As a forensic account, the type of data that will be analysed is determined by each specific
engagement. Different types of data will be analysed for different types of engagements. Sufficient,
relevant, and reliable data is all subject to the expert’s opinion, and can vary from person to person.
Because ever engagement differs in some way, whether minute differences or large ones, so there is no
"one-size-fits-all approach" to defining relevant and sufficient data (LaGrossa, 2023). LaGrossa
continues to explain that the AICPA's professional guidance proclaims assumptions that have the
biggest effect deserve the most attention (2023). Thus, it is of the utmost importance that forensic
accountants thoroughly analyze each engagement to have the best opportunity to obtain the most
relevant and sufficient data. The Federal Rules of Evidence (FRE) have specific rules for evidence and
date, Rule 401 states evidence is relevant if it makes the fact probable than without the evidence and
that "the fact is of consequence in determining the action" (Rule 401. Test for Relevant Evidence,
2011). The forensic accountant must follow the objectives of the specific engagement, and use their
expert knowledge to develop their hypothesis and collect relevant, sufficient, and reliable data.
Gathering Data in Forensic Accounting
Forensic accounting stands at the intersection of accounting and criminal investigation. Similar to a
traditional colleague, a forensic accountant works with financial records. However, instead of noting
trends and providing suggestions to the management, this specialist searches for evidence of fraud
(Jordan, 2022). As a forensic accountant, I would analyze information from multiple sources in order
to reveal discrepancies and errors pointing to potential fraud schemes. Specifically, I would study
audit results to determine the validity of financial statements. In addition, I would study supply and
service contracts to find strange patterns and trace corporate fraud disguised as legit business deals.
Furthermore, I would interview staff members of companies involved in suspicious activities to
confirm the evidence gathered after financial records and contract analysis. Overall, the type of data
analyzed in forensic accounting is determined by the initial source of suspicion. However, financial
statement analysis is usually the first step, whereas contract analysis and interviews act as a failsafe
that helps reveal the truth or prevent false accusations.
Since forensic accounting is a complex profession, an analyst must rely on special tools to ensure the
quality and reliability of the gathered data. The fundamental principle of forensic accounting lies in
finding patterns, actions, relationships, and transactions pointing to fraud schemes. For that purpose,
professional accounting companies utilize analytics repositories that identify and consolidate warning
signals and conduct network mapping to explore potential fraudster relationships (Deloitte, 2018). In
addition, forensic accountants employ algorithms that sift through massive amounts of data to identify
deviations from ordinary behaviors or compare cases to historical fraud schemes (Deloitte, 2018).
Ultimately, the data gathered by a human analyst gets extensively checked by powerful data-mining
algorithms that help identify rare events and prepare the evidence for presentation.
The types of data that a forensic accountant will need to analyze will be determined by the type of
case that they are working on. Even if two cases are the same, they may still require different data
analysis (Rufus et al., 2015). As the text states, a business valuation case could require different data
than the next due to what is being looked at in the case. Doing due diligence will better allow the
accountant to decide what data is necessary. Having sufficient and relevant data can be a matter of
professional judgement (Rufus et al., 2015). While it is easy to see when data is insufficient and
irrelevant, it can be much more difficult to determine what is. A like most things in business, opinions
will vary on what is sufficient and what is relevant to a certain case. The best way that anyone can
know that they have enough data is to make sure to do due diligence for every case. Getting into a
mindset where they think that the same data will work for every case of a certain type can be very
dangerous. It can also be noted that depending on if the case is one looking for fraud or just an analysis
will change the type of data that is needed. Reliable information can be difficult to obtain in some
situations also. In the case study that I am working on for my final, the company had two sets of books
going at the same time. While the auditing firm was able to say that nothing stood out to them as fraud
from the made-up set of books, does not mean that it was not reliable information. Some of the
information provided was accurate, however not all was. One needs to be able to decide if they are
taking everything at face value or questioning just parts of the information and data.
Data analysis is the breakdown of information (data) into segments that help to make informed
decisions. For the information to be useful, there must be a well thought out approach answering
several questions; what data is required, how will the data be analyzed, and how will the results help
support the response. It is important to take into regard the limitations of the data as well, such as
missing data, altered data, data form, data definition, unretained data (Robert Rufus, 2015). Other
considerations are time constraints, access to the data, and technological resources.
To obtain the data it must come from a reliable source.
The first party data comes directly from the individual or entity and is the most meaningful.
The second party is a source that is connected to the subject and may have firsthand information.
Third party data is data that has been retained from an outside source such as a governmental agency
or financial institution.
Fourth party data is not specific data but more informative of the subject’s environment (Robert Rufus,
2015).
A good analysis is dependent on the data being sufficient and relevant. AICPA Rule 201 requires
there be sufficient data to allow for reasonable conclusions or recommendations. z Sufficient should be
in quantity and quality and is supportive of the opinion. z Relevant is dependent on the actual purpose
for the engagement which guides what type of data should be obtained (Robert Rufus, 2015).
As a forensic accountant, the specific data obtained will need to be tailored to the objectives of
intended engagement. In general, when data analysis is conducted, “we take some set of information
and break it down into manageable pieces. The purpose of this action is to drill down to the essence or
meaning of the information, which may not be apparent when viewed as a whole. This interpretation
highlights an important aspect of data analysis—its strategic nature. In a forensic accounting
engagement, successful data analysis is not conducted indiscriminately. It requires a well-defined
purpose, careful planning, and a systematic process, all aimed at refining the working hypothesis”
(Rufus, 2015, page 227). The data obtained needs to sufficient to support their expert opinion and will
be the basis for their witness testimony per Rule 702 and 401 of the federal rules of evidence.
z Rule 702 of the federal rules of evidence states that the testimony of an expert witness would
be allowed if it will help the trier of fact see scientific, technical, or other specialized knowledge of
evidence. z The three specific criteria are:
The testimony is based upon sufficient facts or data.
The testimony is the product of reliable principles and methods.
The principles and methods have been applied reliably to the facts of the case.
With regards to the issue of being sure you have sufficient, relevant, and reliable data, data is sufficient
when it can support your expert opinion, is relevant to the objectives of the engagement, and support
your working hypothesis.
References
Rufus, R. J., Miller, L. S., & Hahn, W. (2015). Forensic accounting. Pearson.
Robert Rufus, L. M. (2015). Transforming Data into Evidence (Part 1). In L. M. Robert Rufus,
Forensic Accounting 1st Edition (pp. 227-246). Pearson Education.
Rufus, R., Miller, L., & Hahn, W. (2015). Forensic accounting. Upper Saddle River, NJ: Pearson
Education.
Deloitte. (2018). Forensic analytics in fraud investigations: Identifying rare events that can bring the
business down. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/finance/us-forensic-
analytics-in-fraud-investigations.pdf
Jordan, J. (2022, March 27). What is forensic accounting & how do forensic accountants investigate?
NarraSoft. https://narrasoft.com/how-to-forensic-accounting/
LaGrossa, J. (2023, February 7). What constitutes sufficient relevant data in CPA forensic services
engagements? The Legal Intelligencer. Retrieved March 9, 2023, from
