A cross-country study on manipulations in financial statements of listed companies. Evidence from Asia

Pages656-677
DOIhttps://doi.org/10.1108/JFC-07-2016-0047
Published date02 October 2017
Date02 October 2017
AuthorMd Shamimul Hasan,Normah Omar,Paul Barnes,Morrison Handley-Schachler
Subject MatterAccounting & Finance,Financial risk/company failure,Financial crime
A cross-country study on
manipulations in nancial
statements of listed companies
Evidence from Asia
Md Shamimul Hasan
Department of Accounting, Faculty of Business Administration,
EXIM Bank Agricultural University, Chapainawabgonj, Bangladesh
and Accounting Research Institute, Universiti Teknologi MARA,
Shah Alam, Malaysia
Normah Omar
Accounting Research Institute, Universiti Teknologi MARA, Shah Alam, Malaysia
Paul Barnes
Department of Accounting, Macquarie University, Sydney, Australia, and
Morrison Handley-Schachler
ECO-ENA: Economics and ECO-Engineering Associates, Inc.,
South Queensferry, UK
Abstract
Purpose The purpose of this study is threefold: rst, to detect trends in nancial statement
manipulation; second, to measure the level of manipulation and to measure the variation
in manipulation between countries; and, third, to identify widely used techniques in nancial
statements manipulation.
Design/methodology/approach This study uses nancial data of listed companies from Asia,
namely, Japan, Singapore,Malaysia, Indonesia, Thailand, Hong Kong and China.The study adopts nancial
ratios, nancial forensic tool, dichotomous approach and statistical tools to analyze the data (84,000
observations)over a period of four years from 2010 to 2013.
Findings The results show that 34 percent of sample companies in selected Asian countries are involved
in the manipulation of nancialstatements; the average level of manipulation (overall manipulation index) is
72 per cent; and there is a signicant differencebetween countries at 5 per cent level. The study alsoidenties
four most commonly used techniques,namely: dayssales in receivable (DSRI), depreciation (DEPI), assets
quality(AQI) and total accruals to total assets (TATA).
Research limitations/implications Although this study found a signicant national difference
between countries in termsof practicing manipulation in nancial statements, it did not address the issue of
why some countries have higher level of manipulationand greater uctuations in manipulation than others.
Further studycould be conducted to look for the reasons on these issues.
Practical implications Investors and other stakeholders are advised to judge the manipulation in
nancial statements before xing up for investment. At least they should examine Sales, Accounts
JEL classication M41, N25, C43
The researchers gratefully acknowledge the nancial support and generosity of Accounting
Research Institute (ARI) and the Ministry of Education, Government of Malaysia without which the
present study could not have been completed.
JFC
24,4
656
Journalof Financial Crime
Vol.24 No. 4, 2017
pp. 656-677
© Emerald Publishing Limited
1359-0790
DOI 10.1108/JFC-07-2016-0047
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1359-0790.htm
Receivable,Depreciation, Value of Fixed Assets and Accruals data beforeaccepting the nancial statement in
good faith.
Social implications The trend of manipulation in nancial statements is increasing day by day
and that is why it needs to prevent to protect our society from white collar crime. The cost of white
collar crime is much higher and key executives are making money at the expense of investors and
other stakeholders. This kind of study creates awareness among stakeholders about the manipulation
as well as provides techniques to examine the faithfulness of nancial statements. Then, managers
will not overstate or understate either revenues or expenses easily, as it can damage the goodwill.
Originality/value This is the rst study of its kind addressing measurement of manipulation score,
overall manipulation index (OMI) and identication of widely used variables of manipulation in nancial
statementsare new contributions towards existing literature of earningsmanipulation.
Keywords Financial statements, Beneish model, Earnings manipulation,Fraudulent nancial reporting,
M-score, Manipulation score, Overall manipulation index, Asian countries
Paper type Research paper
Introduction
Manipulation in nancial statements is perpetuated by management of a company to
hide reality. They do it using discretionary authority often to full the expectation of
stakeholders instead of showing real performance and nancial position. Hasan et al.
(2014c,2016) state that corporate accruals (discretionary accruals) do not come from the
business cycle but from the mind set of unscrupulous management who wants to suggest
unbeatable performance. Fraudulent nancial statements are a product of deceitful top
management, especially CEO and CFO, as without their involvement, it is impossible to
perpetrate nancial statements. Users of nancial reports are worried about the
truthfulness of nancial statements. Researchers have tried for many years to address
this issue using different mechanism, such as M-Score (Beneish, 1999), Z-Score (Altman,
1968) and corporate accruals (Jones, 1991;Kothari et al., 2005;Dechow and Ge, 2006;
Hasan et al., 2014a,2014b,2016,2017), but still it is a grey area, as fraudsters do not have
any boundaries to commit fraud. In this study, grey area is dened as susceptible areas or
elements of nancial statements which index value is greater than the bench mark index
of banish model. Financial ratios, statistical model, mathematical model, data mining
techniques, etc., are generally used to detect the nancial statement fraud. Detection of
fraud could be considered as a primary task of fraud investigation process, but it is not
enough and there is a long way to go to prevent it. A predictive diagnosis of manipulation
is simply needed to identify the real problem, then it would be easier to prevent
fraudulent nancial reporting activities. Financial statement fraud usually involves ve
schemes:
(1) ctitious revenue schemes;
(2) improper timing schemes;
(3) understating liabilities schemes;
(4) improper disclosure schemes; and
(5) improper asset valuation schemes.
Diagnosis of each variable of the model can give us a direction about where the fraudulent
activities are actually being done (index-level manipulation). Comparing the level of
manipulation either over the years or across companies or countries is also an effective
measure to see the manipulation level across countries. A common measurement unit is
useful to compare the manipulation across companies or countries. Overall manipulation
Financial
statements of
listed
companies
657

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