Factors Influencing Financial Statement Fraud: An Analysis of the
Fraud Diamond Theory from Evidence of Thai Listed Companies
CHANIDA YARANA
Department of Accountancy, Faculty of Business, Economics, and Communications,
Naresuan University,
99 Moo 9 Tambol Thapo, Muang Phitsanulok Province, Phitsanulok, 65000,
ORCiD: https://orcid.org/0000-0001-8542-9508
THAILAND
Abstract: - Since stakeholders of listed companies rely on the financial statement. However, prior studies
pointed out that financial statement fraud is a significant cause of fraud among Thai-listed companies. This
increases the risk for stakeholders’ decision-making. Thus, this study initially examines empirical evidence
regarding financial statement fraud in line with the Fraud Diamond Theory in Thailand. It proposes to reflect
factors of financial statement fraud that exist. The objectives of this study were 1) to analyze the factors of the
Fraud Diamond Theory that influence financial statement frauds of listed companies in Thailand 2) to examine
the effects of the Fraud Diamond Theory factors on the financial statements of listed companies in Thailand,
and 3) to study the relationship between moderator variables, namely the size of the company and the risks of
the industry, and the factors of the Fraud Diamond Theory influencing the financial statement fraud of listed
companies on the Stock Exchange of Thailand. There were ten independent variables examined as factors
influencing financial statement fraud. The independent variables were classified into four categories, pressure,
opportunity, rationalization, and capability. This study applied a quantitative research approach. Secondary data
were collected from 371 listed companies on the Stock Exchange of Thailand during the 2015–2020 period.
There were 1,855 observations in total. The research used descriptive statistics and logistic regression analysis
to prove the research hypotheses. The results revealed that 11.48 percent of the samples had a high probability
of financial statement fraud. External pressures such as financial targets (ROA), rationalizations such as accrual
(ACCRUAL), and the moderator variable, industry risk (IND), influenced the financial statement fraud on the
Stock Exchange of Thailand at a statistical significance level of 0.05. On the other hand, the other eight
independent variables and the moderator variable, the size of the enterprise, had no significant influence on
financial statements fraud on the Stock Exchange of Thailand.
Key-Words: - The Fraud Diamond Theory, Financial Statement Frauds, Thai Listed Companies
Received: April 2, 2023. Revised: July 9, 2023. Accepted: July 18, 2023. Published: July 27, 2023.
1 Introduction
Since the beginning of the economy, fraud has been
a constant problem that has grown in the financial
world. Even though academics, the government, and
other groups try to stop frauds like corruption,
misappropriation of assets, and accounting fraud,
they still happen. Studies show that there are a lot of
financial statement frauds in business, [1], including
in Thailand, [2]. On the one hand, financial
statements are a way for management to tell
investors, regulators, clients, and the public how the
company did in the last fiscal year. Because of this,
they tend to pressure corporations to show a "good
image and healthy profits." On the other hand,
pressure from outside sources and other factors may
contribute to financial statement fraud, which
destroys the economy, [3]. Nevertheless, the
motivations behind fraudulent financial reporting
are vague and difficult to identify, [4]. Academics
researched to understand the rationales of financial
statement frauds by analyzing components of fraud
theories such as the Fraud Triangle Theory, [4], [5],
[6], the Fraud Diamond Theory, [7], [8], and the
Fraud Pentagon Theory, [9], [10]. At the same time,
some researchers researched to detect financial
statement fraud and explain the relationship between
fraud components in the fraud theories by applying
quantitative techniques. The ratio analysis, [11], and
statistical models such as the F-score model, [4],
[6], [12], [13], and the M-score model, [3], were
applied to measure fraudulent financial statement
reporting. [3], cited that the results of prior studies
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could be more consistent. The research has yet to
study some variables, [3]. Also, a deliberated
analysis of factors contributing to financial
statement fraud is rarely mentioned in the Thai
context. To this end, further study is needed to study
in Thailand.
1.1 Problem Formation
As previously stated, there was a paucity of
empirical research concerning the elements
influencing financial statement fraud in Thailand.
Specifically, there was less evidence when the
aspects of the Fraud Diamond Theory were
included. This study has three primary research
topics for this purpose.
I. How much do the factors of the Fraud
Diamond Theory affect financial statement
frauds at publicly traded companies in
Thailand?
II. How does each factor of the Fraud Diamond
Theory affect financial statement fraud?
III. How do the factors of the Fraud Diamond
Theory that affect financial statement fraud
on the Stock Exchange of Thailand relate to
the moderator variables (size and industry
risk)? Moreover, is there a significant
relationship?
1.2 Research Objectives
I. To analyze factors of the Fraud Diamond
Theory that influence the financial statement
fraud of listed companies in Thailand.
II. To examine the effect of the factors of the
Fraud Diamond Theory on the financial
statement frauds of listed companies in
Thailand.
III. To study the relationship between moderator
variables, namely the size of the company
and the industry's risks, and the factors of the
Fraud Diamond Theory influencing the
financial statements fraud of listed
companies on the Stock Exchange of
Thailand.
