JRSSEM 2021, Vol. 01, No. 2, 148 – 162
E-ISSN: 2807-6311, P-ISSN: 2807-6494
DOI : 10.36418/jrssem.v1i2.13 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
FINANCIAL STATEMENT DETECTION USING FRAUD
DIAMOND
Menik Indrati¹
Nadya Claraswati²*
1,
2
Faculty of Economics and Business, Esa Unggul University, Bekasi, Indonesia
e-mail: menik.indrati@esaunggul.ac.id
1
, [email protected]
2
*Correspondence: nclaraswati@gmail.com
Submitted: 18 September 2021, Revised: 26 September 2021, Accepted: 27 September 2020
Abstract. This study aims to detect fraudulent financial statements using the theory fraud
diamond. Financial statement fraud is measured using the Modified Jones Model. Disclosure of
accrued income from credit sales and accrued receivables of the company is the reason for using
the Modified Jones Model. In this study, the authors add the use of the receivables ratio as a proxy
variable from the nature of the industry so that the most suitable research model used in detecting
financial statement fraud is using the Modified Jones Model. The population in this study are all
property and sector companies real estate listed on the Indonesia Stock Exchange for the 2015-
2019 period. The sample in this study was 20 companies (100 company data with an observation
period of 5 years) in the property and sector real estate listed on the Indonesia Stock Exchange
from 2015 to 2019. Using multiple linear regression statistical methods and hypothesis testing
using SPSS version 26. This study indicates that financial stability, target, and auditor change do
not affect financial statement fraud. Meanwhile, external pressure, the nature of the industry, and
total accruals affect fraudulent financial statements.
Keywords: fraud in financial statements; fraud diamond; financial stability; pressure; financial
targets; nature of the industry.
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INTRODUCTION
The limited amount of vacant land is
one of the factors that makes real estate a
profitable business in the context of rapid
population growth and increasing demand
for housing and the limited land area
required for developer's real estate to
remain competitive (Lessambo, 2014).
Many frauds occur in the real estate
industry, especially in anticipation of
paying taxes so that the amount is not high.
Certain types of fraud can occur inland, and
real estate transactions where the numbers
are shown do not match the actual events.
This is done because the tax imposed is not
high and each party benefits from the fraud
committed (Fimanaya & Syafruddin, 2014).
Information provided by the needs or
desires of certain parties can pose a risk of
fraud because the financial statements do
not describe the company's actual state but
are prepared to achieve the goals of certain
parties (Zhou & Kapoor, 2011). Given the
impact of financial conditions on
stakeholder decisions, companies are
forced to provide interesting financial
information. This is done to help companies
obtain support through investments or
loans from these stakeholders (Novrianty,
2018). Because until now, fraud in the
property sector still occurs due to lack of
supervision and opportunities that
continue to exist (Warohman, 2017). There
are many ways to detect fraud, such as
diamond fraud. Wolfe & Hermanson (2004)
developed a model fraud triangle by
adding capability as one of the factors
driving fraud.
In the element fraud diamond, financial
stability with elements of pressure that
threaten the business is caused by the state
of the industry, economy, or business
conditions. Management is often forced to
show that the company can manage its
assets well, achieve profitability, and
generate high returns for investors
(Septriyani & Handayani, 2018). The high
value of assets owned by a company makes
it attractive to investors, creditors, and
entrepreneurs. However, when the
company's total assets fall, investors may
not care because they conclude that its
financial situation is terrible. As a result,
management uses fraudulent financial
statements as a tool to protect against
volatile economic conditions (Sihombing,
2014).
Stakeholder demands and demands
from third parties put external pressure on
the company to remain competitive and
work harder. To overcome these pressures,
companies need additional debt or external
sources of capital to stay competitive, such
as R&D funding and capital investment
(Skousen et al., 2011). Risks that can occur,
such as manipulating income to achieve
company management goals and showing
the current year's net income as or
exceeding the previous year's profit, will
eliminate investors' interest in investing
(Skousen et al., 2011).
