Chapter 1 - Data Analytics for Accounting and Identifying Questions

Question 1

What is data analytics?

Answer 1

The process of evaluating data and coming up with insights/conclusions that can help organizations.

Question 2

What are the 3V’s of Data?

Answer 2

Volume - size

Velocity - frequency

Variety - different types

Question 3

How does data analytics affect auditing?

Answer 3

1. Enhances audit quality by being able to test complete sets of data as opposed to samples.
2. Identifying anomalies or trends

Question 4

How does DA affect financial reporting?

Answer 4

1. Better estimates of collectability (bad-debt), and other things like contingent liabilities, etc.
2. Better understanding of business environment through social media.
3. Identify risks or opportunities

Question 5

How does DA affect Tax?

Answer 5

1. Sophisticated tax planning strategies
2. Better understanding of international transactions, investments, M&As
   3.

Question 6

What is the IMPACT acronym?

and what is its purpose?

Answer 6

1. Identify the questions
2. Master the data
3. Perform test plan
4. Address and refine results
5. Communicate insights
6. Track outcomes

Purpose: it’s a data analytics model. Essentially, it provides a framework or methodology for addressing data analytic questions

Question 7

I in IMPACT

Answer 7

Identify the Questions

Understand the business problems that need to be addressed.

Having a concrete, specific question that is potentially answerable by Data Analytics is an important first step.

Question 8

M in IMPACT

Answer 8

Mastering the data

Knowing what data is available inside the ERP of the company and how they relate to the problem you’re trying to solve.

Question 9

P in IMPACT

Answer 9

Perform the test plan

Analyzing the data: selecting the appropriate model to find a target variable

Using all available data, we see if we can identify a relationship between the response or dependent variables and those items that affect the response (also called predictor, explanatory, or independent variables). To do so, we’ll generally make a model, or a simplified representation of reality, to address this purpose.

Question 10

A in IMPACT

Answer 10

Address and Refine Results

It is an iterative process to arrive at the best answer

ask further questions, explore data, rerun analyses

But once that is complete, we have the results ready to communicate to interested stakeholders.

Question 11

C & T in IMPACT

Answer 11

Communicate Insights and Track Results

A picture’s worth a thousand words, that being said don’t neglect substance for the superficial though.

(visualizations)

Tracking outcomes - how frequently should you perform the analysis, what are the trends?, what has changed since you did your analysis?

Question 12

Big Data

Answer 12

Datasets that are too large and complex for businesses’ existing systems to handle utilizing their traditional capabilities to capture, store, manage, and analyze these datasets.

Question 13

Classification

Answer 13

A data approach that attempts to assign each unit in a population into a few categories potentially to help with predictions

Question 14

Clustering

Answer 14

a data approach that attempts to divide individuals (like customers) into groups (or clusters) in a useful or meaningful way.

Question 15

co-occurrence grouping

Answer 15

 A data approach that attempts to discover associations between individuals based on transactions involving them.

Question 16

Data dicitionary

Answer 16

Centralized repository of descriptions for all of the data attributes of the dataset.

Question 17

data reduction

Answer 17

A data approach that attempts to reduce the amount of information that needs to be considered to focus on the most critical items (i.e., highest cost, highest risk, largest impact, etc.)

Question 18

link prediction

Answer 18

A data approach that attempts to predict a relationship between two data items.

Question 19

profiling

Answer 19

A data approach that attempts to characterize the “typical” behavior of an individual, group or population by generating summary statistics about the data (including mean, standard deviations, etc.).

Question 20

predictor (or independent or explanatory) variable

Answer 20

A variable that predicts or explains another variable.

Question 21

response (or dependent) variable

Answer 21

A variable that responds to, or is dependent, on another

Question 22

regression

Answer 22

A data approach used to predict a specific dependent variable value based on independent variable inputs using a statistical model.

Question 23

similarity matching

Answer 23

A data approach that attempts to identify similar individuals based on data known about them.

Question 24

Effects of data analytics on audit

Answer 24

• Shift from checking for errors, material misstatements, fraud and risk in financial statements to collecting and analyzing data much like a business analyst does and providing insights to clients for decision making. This is expected to change the length of engagements with clients for external auditors
• It also improves capabilities in fraud detection as you no longer need to limit yourself to testing a sample only (substantive and detailed testing improved)

Question 25

Effects of data analytics on financial reporting

Answer 25

• Improvements in estimates such as accounts receivable, bad debt, allowance for doubtful accounts, etc.
• Obsolete inventory, valuing inventory at market or cost, when will it be out of date, etc.
• Goodwill impairment
• Contingent liabilities - warranty claims or litigations
• Better understanding of environment: threats and opportunities

Question 26

DA benefits for Tax

Answer 26

• be used is the capability to predict the potential tax consequences of a potential international transaction, R&D investment, or proposed merger or acquisition.
• Might be slow to take due to the lack of tax data infrastructure. But it will take, so be ready to make your mark