1.3 Research Hypotheses
I. H1: External pressure affects the likelihood
of financial statement fraud of listed
companies in Thailand.
II. H2: Financial targets affect the likelihood of
financial statement frauds of listed
companies in Thailand.
III. H3: Financial stability affects the likelihood
of financial statement frauds of listed
companies in Thailand.
IV. H4: The number of audit committees affects
the likelihood of financial statement fraud
of listed companies in Thailand.
V. H5: The number of audit committee
meetings affects the likelihood of financial
statement fraud of listed companies in
Thailand.
VI. H6: The nature of the industry affects the
likelihood of financial statement fraud of
listed companies in Thailand.
VII. H7: Change in auditor affects the likelihood
of financial statement frauds of listed
companies in Thailand.
VIII. H8: Accrual affects the likelihood of
financial statement frauds of listed
companies in Thailand.
IX. H9: The proportion of outside
commissioners affects the likelihood of
financial statement fraud of listed
companies in Thailand.
X. H10: Institutional relationships affect the
likelihood of financial statement frauds of
listed companies in Thailand.
XI. H11: The company's size moderates the
likelihood of financial statement frauds of
listed companies in Thailand.
XII. H12: The risk of industry moderates the
likelihood of financial statement frauds of
listed companies in Thailand.
1.4 Significance
This research aims to look at the factors of the fraud
diamond theory and find real-world evidence of the
factors that lead listed companies in Thailand to lie
on their financial statements. The results of this
study will be beneficial for the management of listed
companies in Thailand in terms of corporate
governance enhancement. In addition, auditors of
listed companies might consider the results of this
study as fraudulent warnings when conducting audit
and assurance engagements.
2 Literature Review
2.1 Concepts and Elements of the Fraud
Diamond Theory
In 2004, Wolfe and Hermanson added to Cressey's
fraud triangle theory, [14], by developing the fraud
diamond theory, [15]. Fraudulent financial reporting
tends to increase constantly and is likely to become
more severe, [15]. While many studies mentioned
three elements of the fraud triangle theory,
composing 1) incentive (pressure), 2) opportunity,
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and 3) rationalization, [15], improved the Fraud
Triangle theory to prevent and detect corporate
fraud effectively. In the fraud diamond theory, [15],
added capability as the main component of the fraud
act. Thus, they suggested four main features of the
fraud acts, namely the "fraud diamond," which is
composed of 1) pressure, 2) opportunity, 3)
rationalization, and 4) capability, [15]. The fraud
diamond theory mentions "a fraudster's thought
process," defining "pressure" as the incentive of a
fraudster who wants to or needs to commit fraud.
"Opportunity" is a weakness of the control system
that can cause a fraudster to commit fraud if he
could. "Rationalization" is a thought process when a
fraudster has convinced himself that his behavior is
worthy, though it may be dangerous. "Capability" is
a personal attribute or personal ability to play a
significant role in conducting fraud. A capable
fraudster will "turn an opportunity for fraud into
reality", [15]. Researchers popularly applied the
fraud diamond theory. For example, studies by [3],
[11], [16], assigned the elements of fraud to
understand financial statement fraud. Further study
is required to identify indicators of pressure,
opportunity, rationalization, and capability, [11].
Therefore, this study considers applying the fraud
diamond theory to explain financial statement fraud
in Thailand.
2.2 Financial Statement Frauds and Fraud
Detection
Accounting fraud has been widely spread
worldwide, [4], [17]. Various fraud acts include
forging documents, embezzlement, and asset
misappropriation. However, financial statement
fraud is a significant accounting fraud, [18], [17].
Due to its typical command by management and
tendency to cause severe corporate collapses,
accounting fraud is "the most harmful financial
crime", [8]. Accounting fraud is "the calculated
misrepresentation of the financial statement that
companies publicly disclose", [17]. Personal
benefits like compensation and mounting
obligations serve as its driving forces. However,
most companies must assign audit and assurance
services to auditors, and the auditing procedures are
often ineffective in detecting financial accounting
fraud. In response to eliminating fraud, academics
attended to develop various techniques of fraud
detection, for example, comparative techniques,
ratio analysis, percentage analysis, cash flow
analysis, [1], Benford's Law of Odd Numbers,
statistical analyses such as Altman Z-score, Benish
M-score, Vladu, Amat, and Cuszdiorean Z-score,
and F-score, [19]. Computerized techniques are also
utilized in detecting financial statement fraud at
present. For instance, [20], noted that specialist
software with real-time fraud detection, data mining,
and data matching is also popularly used in fraud
detection, [20].
2.3 Prior Studies and Independent Variables
Several studies on fraud theories and financial
statement fraud detection have been conducted. For
example, [5], utilized the fraud triangle as a
conceptual theory to understand accounting fraud in
Indonesia. He applied the Beneish M-score model to
detect earnings manipulation in the Indonesian
business context. In his study, panel data is used to
test research hypotheses. The results revealed that
high pressure on financial stability, leverage,
financial targets, low numbers of independent
commissioners, the nature of the industry, and
frequent changes in auditors influence financial
statement fraud in Indonesia.
