CH10 audit approach Flashcards

(25 cards)

1
Q

What are overall responses to risks of material misstatement?

A

Changes to the general audit strategy or reaffirmations to staff of the general audit strategy

Examples include emphasizing professional scepticism and assigning more experienced staff.

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2
Q

What is one way to respond to risks of material misstatement?

A

Emphasizing to audit staff the need to maintain professional scepticism

This ensures that auditors remain critical and questioning throughout the audit process.

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3
Q

How can auditor teams be strengthened in response to risks of material misstatement?

A

Assigning additional or more experienced staff to the audit team

Experienced staff can provide better judgment and oversight.

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4
Q

What role can experts play in responding to material misstatement risks?

A

Using experts, the work of internal auditors or other auditors

Experts can provide specialized knowledge that enhances audit quality.

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5
Q

What is a method to enhance supervision during an audit?

A

Providing more supervision on the audit

Increased supervision can help ensure adherence to audit standards.

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6
Q

What does incorporating unpredictability into audit procedures entail?

A

Incorporating more unpredictability into the audit procedures

This can help deter potential misstatements by making it harder for clients to anticipate auditor actions.

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7
Q

According to ISA 330, what must auditors design and perform?

A

Further audit procedures whose nature, timing and extent are based on and in response to assessed risks of material misstatement at the assertion level

This ensures that audit efforts are tailored to specific identified risks.

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8
Q

What is data analytics in the context of auditing?

A

The use of technology through the audit to improve audit quality.

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9
Q

Why has data analytics become important in auditing?

A

Due to much of the client’s data now being stored on computers rather than printed paper.

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10
Q

At which stages of the audit can data analytics be utilized?

A

From the risk assessment stage to the testing of controls and substantive testing.

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11
Q

What is one method used in the planning & risk assessment stage of auditing?

A

Use of graphics to visualize results through the year vs last year or budgets.

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12
Q

What type of analysis can help identify unusual transactions?

A

Ratio analysis month by month.

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13
Q

What unusual transactions might data analytics help identify?

A

Manual/unauthorized journals vs authorized system generated.

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14
Q

How can data analytics help in identifying invoice issues?

A

Easier identification of duplication of invoices or journals.

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15
Q

What type of data can alert auditors to potential problems?

A

Unstructured data such as comments on social media or emails.

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16
Q

In substantive testing, what is a key advantage of data analytics?

A

Procedures can be on the whole population rather than sampling.

17
Q

What is an example of a comparison made during substantive testing?

A

Comparing last time an item was purchased then sold for cost/NRV testing.

18
Q

What can be calculated to analyze receivables?

A

Receivables days calculated by customer or revenue trends by product.

19
Q

What trend analysis can be done to identify issues?

A

Analysis of gross margin trends by unit to identify those with negative margins.

20
Q

What detailed recalculations can be performed in auditing?

A

Detailed recalculations of fixed depreciation assets by item.

21
Q

What matching procedure is used in testing controls?

A

Matching of orders to goods dispatch notes to sales invoices to cash received.

22
Q

What is a limitation of data analytics in auditing?

A

It relies on the quality of the data, and if controls are weak, this quality might be poor.

23
Q

What insight can data analytics provide regarding controls?

A

You can see who is posting what and consider whether they should be.

24
Q

What are key issues for auditors regarding data analytics?

A

Developing systems and expertise to manipulate and interrogate the systems and the cost of this infrastructure.

25
Four data analytics routines relevant to inventory
Identify journal entries impacting inventory Match POs, GRNs and purchase invoices Reperform inventory ageing analysis Compare value with post y/e selling prices