The Role of Pentagon Fraud in Detecting Fraudulent Financial Statements
نویسندگان
چکیده
Pentagon fraud is one type of financial that occurs in companies. when a company hides or deceives statements to reduce the amount taxes it must withhold increase value for investors report. The purpose this study was examine and analyze effect pentagon variable on statement with dependent proxy being F-Scores. While independent variables used are stability (ACHANGE), target (ROA), nature industry (RECEIVABLE), ineffective monitoring (BDOUT), change auditor (CPA), directors (DCHANGE), frequent number CEO's picture (CEOPIC). This research use samples consumption sector companies listed Indonesia Stock Exchange (IDX) period 2016–2020. By using purposive sampling, there 55 from 11 data analysis method multiple linear regression analysis, hypothesis testing t-test, f-test, descriptive test, coefficient determination. results shows stability, monitoring, auditor, direction have no significant influence statements. But target, industry, statement.
منابع مشابه
A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements
Financial statement fraud has increasingly become a serious problem for business, government, and investors. In fact, this threatens the reliability of capital markets, corporate heads, and even the audit profession. Auditors in particular face their apparent inability to detect large-scale fraud, and there are various ways to identify this problem. In order to identify this problem, the majori...
متن کاملThe Role of Imputation in Detecting Fraudulent Financial Reporting
Financial fraud detection plays a crucial role in the stability of institutions and the economy at large. Data mining methods have been used to detect/flag cases of fraud due to a large amount of data and possible concept drift. In the financial statement fraud detection domain, instances containing missing values are usually discarded from experiments and this may lead to a loss of crucial inf...
متن کاملForecasting Fraudulent Financial Statements using Data Mining
This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms in the recent period 2...
متن کاملThe Detection of Fraudulent Financial Statements: an Integrated Language Model
Among the growing number of Chinese companies that went public overseas, many have been detected and alleged as conducting financial fraud by market research firms or U.S. Securities and Exchange Commission (SEC). Then investors lost money and even confidence to all overseas-listed Chinese companies. Likewise, these companies suffered serious stock sank or were even delisted from the stock exch...
متن کاملData Mining techniques for the detection of fraudulent financial statements
This paper explores the effectiveness of Data Mining (DM) classification techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. In accomplishing the task of management fraud detection, auditors could be facilitated in their work by using Data Mining techniques. This study investigates the usefulness of Decis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Golden Ratio Of Finance Management
سال: 2022
ISSN: ['2776-6780']
DOI: https://doi.org/10.52970/grfm.v2i2.185