Fraud theories like the fraud diamond theory
and the fraud pentagon theory have been used to
determine why people lie on their financial
statements. For example, from 2012 to 2016, [7],
used the fraud pentagon theory to find and
investigate financial reporting fraud in Southeast
Asian countries. In their study, the correlation was
applied to test hypotheses. The results disclosed that
the external pressure nature of the industry has a
significant adverse effect on financial statement
fraud. In contrast, financial targets, audit opinions,
and changes of directors have substantial positive
effects.
Also, the fraud diamond theory has been used as
a theoretical concept in the past, for example, [3],
[11]. [21], assigned the fraud diamond theory and
moral reasoning to construct a model. They proved
that culture and motivation significantly affect
Indonesian officers' fraudulent behaviors in the
public sector. Their study utilized structural
equation modeling (SEM) as a statistical technique
to link theoretical concepts with empirical evidence.
[4], applied the fraud diamond theory to analyze
factors that affect financial statement fraud. The
main findings highlighted that pressure and
opportunity are two key factors influencing
accounting fraud. [11], used the elements of a fraud
diamond in detecting accounting frauds in the
banking sector within the stock market of Indonesia.
External pressure, financial stability, and capability
significantly affect financial reporting frauds. [3],
applied the fraud diamond theory to investigate
financial statement fraud. The findings showed that
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financial statement frauds are influenced by
financial stability, personal benefits, the nature of
the industry, multiple ownerships of management, a
change in auditor, rationalization, and capability.
According to [15], four elements might cause fraud
in an organization. Firstly, pressure often occurs
when individuals have reasons to commit fraud.
[11], mentioned that external pressure might lead to
pressure on a company. In their study, pressure from
outside the organization may influence management
to commit fraud because of the high expectations
and demands of the public. [11], applied a debt ratio
to measure external pressure on the company. The
result revealed that companies in Indonesia had a
high debt ratio, which caused the possibility of
financial statement fraud. [12], [13], cite that
financial targets such as return on assets (ROA) lead
companies to commit fraud. The reason is that
managers often present high performance if they
expect high benefits, such as bonuses. Therefore, a
higher ROA can influence fraud commitment.
Moreover, [11], [9], mentioned that financial
stability could be a factor of 'pressure' from the
outside. External factors such as economics and
industry might threaten financial stability. The
liquidity ratio of the companies is measured
according to [11], [9], and financial stability. It is
revealed that the low liquidity ratio leads managers
to commit fraud. Secondly, an opportunity usually
occurs when an organization has weak control. [4],
applied the number of audit committees as an
independent variable in their study. They noted that
many audit committees could reduce the possibility
of financial statement fraud. Also, several audit
committee meetings lead to a high quality of the
company's controls. [11], [5], cited that the nature of
the industry, measured by the receivables ratio,
might be an opportunity to commit fraud. Their
study revealed that the more advanced the industry’s
development, the higher the complexity of the
companies’ activities. The increased complexity of
business transactions and management leads to
abusing their subjective judgment. Thirdly,
rationalization refers to individuals’ attitudes or
characters that encourage them to commit acts of
fraud. [3], applied 'change in auditors' and 'accruals'
as independent variables of the rationalization
factor. A change in auditors means a change in the
frequency of auditor rotation. [3], cites that financial
statement fraud is probable if the companies change
auditors. Also, accrual can be an independent
variable of rationalization. It refers to the gap
between net cash inflow and a company's net
income. According to [14], high accrual amounts
lead to a high probability of financial statement
fraud. Fourthly, capability means the ability of
individuals with high authorization, which
encourages them to commit fraud. Their study used
the proportion of outside board commissioners as an
independent variable, [11]. The researchers noted
that independent commissioners from outside the
companies are not accustomed to controlling
shareholders, which might cause a high risk of
financial statement fraud. In contrast, [13], applied
an institutional ownership ratio as their independent
capability variable. They cited the possibility that
institutional ownership could control management.
Higher, adequate supervision helps reduce financial
statement fraud. [3], noted that the results of prior
studies are inconsistent, and some variables have not
been analyzed in the research, [3]. This study was
aimed at increasing the evidence supporting fraud in
accounting figures in the context of Thailand.