The company will be said to be stable
when the company is in a position
appropriate in an industrial environment.
This stable condition can be measured
through accounts receivable in the financial
statements (Irwandi et al., 2019). In the
financial statements, there are certain
accounts whose balance is determined by
the company based on an estimate, for
example, bad debts and obsolete inventory
150 | Financial Statement detection Using Fraud Diamond
accounts (Sari & Herdiana, 2016). The
nature of industry conditions in the
inventory and accounts receivable differ
between companies that commit fraud and
companies that do not commit fraud as
disclosed by (Summers & Sweeney, 1998).
To illustrate the rationalization,
explained using the total accrual by
comparing the total net income for the
current year minus the actual cash flows
from operating activities (Skousen et al.,
2011). The existence of attitudes,
characteristics, or other ethical standards
allows certain parties to commit fraud or
force someone under pressure to
rationalize fraud (Skousen et al., 2011).
Knowing that there are gaps in when
and how perpetrators can commit fraud is
an act of capability (Goleman et al., 2019).
Where fraud would not occur without the
right people with the capacity and
opportunity to carry out all the details of
the scam, fraud would not happen. One of
the factors that can determine the potential
for fraud in the CEO, board of directors,
managers, or other department heads are
using these positions to influence other
people to expedite their fraudulent actions
(Nisa et al., 2019).
According to Indarto & Ghozali
(2016), do not use the nature of the
industry as a research variable and do not
use total accruals as a proxy for the
rationalization variable. The study was
conducted on banking companies in the
2009-2014 period by showing that the
elements in the fraud diamond consisting
of financial stability, pressure, financial
targets, and ability are positively related to
fraudulent financial statements. However,
the researcher uses the proxy variable
nature of the industry, total accruals as a
proxy variable for rationalization, and the
object of research used is property and
companies real estate listed on the
Indonesia Stock Exchange (IDX) for the
2015-2019 period.
Agency Theory
The emergence of an agency
relationship is because there is a contract
between the agent and the principal who
delegates authority over decision-making
to management (Jensen & Meckling, 1976).
The essence of agency theory is
determining the most efficient contract
between the principal and the agent
(Indrati et al., 2018). When managers are
interested in maximizing their welfare,
agents may not act in the interests of
stakeholders. Therefore, the information
produced by management allows
misleading users of financial statements.
The difference in interest will result in a
conflict of interest between agents and
principals, leading to agency costs. Agency
theory arises because of the diversity of
interests between management and
stakeholders. The goals between
management and investors are challenging
to reconcile, which causes unclear
information between the two parties. This
condition occurs because managers have
more information about the company than
the information obtained by shareholders,
so that it will encourage manager behavior
to manipulate some information to
investors (Annisya et al., 2016).
Theory Diamond Fraud
Added by Wolfe & Hermanson (2004),
element capability of the three factors that
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have been found before are factors that can
influence a person to commit fraud. Wolfe
& Hermanson (2004) argues that fraud will
not occur without the right people with
suitable capacities and opportunities. The
conditions involve possible cheating
factors, including location, brainpower,
self-confidence or ego, compulsions, stress
immunity, and effective lying. In
committing fraud, one must have the ability
to see loopholes and take advantage of
them as opportunities to commit fraud.
Fraud occurs because of the chance to do
so, pressure, and the power of individuals
who can make it happen. Therefore, the
company uses the services of a public
accountant to audit the company's financial
statements, which is expected to limit
fraudulent practices, so that it is expected
to increase stakeholder confidence in the
company's balance sheet (Sihombing,
2014).
