. Due to this reason, the same standards cannot be
applied for all auditee businesses, if they won’t allow it, thus, resulting in
inconsistent results for different audits.
Auditors also need to learn how to properly use data analytic tools for the best
results. The use of data analytics across the auditing process is not effective if
data processed and extracted by these tools cannot be interpreted properly by
the auditors. This poses a challenge to the use of data analytics as it requires
the auditors to be trained to properly use these tools to their advantage.
Another challenge for the use of data analytics is that while these tools can be
useful in processing data, the data is still provided by the auditee business. This
means that this data can still be manipulated by them. Similarly, the data
required for these tools to function may not be readily available and needs to be
extracted. If data cannot be extracted or the data is incomplete, then the data
analytics tools cannot perform effectively.
These are some of the examples of the challenges posed to auditors for using
data analytics.
Muhammed Jazeem ACCA, MCOM, PGDM
Conclusion
Data analytics is the use of systems or software to analyze data and extract
useful information from it. While data analytics has been used in other
industries, it is fairly new in the auditing industry.
There are many uses and benefits of data analytics in audits throughout the
auditing process, such as risk assessment, audit planning, test of controls, etc.
However, using data analytics within these processes may come with a few
challenges.
Muhammed Jazeem ACCA, MCOM, PGDM