Although there have been studies in Southeast Asian
countries such as Indonesia, [5], [9], [10], [12], [13],
[22], [23], [24], [25], [26], and Vietnam, [6], there is
scant empirical evidence in Thailand explaining the
factors influencing financial fraud at companies
listed on the Thai Stock Exchange. In addition, this
research was studied under the fraud diamond
theory. Although there were previous studies such
as, [13], this research has added the proportion of
outside commissioners and institutional ownership
(capability) as the independent variables to study in
the context of Thailand, and the moderator
variables, namely the sizes of companies (SIZE) and
risk of industry (IND). To determine which variable
influences fraudulent financial statements of
companies listed on the Thai Stock Exchange. The
conceptual framework is set as follows (Figure 1):
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Fig. 1: Conceptual Framework
3 Methodology
3.1 Population and Sample
This research employed a quantitative approach and
secondary data. The financial statements and annual
reports were collected from 371 companies,
excluding those in the finance, property,
construction, and unidentified sectors. In 2020, there
were 630 listed companies on the Stock Exchange
of Thailand (SET) (www.set.or.th, achieved
November 2020). The samples were selected using
the purposive method. There were 1,855
observations obtained from the SET SMART
database, which is the website of the Stock
Exchange of Thailand (http://www.setsmart.com).
The financial statements of selected companies must
present complete annual reports in Thai Baht
currency during the 2015–2020 period. The listed
companies selected financial statements must
disclose research variables' data.
3.2 Measurement of Research Variables
3.2.1 Independent Variables
Based on the Fraud Diamond Theory's independent
variables, there are four types of fraud: pressure,
opportunity, rationalization, and capability.
Financial targets, financial stability, and external
pressure served as proxies for the pressure. The
number of audit committees indicated the
opportunity, the number of audit committee
meetings, and the nature of the industry, [22].
Changes in auditors and accrual served as proxies
for the rationalization, and the proportion of outside
board commissioners (IndCom) and institutional
ownership ratio (KI) served as proxies for the
capability.
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3.2.2 Moderator Variables
Moderator variables refer to variables that are
considered additionally in the study. Since it can
influence independent and dependent variables, [8],
the interaction between the independent and
moderator variables may precede the description of
the dependent variable. [26], suggested two
variables influencing financial statement fraud:
company size and industry risks, [26].
Financial statement fraud is less likely to
happen at big companies than at small ones. The
reason is that large companies are more stable and
efficient than smaller companies. For example, large
companies have a greater frequency of disclosure—
financial reporting requires more attention to
accounting standards. Large companies tend to have
good-quality financial statement analysis and review
of financial reports. Large companies' monitoring
processes are more frequent than small companies,
[26].
Industry risk can also be considered a moderator
variable. The reason is that the quality of each
entity's financial statements is subject to industry
risk. The type of business operations and
environment contribute to industry risk, an external
factor. The diversification of business operations led
the companies to select different accounting
policies. Alternative ways of accounting practice led
to the creative accounting practice of management.
[27], Indonesia's manufacturing industry has the
most vulnerable risk, [27]. Thus, this study assumes
that industry risk may also moderate financial
statement fraud in the Thai context. The variables
used and the measurement is presented in Table 1.
Therefore, the proposed model of this study is as
FRAUD = ß0+ ß1 Express + ß2 Roa + ß3 Stab +
ß4 Noaudit + ß5 Nomeet + ß6 Nature +
ß7 Change + ß8 Accrual + ß9 Indcom + ß10 (1)
Table 1. Variables and measurements
Variables
Measurement
External pressure
Debt ratio =Total Debt
Total Assets
Financial targets
ROA =Net profit after tax
Total Assets
Financial stability
Liquidity ratio =Current Assets
Current Liabilities
Number of audit committees
Number of the audit committee
Number of audit committee meetings
Number of audit committee meetings
Nature of industry
Special Receivables =(Other receivables )t
(Total receivables )t
Change in auditors
Code 1 is a change in auditors in the study period,
and 0 otherwise
Accrual
Accrual = (Profit after tax
−Net cash flow from operation))
The proportion of outside board commissioners
(IndCom)
IndCom =The number of independent commissioners
Total number of commissioners
Institutional ownership
KI =Total institutional share
Total outstanding share
Size (Moderator Variable)
SIZE = Logarithm of Total Asset
Industry Risk (Moderator Variable)
Code 1 is a company in the manufacturing industry
in the study period, and 0 otherwise.
Source: Summarize from the literature review
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3.2.3 Dependent Variables
The F-score statistical technique measures the
dependent variable. [28], developed the F-score
model. The statistical model addresses the
probability of detecting fraud on financial
statements. [28], stated that this study applied the
model to Enron in 2000. The model formula is the
following:
Logit = −7.893 + 0.790 x (rsstacc )+
2.518x(chrec )+ 1.191x(chinv )+
1.979x(softassets )+ 0.171x(chcs )+
(−0.932)x(chroa )+ 1.029x(issue) (2)
Prob (FFR) = e^logit/ (1 + e^logit) (3)
Then, the researcher applied the F-score (Enron)
formula of [6].
The F-Score (Enron) formula equals
(Prob(FFR)/0.0037). In this study, outline variables
were omitted using the "Winsorization" technique
(p < 0.10) of STATA software version 14 to ensure
that all variables were normally distributed.
Multicollinearity was assessed. The correlation
coefficient between independent variables had
values ranging from –0.0177 to 0.2366 and was not
greater than 0.8, which means that this study's
independent variables had fewer multicollinearity
problems. Logistic regression analysis was
completed in STATA version 14.