Fraudulent Financial Statements
Companies are always required to
make improvements and increase their
operational efficiency to increase their
market value. If a company cannot increase
its value in the capital market, it risks
bankruptcy. The company does not always
meet the market demand for better
performance every year. The existence of
market demands to have better
performance year after year cannot
necessarily be completed by the company
(Gantino, 2013). If the company
experiences an increase, the percentage
may not be too significant compared to
similar competitor companies. Therefore,
companies often carry out earnings
management in various ways to win
investors' hearts (Suryani, 2019). Fraudulent
financial statements in the disclosure of
financial statements are one of the
behaviors that violate the law by
manipulating users of financial information
so that it has a significant impact, such as
loss of investor, customer trust, and
damage to the auditor's reputation.
Management deliberately provides
false information to please investors and
creditors. Fraud in the presentation of
financial statements can result in poor
financial information and impact
stakeholders. Not only investors will be
affected, but creditors and auditors as well.
Auditors need to understand the
characteristics of fraud budget preparers to
anticipate and respond to errors made by
management (Sihombing, 2014).
Relationship Between Variables
The relationship between variables in
this study is depicted in the research model
as follows:
Figure 1. Research Model
The test was carried out using the
152 | Financial Statement detection Using Fraud Diamond
multiple linear regression method with the
classical assumption test stages, including
normality, multicollinearity,
autocorrelation, and heteroscedasticity.
Then the accuracy of the regression
function in knowing the accrual value can
be measured from the goodness of fit
value. Statistically, the excellence of fit
value can be calculated from the coefficient
of determination, F test, and T-test.
Based on the explanation above, this
study aims to examine the factors that
influence financial statement fraud,
including external pressure, financial
stability, financial targets, industry
conditions, total accruals, and changes in
directors that can affect someone to
commit fraud. Companies caught
committing fraudulent acts will experience
a loss of investor confidence and more fatal
consequences such as bankruptcy or
bankruptcy. And as material for company
evaluation and improvement, companies
need to identify fraudulent financial
statements using fraud diamonds. So that
doing this research will provide benefits for
the parties concerned.
METHODS
Population and Research Sample
The population in this study uses
property companies (real estate) listed on
the Indonesia Stock Exchange. This study
uses secondary data from the company's
annual financial statements obtained from
the official website of the Indonesia Stock
Exchange for the period 2016 to 2019. The
sampling in this study uses a purposive
sampling technique using specific
considerations.
Operational Definition of Variable
Financial statement fraud will be
measured using the Modified Jones
Model as determined by Dechow et al.
(2012). Modified Jones Model is one of
the calculation models determining
earnings management Dechow et al.
(2012). Modified Jones Model has the
concept of accruals divided into two,
namely discretionary accruals and
non-discretionary accruals.
Discretionary Accruals are the
recognition of accruals of profits or
expenses that are not bound and are
not regulated and are the choice of
management policy. While Non-
Discretionary Accruals are appropriate
accruals and are under generally
accepted accounting principles, if they
are violated, they can affect the quality
of financial statements to be
unreasonable (Rohmaniyah &
Khanifah, 2018). Modified Jones Model
is used because it reflects credit
income on an accrual basis. In this
study, the receivable ratio is used as a
proxy variable in the element fraud
diamond. So the Modified Jones
Model is very suitable as a method of
measuring financial statement fraud.
Until now, the Modified Jones Model is
considered the best in detecting
earnings management (Tianran, 2012).
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Table 1. Operational Definition of Dependent Variables
No
.
Variable
Measurement
Scale
Dependent
1.
Modified
Jones
Model
Tacit
Taci t / A it -1
NDAit
DAit
= Niit – CFOit
= β1(1/Ait-1)+β2(ΔRevt/Ait-1)+β3(PPEt/Ait-
1)+e
=β1(1/Ait-1)+β2(ΔRevt/Ait-1-ΔRect/Ait-
1)+β3(PPEt/Ait-1)
= TACit/Ait-NDAit
(Dechow et al., 2012) and (Skousen & Twedt.,
2009)
Ratios
154 | Financial Statement detection Using Fraud Diamond
In this study, there is one dependent
variable using fraudulent financial
statements and six independent variables:
financial stability, external pressure,
financial targets, receivable ratios, total
accruals, and turnover of directors.