3.2.4 Ethical Statement
The Human Research Ethics Committee of
Naresuan University granted the ICH-GCP research
certification. It was approved regarding the
Declaration of Helsinki, the Belmont Report, the
CIOMS Guideline, and the International Conference
on Harmonization in Good Clinical Practice. The
researcher strictly conducted the research with
confidentiality and was concerned with the effects
on the listed companies' reputations. To maintain the
confidentiality of the financial statements of listed
companies in Thailand, the researcher did not
mention or analyze research results by referring to
the names of the companies and the industry groups
throughout the research.
4 Results and Discussion
4.1 Descriptive Analysis
The results showed in Table 2.
Table 2. Frequency distribution based on F-Score
Enron
Year Fraud Non-fraud
Total
Obs.
%
Obs.
%
Obs.
%
2016
43
2.32
328
88.41
371
100
2017
47
2.53
324
87.33
371
100
2018
43
2.32
328
88.41
371
100
2019
52
2.80
319
85.98
371
100
2020
28
1.51
343
92.45
371
100
Total
213
11.48
1,642
88.52
1,855
100
Source: Own edition and calculations
Table 2 presents descriptive statistics of this
study's dependent, independent, and moderator
variables; the proxies EX.PRESS, STAB,
NOAUDIT, INDCOM, KI, and SIZE were greater
than 0. According to Table 2, the results show that
1,642 observations were diagnosed as non-fraud,
whereas 213 were diagnosed as financial statement
fraud. Overall, the accuracy of the model was
88.52%.
Table 3 presents descriptive statistics of this
study's dependent, independent, and moderator
variables; the proxies EX.PRESS, STAB,
NOAUDIT, INDCOM, KI, and SIZE were greater
than 0.
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Table 3. The results of the descriptive statistics test
Proxy
Min
Max
Mean
S.D
FRAUD
0
1
.115
.319
EX.PRESS
.12
.69
.403
.192
ROA
-.05
.12
.037
.053
STAB
.55
6.16
2.237
1.78
NOAUDIT
2
5
3.175
.369
NOMEET
0
23
5.685
2.850
NATURE
0
1
.643
.458
CHANGE
0
1
.491
.500
ACCRUAL
-2357189
185356
-525723
773777
INDCOM
.33
.5
.403
.642
KI
.4
7.26
4.164
2.026
IND
0
1
.216
.411
SIZE
103032.76
254418284
34649636
147536150
Note: Total Observations (N) = 1,855
Source: Results of data processing STATA 14
4.2 Logistic Regression Analysis
This study utilized a 0.05 significance level for the
logistic regression analysis. The researcher assessed
the feasibility of the regression model using Hosmer
and Lemeshow's goodness-of-fit test to ensure that
the empirical data was appropriate for the model. It
was found that the chi-square was 5.22, and a
significant value was 0.7339 (p > 0.05),
demonstrating that the model can predict the value
of observations. Table 4 illustrates that the log-
likelihood statistics were -649.8735, and -2Log
likelihood = 1,322.56 (the higher the value, the less
accurate the model). Thus, the result indicates that
the model hypothesized fits the data. However, the
Cox & Snell R square value was 0.0115, and the
pseudo-R-square was 0.0172, meaning only 1.72%
of what affects financial statement fraud. Therefore,
this result indicates the weakness of independent
variables in explaining fraud in this study. Based on
Table 4, financial targets (ROA) and accrual
(ACCRUAL) are the factors that affect the financial
statement fraud of listed companies in Thailand.
Therefore, the second hypothesis (H2) and (H8)
were accepted. The mathematical model can be
presented as follows:
Fraud = -1.96 – (4.708 x ROA) + (2.56 x
ACCRUAL) + e (4)
Table 4. The results of Logistic regression models
Proxy Coef. OR. Sig. HA
ROA -4.708 .00902 0.00 Accepted
ACCRUAL 2.56 1 0.02 Accepted
Constant -1.96 0 0.02
Source: Results of data processing STATA 14
Note: The number of obs. = 1,855
LR chi2 (10) = 22.1
Prob > chi 2 = 0.0115
Pseudo R2 = 0.0172
Log-likelihood = -649.8735
According to Table 4, OR. or Odds Ratio refers to
the logistic coefficient (0, 1,……, 10). Thus, the
logistic model can be presented as follows:
()== : I = 1, 2, 3,...., 10 (5)
When
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= ^( )
1−^()
=0 + 1 + 2 + 3 +⋯+10 (6)
If b_i > 0, then e^(b_i ) > 1 means that the odds
value increases or the likelihood of financial
statement fraud increases.
If b_i < 0, then e^(b_i ) <1 means that the odds
value decreases or the likelihood of financial
statement fraud decreases.
If b_i = 0, then e^(b_i ) = 1 means that the odds
value is neither increasing nor decreasing.
Model interpretation:
The pressure factor, which represents a proxy
value with financial targets (ROA), increasing by
0.01 unit, reducing the likelihood of financial
statement fraud by one unit, can account for the
odds ratio of variable ROA = 0.01, which is less
than 1. According to the STATA statistical program
result, the interval estimates of the odds ratio at a
95% confidence level found that P (0.000507 <= of
the ROA variable <= 0.1603336) = 0.95 had a
minimum value of 0.000507, which is less than one.
The maximum is 0.1603336, which is also less than
1. It can be concluded that ROA variables are
related to changes in the odds ratio.
The rationalization factor, a stand-in for
ACCRUAL, has a positive effect on financial
statement fraud in Thailand for companies on the
stock market. This explains why the odds ratio of
the variable ACCRUAL equals 1. Let's say the
listed companies' accrual (profit after taxes or net
cash flow from operating activities) increases by
one point. In that case, there will be a one-point
increase in the possibility of financial statement
fraud. Interval estimation of the odds ratio at a 95%
confidence level found that P(1 <= of ACCRUAL
<= 1) = 0.95 had the highest and lowest values of 1.
In conclusion, the ACCRUAL variable is related to
the odds ratio change.
4.2.1 H1: External Pressure Affects the
Likelihood of Financial Statement Fraud of
Listed Companies in Thailand
The results revealed that the EX.PRESS coefficient
was 0.878446, more than 0.05. External pressure
measured by debt ratios positively affected financial
statement fraud. However, the effect was not
significant. This result contrasted with [11], and the
Fraud Diamond Theory, [15], where the researcher
claimed that pressure proxied by debt ratio
significantly affected financial statement fraud.
According to [9], a low leverage (debt) ratio can be
achieved to convince investors that the companies
do not struggle with financial problems, [9]. The
possible reason is that those companies have less
borrowing capital than capital market investors.
Therefore, the total debt to total assets ratio
positively influences financial statement fraud but is
not statistically significant, [9].
4.2.2 H2: Financial Targets Affect the Likelihood
of Financial Statement Frauds of Listed
Companies in Thailand
The result showed that financial targets (ROA) had
a coefficient of - 4.71 and a significant value of
0.00. It means the financial targets have negatively
and significantly affected the financial statement
fraud of listed companies in Thailand. The result
went against, [4], [11], [12], [15], [16], [22], [23],
[24], [27], [29], [30], who said that a higher ROA
tends to lead to more financial statement fraud. One
reason could be that financial targets proxied by
ROA cannot cause financial statement fraud unless
managers' bonuses depend on how much money the
company makes, [9]. On the other hand, the
company will try to keep the return on assets (ROA)
low or decrease it because management is
concerned that if the rate of return on assets
increases to a very high level, the likelihood of
monitoring and fraud detection will also increase.
So, management tends to promote a culture where
the rate of return on assets stays low or goes down.
This action can cause a high probability of financial
statement fraud, [31]. The negative relationship
between ROA and financial statement fraud was
consistent with the results of [6], [26], [32], [33].
Further, researchers explained that companies with a
lower ROA than the previous year would try to
increase their earnings per asset ratio in the current
year. Therefore, the company's executives' pressure
may force them to commit fraud in financial
statements, [9].
4.2.3 H3: Financial Stability Affects the
Likelihood of Financial Statement Frauds of
Listed Companies in Thailand
The STAB coefficient was 0.071578, and a
significant value was 0.23, greater than 0.05.
Therefore, financial stability had a positive effect
but was not significant. The result of this study is
consistent with the research of, [23]. The probable
reason was that the listed companies had a high
level of monitoring and control. In addition, external
factors such as economic conditions and social
situations might delay fraud by the entities, [23].
However, these findings contradict, [11], which
found a statistically significant negative correlation
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between financial stability and financial statement
fraud. The researcher explains that companies
experiencing liquidity problems due to economic
conditions may struggle to settle their debts and
obligations. The company's management is therefore
pressured to distort the financial statements.
4.2.4 H4: The Number of Audit Committees
Affects the Likelihood of Financial Statement
Fraud of Listed Companies in Thailand
The result shows that the number of audit
committees negatively affected the financial
statement fraud of listed companies in Thailand
(coefficient = - 0.292357) but had no
statistical significance (Sig = 0.88), which was more
than 0.05. The result is in line with the study in [11].
The possible reasons are that the public believes
several external auditors can deliver high-quality
financial reports and reduce fraud. Instead,
companies build the reliability of their entities
through external audit engagement.
4.2.5 H5: The Number of Audit Committee
Meetings Affects the Likelihood of Financial
Statement Fraud of Listed Companies in
Thailand
The results show a statistically insignificant number
of audit committee meetings (beta value = -
0.014751, sig. = 0.6) that have a negative effect on
financial statement fraud in listed businesses in
Thailand (sig. = 0.60). According to [4], there is a
negative correlation between audit committee
meetings and financial statement fraud. The reason
is that organizations with fewer audit committee
meetings are more likely to perpetrate financial
statement fraud. Moreover, regular audit committee
meetings can convince investors that a company's
financial reports are of high quality. Furthermore,
the outcome is compatible with the Fraud Diamond
Theory, [15].