Financial stability (FS) is proxied by the
percentage of changes in total assets by
comparing comprehensive support for the
current year with total assets for the
following year (Skousen et al., 2011).
External pressure (DTA) is proxied by ratio
leverage measured by dividing total debt
by total equity (Ines, 2017). Return on
assets (ROA) is used as a proxy for the
variable target financial as measured by
income after interest and taxes divided by
the company's total support for the year
(Ines, 2017). The nature of the industry,
which is a proxy variable for the
opportunity, is measured by using the
receivables ratio, which compares the
current year's receivables and sales with the
previous year's receivables and sales (NOI)
(Skousen et al., 2011). Rationalization is
measured by using the current year's net
income minus cash from the company's
operational activities (TATA) (Sihombing,
2014). Also, the capability where the
change of directors can result in a period of
stress that will impact the opening of
opportunities to commit fraud (COD)
(Wolfe & Hermanson, 2004). Change of
directors, which is also measured by a
variable dummy. If there is a change in the
company's directors during the 2015-2019
period, code one will be given, whereas if
there is no change in the board of directors
during that period, it will be coded 0.
A quantitative approach is used as a
research design, which proves a significant
effect of independent variables on the
dependent variable. The variable
determined in this study is the dependent
variable using a fraudulent financial
statement, and the independent variable is
financial stability, external pressures,
financial targets, receivable ratios, total
accruals, and changes in directors.
The population in this study uses
property companies (real estate) listed on
the Indonesia Stock Exchange. This study
uses secondary data from the company's
annual financial statements obtained from
the official website of the Indonesia Stock
Exchange for the period 2015 to 2019. The
sampling in this study uses a purposive
sampling technique using certain
considerations.
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Table 2. Independent Variable Operational Definition
Independent
Financial
Stability
FS
= (Total Assets t - Total Assets t - 1)
Total Assets t – 1
(Skousen et al., 2011)
Nominal
External
pressure
Debt to
Assets Ratio
= Total Debt
Total Assets
(Kasmir., 2013)
Ratio
Financial
Target
ROA
= Earning After Interest and Tax
Total Assets
(Kasmir., 2013)
Ratio
Nature of
Industry
NOI
= Receivables t – Receivables t-1
Sales t Sales t-1
(Summers & Sweeney, 1998)
ratio
Rationalizatio
n
TATA
Net income – cash Flows from the operation
(Dechow et al., 2012)
the ratio
of
Change of
Director
variable mock (dummy variable )to the turn of the Board
of Directors, where 1 = there is a change of directors for
five years priority to the occurrence of fraud and 0 = no
change of directors for five years priority to the event of
fraud
(Skousen et al., 2011)
Ordinal
156 | Financial Statement detection Using Fraud Diamond
Data Analysis Method
Hypothesis testing was carried out
using software SPSS version 26, and
multiple regression analysis using multiple
linear regression equations as follows:
Information :
DACCit : Discretionary accruals company in
the period t
β 0 : Constant
β 1,2,3,4,5,6 : Regression
coefficient of each proxy
FS : Financial Stability
DTA : Debt to Asset
ROA : Return on Asset
NOI : Nature of Industry
TACIT : Total Accruals
e : Error
DACCit = β0 + β1 FS + β2 DTA
+ β3 ROA + β4 NOI + β5 TACIT + β6
CoD + e
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RESULTS AND DISCUSSION
Table 3. Test Results
Descriptive Statistics
N
Minimum
Maximum
Mean
Std.
Deviation
FS
13.5939 .17782
12.37
13.73
92
DTA
78.73 36,066 19.76658
.34
92
ROA
-1.10.3735 .59820
1.26
92
NOI
.8426 .06806
.50
.94
92
Taci t
-
0.14523 .57413 .030569
5 .08033574
92
COD
92
0
1
.222
.415
DCAIT
92
-15.85
-3.23
-8.4029
2.19136
Valid N
(listwise)
92
Table 3. Test Results of Multiple Linear Regression Analysis
Model
Unstandardized Coefficients
Standardized
Coefficients
t
Sig.