4.2.6 H6: The Nature of the Industry Affects the
Likelihood of Financial Statement Fraud of
Listed Companies in Thailand
The results show that industry characteristics make
financial statement fraud more likely (Beta = -
0.183257). The significance value for the sixth
hypothesis test was 0.25, which was less than 0.05.
Hence, the nature of the industry has no major effect
on financial statement fraud among Thailand's
publicly traded firms. The result is consistent with,
[13], in which the researcher asserts that the board
of directors cannot strike a balance between the
nature of the industry and financial statement fraud
because companies sometimes require cash for
operations, resulting in the deduction of accounts
receivable owned by the companies. The statement
of financial status must reflect the high value of
cash, but there is a limit to the amount of cash on
hand. Thus, this may push businesses to manipulate
their financial figures. By neglecting outstanding
trade accounts receivable, management may
understate accounts receivable, [23].
4.2.7 H7: Change in Auditor Affects the
Likelihood of Financial Statement Frauds of
Listed Companies in Thailand
A change in auditors had a beta value of 0.076712,
influencing financial statement fraud. Still, the
significant value was 0.60, which exceeded 0.05.
Thus, the outcome suggested that a change in
auditor had no impact on financial statement fraud.
This conclusion contradicts, [24], which found that
auditing switching positively impacted financial
statement fraud. According to [24], yearly auditor
changes may result from falsifying financial
statements. The corporation committing
misbehavior does not want any administrative
irregularities to be probed. Hence, there is a high
rate of audit company turnover. It may take a
significant amount of time for a newly hired audit
team to get familiar with the company's business
environment. New auditors are often unable to
discover fraud within a single accounting period.
4.2.8 H8: Accrual Affects the Likelihood of
Financial Statement Frauds of Listed Companies
in Thailand
Accrual significantly positively affected financial
statement fraud of listed companies in Thailand
(beta value = 2.56, sig. = 0.02). When considering
the odds ratio of the ACCRUAL variable as equal to
1, the accrual factor (rationalization) increase of one
unit would also increase the likelihood of financial
statement fraud by one unit with a statistically
significant level of 0.05. This positive relationship
was consistent with the Fraud Diamond Theory, [3],
[4], [6], [25], [26], [34], [35], results. The possible
reason is that management policies caused accrual
changes—the higher the value of changes, the
higher the likelihood of fraudulent accounting, [3].
It can be implied that financial statement dilemmas
could occur among listed companies in Thailand
when executives exercise their rationalization to
apply accounting policies relating to accrual
transactions. Therefore, management should
appropriately scrutinize the accrual policies before
practice to prevent financial statement fraud.
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4.2.9 H9: The Proportion of Outside
Commissioners Affects the Likelihood of
Financial Statement Fraud of Listed Companies
in Thailand
The results show that the number of outside board
members had no statistically significant effect on
financial statement fraud (beta value = -0.118620,
sig. = 0.92). The results of this study agree with the
Fraud Diamond Theory's, [15], hypothesis and, [11],
findings. [11], argued that external managers, who
are independent, do not have access to shares in the
company and do not have a say in how it is run or
who runs it. So, they thought that the outside board
commissioners would help improve the financial
statement's quality. Thus, an outside board of
commission can significantly reduce the likelihood
of fraud, [11].
4.2.10 H10: Institutional Relationships Affect the
Likelihood of Financial Statement Frauds of
Listed Companies in Thailand
The result demonstrates that institutional ownership
had a negative effect on financial statement fraud.
(Beta value = -0.007380, sig = 0.84). In other words,
if the ownership from other external institutions
increases by 0.0073780 units, the financial
statement fraud will decrease by 1 unit.
Nevertheless, there is no statistical significance. The
negative relationship between institutional
ownership and financial statement fraud aligns with
[13], [15]. However, [13], mentioned that
institutional ownership could not significantly affect
financial statement fraud because insufficient
evidence supports the link between institutional
ownership and the decreasing number of frauds. The
number of institutional owners cannot guarantee that
the management will not commit fraud on the
financial statements. Therefore, it cannot be
concluded that institutional ownership relates to
financial statement fraud, [13].
4.2.11 H11: The Company's Size Moderates the
Likelihood of Financial Statement Fraud of
Listed Companies in Thailand
The result shows that there is no proxy effect on
financial statement fraud in Thai companies that are
on the stock market. The ROASIZE and
ACCRUALSIZE proxies positively relate to fraud
(beta values of 1.31972 and 4.50, respectively).
However, no significant relationships existed (Sig. =
0.23 and 0.66, respectively). Thus, the company's
size does not moderate the likelihood of financial
statement fraud in listed companies in Thailand.
Therefore, the eleventh hypothesis (H11) was
rejected.