B
Std.Error
Beta
1
(Constant)
-33.4
17 133
-1.949
.055
FS
1,298
1,245
.105
1,042
.300
DTA
.013 .254
.28
2,212
.030
ROA
-.479
.425
-.131
-1.127
.263
NOI
7.6
3.31
.236
2.296
.024
Taci t
.304
2,884
8,303
2,879
.005
COD
-.680
.529
-0.129
-1.284
.203
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DISCUSSION
The descriptive statistical analysis can
provide an overview of the data consisting
of the minimum, maximum, average
(mean), and standard deviation values.
Descriptive statistics of all variables used in
the study can be explained as follows:
The amount of data (N) were included
in this study was obtained from a sample of
92 real estate companies and real estate
listing on the Indonesian Stock Exchange,
which was taken using the method.
Purposive sampling The dependent
variable as measured by discretionary
accruals (DCAIT) has a minimum value of -
15.85, a maximum of -3.23, an average of -
8.4029, with a standard deviation of
2.19136. The minimum measure of financial
stability (FS) is 12.37, the maximum is 13.72,
the average is 13.5939, and the standard
deviation is 0.17782. The minimum debt to
the asset (DTA) is 0.34, the maximum is
78.73, the average is 36.0660, and the
standard deviation is 19.76658. Return on
Assets (ROA) has a minimum value of -1.10,
a maximum value of 1.26, an average value
of 0.3735, and a standard deviation of
0.59820. Nature of Industry which is
proxied using the receivables ratio (NOI),
has a minimum value of 0.50, a maximum
of 0.94, an average of 0.8426, and a
standard deviation of 0.06806. The
rationalization proxied using total accruals
divided by total assets t-1 (TACIT) has a
minimum value of -0.14523, a maximum of
0.57413, an average of 0.305695, and a
standard deviation of 0.08033574. The
variable is dummy used to measure the
change of directors (COD). The indication
of the evolution of directors is given a
number 1, and no change of directors is
given a number 0. Therefore, the minimum
value is 0, the maximum is 1, the average is
0.22 with a standard deviation of 0.415.
The results of research conducted on
hypothesis testing H1-H7 indicate that
there are accepted hypotheses and
rejected hypotheses. The explanation of
each theory is as follows:
The results of the multiple linear
regression analysis of the first hypothesis
are financial stability which is proxied by
the comparison of total assets minus total
assets of the previous year divided by total
assets before having a significant value of
0.300 and an arithmetic value of 1.042. It
can be concluded that the results of linear
regression analysis of financial stability do
not affect fraudulent financial statements.
So H₁ is rejected, this result is in line with
(Yusroniyah, 2017). The result shows that
financial stability does not significantly
affect financial statement fraud. No matter
how much the number of assets owned by
the company changes, this will not
necessarily impact fraudulent financial
statements in the future because
companies with significant assets are
unlikely to carry out financial stability to
attract investors to invest in the company.
(Yusroniyah, 2017).
External pressure shows a result of
0.030 where the significance value is
smaller than 0.05, so H₂ is accepted. This
result is the same or consistent with
Suryani's (2019).'s results. The emergence
of the company's reasons for fraudulent
financial statements will be more open if
the company's operations financed by debt
are more significant than the company's
capital. This has become one of the
company's focuses in terms of indications
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of selective management in choosing the
company's operational funding options.
But this can have a destructive impact if the
company continues to make loans without
considering the capital they have to pay off
these obligations. The significant difference
between the company's debt and the
company's total capital is an indication that
the company is not in good health.
Therefore, management will be under
pressure to commit fraudulent financial
reporting by increasing their total equity to
offset the amount of company debt
(Sihombing, 2014).