4.2.12 H12: The Risk of Industry Moderates the
Likelihood of Financial Statement Frauds of
Listed Companies in Thailand
The effect of a moderator variable (Risk of Industry)
revealed that ROA had a significant negative effect
on the financial statement fraud of listed companies
in Thailand (beta value = -5.53715, sig. = 0.00).
Inter_ACCRUALINDUS significantly positively
affected the financial statement fraud of listed
companies in Thailand (beta value = 9.48, sig. =
0.04). However, ACCRUAL and Inter_ROAINDUS
were not considerably affected by the financial
statement fraud (beta values of 1.81 and 1.301582,
and sig values of 0.09 and 0.67, respectively).
Therefore, the twelfth hypothesis (H12) was
accepted. The industry risk moderates the likelihood
of financial statement fraud in listed companies in
Thailand. The mathematical model can be presented
as follows:
= −1.74 – (5.54 ) + (8)
The Hosmer and Lemeshow test showed that Chi-
square = 10.96, greater than 5.00, and sig. = 0.2039,
which was greater than 0.05. Thus, this model is
appropriate. In addition, Log-likelihood equal to
-648.90308 is calculated for -2Log Likelihood
(-2LL), which is equal to 1,297.81, which is less
than -2Log Likelihood (-2LL), which has only
constants (= 1,322.56). The pseudo-R square
(Nagelkerke R square) was 0.0187. Industry risk is
another variable expected to influence this research's
independent and dependent variables. This study
found that industry risks significantly influenced
accrual variables and financial statement fraud.
Contrary to research by [35], the research found that
industry risks could not moderate financial
statement fraud in Indonesia. The quality of the
financial reports of listed companies in the Thai
context depends on industry risks, which are
external factors. Each industry is sensitive to
financial information, especially accrual
transactions. The higher the industry's risk, the
greater the possibility of financial statement fraud
because of the inherent risk to the company.
However, this correlation can only be explained by
the sample selected in this study. This may change if
other examples are selected to study, [28].
5 Conclusion
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5 Conclusion
This study was done to look at the factors of the
Fraud Diamond Theory and see how those factors
and the moderate factors affect financial statement
fraud in Thai companies listed on the stock market.
The researchers used four parts of the Fraud
Diamond Theory to classify ten independent
variables: pressure, opportunity, rationalization, and
capability. Independent pressure variables are
external pressure, financial targets, and financial
stability. The number of audit committees, the
frequency of audit committee meetings, and the
nature of the industry serve as proxies for
independent variables of opportunity. Independent
variables of rationalization are changing in auditors
and accrual. Independent variables of capability
were the proportion of outside commissioners and
institutional ownership (K.I.). Moderator variables
were the size of the company and the industry's risk.
The dependent variable was the F-score (Enron)
model, proxied by fraud = 1 and non-fraud =0, [28].
Logistic regression was analyzed using STATA
version 14. One thousand eight hundred fifty-five
observations of the period 2015–2020 were gathered
from www.set.or.th and the SET SMART database
of the Stock Exchange of Thailand. The findings
revealed that 231 (11.48%) would likely commit
fraud on financial statements. It can be concluded
that the factors of the Fraud Diamond Theory did
not significantly affect the financial statement fraud
of listed companies in Thailand, except for pressure
(financial targets proxied by ROA) and
rationalization (ACCRUAL). The moderator
variable, such as industry risk (IND), influenced the
financial statement fraud on the Stock Exchange of
Thailand at a statistical significance of 0.05.
This research adds to the Fraud Diamond
Theory, [15], which can be used to describe fraud in
financial statements at the Stock Exchange of
Thailand. The Fraud Diamond Theory says that
there is a chance of fraud in financial statements
because of two elements: 1) pressure (financial
targets) and 2) rationalization (accrual). On the other
hand, industry risks can make fraud at the Thai
Stock Exchange and the financial statements of the
Stock Exchange of Thailand less likely. However,
from the study results from 2016–2020, it was found
that companies listed on the Stock Exchange of
Thailand were only 11.48% likely to commit
financial statement fraud, which is considered a
minority by comparison. An overview of the Stock
Exchange of Thailand shows the reliability of
financial and annual reports communicated to
shareholders and other company stakeholders. This
research also provides practical contributions for the
executives of listed companies in improving good
corporate governance. Management should consider
the return on assets (ROA) and Accrual when they
employ the business's management policy.
Executives of listed companies can motivate
transparency and verifiable accounting information.
As a result, profits are added to financial statements.
Moreover, using outstanding items due to improper
discretion will be reduced.
Acknowledgement:
I thank the Faculty of Business, Economics, and
Communications, Naresuan University, Thailand,
for supporting the research funding.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The author contributed in the present research, at all
stages from the formulation of the problem to the
final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
This research has been granted funding from the
Faculty of Business, Economics, and
Communications, Naresuan University, for the
fiscal year 2021.
Conflict of Interest
The author has no conflicts of interest to declare that
are relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
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