Return on assets, a proxy variable for
financial targets, shows that the results do
not affect fraudulent financial statements.
So H₃ is rejected. This is in line with research
conducted by Aulia (2018), which proves
that companies are advised not only to
have high profitability targets but also to be
supported by improvements in operational
quality in the company. Because no matter
how high a company's profitability target is,
not necessarily an indication of fraudulent
financial statements (Aulia, 2018).
The nature of the industry, which is a
proxy for the receivables ratio, gives a value
of 0.024 where the value is smaller than
0.05, so H₄ is accepted. In line with
Sihombing (2014) which states that an
increase in the company's receivables from
the previous year can indicate that the
company's cash turnover is not in a stable
condition. The number of accounts
receivable and the high ratio of bad debts
owed by the company will reduce the
amount of cash that the company can use
for its operational activities. Limited cash
can be an impetus for management to
manipulate financial statements (Septriyani
& Handayani, 2018).
Total accruals, a proxy for the variable
rationalization, prove that the significance
value is smaller, namely 0.005 compared to
0.05. Then H₅ is accepted. This result is the
same or consistent with research
conducted by Novrianty (2018). This
happens if the higher the total accruals of a
company, the more fraudulent in the
financial statements. Total accruals can
reflect the company's operating activities
by calculating the current year's net income
minus the incremental cash flows from the
company's operating activities (Dechow et
al., 2012). This happens as a form of
justification by the company to make the
company's financial condition look in good
condition but by cheating or manipulating
profits (Dechow et al., 2012).
Change of director, used as a proxy
variable for capability, shows insignificant
results, namely -1.284, where the
significance value is smaller than the t-
count value of 1.98827. So H₆ is rejected.
This is in line with research conducted by
(Annisya et al., 2016). The change of
directors in the company does not affect
the potential for fraudulent financial
statements. This happened because the
evolution of directors was not because the
old directors took advantage of their ability
to commit fraud but because of other
things. In addition, the change of directors
was successful because the new directors
could use their position to advance the
company further and prevent fraud (Aulia,
2018).
The f test determines whether all
independent variables included in the
regression model have the same effect on
the dependent variable. The calculated F
160 | Financial Statement detection Using Fraud Diamond
value is 2.812, and the significance value is
0.15, indicating that n is smaller than 0.05
(sig < 0.05), which accepts the H₇
hypothesis, indicating that financial
stability, external pressures, financial
objectives, nature in the industry,
rationalization and the ability to influence
financial statement fraud simultaneously.
CONCLUSIONS
Research data are 61 property and
sector companies' real estate listed on the
Indonesia Stock Exchange during 2015-
2019. The research sample is 20 companies
(100 data with five years of observation)
with sample selection criteria using
purposive sampling. This shows that
financial stability, financial target, and
director change do not affect financial
statement fraud. External pressure, the
nature of the industry, and total accruals
affect financial statement fraud.
There are limitations in this study
because it has not used all the variables in
the fraud diamond, and there is a lack of
statistical bias, which is a side effect of
quantitative research methods in reflecting
fraud risk factors. Future research is
expected to use a broader population and
sample listed on the Indonesia Stock
Exchange. For further researchers, it is
recommended to measure rationalization
and ability to use qualitative methods and
use surveys using a Likert scale as primary
data to reflect rationalization and ability
variables.
The managerial implication of this research
for the company is that the management is
expected to be more careful in including
costs or expenses in calculating profits. If an
error occurs, it will impact the more
significant opportunity to carry out
earnings management by reflecting on this
study where external pressure, nature of
the industry, and total accruals positively
affect financial statement fraud. As for
potential investors, to be more careful in
making investment decisions in companies
to be invested in. by assessing changes in
the receivable ratio, changes in the debt to
assets ratio, changes in the company's total
accruals from year to year, as well as
changes in the company's current year
profit in the observation period presented
in the financial statements.
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