Detecting Indications of Financial Statement Fraud: a Hexagon Fraud Theory Approach
نویسندگان
چکیده
This study emphasizes on examining the fraud hexagon theory referring to signs of financial statements, which employs all manufacturing companies listed in IDX (Indonesia Stock Exchange). However, total selected sample are 153 industry. The categorized into indicated and not committing 2010-2018 period by applying Beneish M-Score. findings demonstrated that stability, targets, external pressures, nature industry, CEO duality can be applied predict statements. Meanwhile, personal needs, ineffective monitoring, quality auditors, auditor turnover, director marginal costs cannot indicate occurrence statement. conclude pressure, ego, opportunity significantly affect statement fraud. Future research suggested consider different proxies for fraudulent statements; hence, accuracy compared with this study. Moreover, adding other conspiracy such as bonuses received managers will beneficial.
منابع مشابه
Predicting financial statement fraud using fuzzy neural networks
Fraud is a common phenomenon in business, and according to Section 24 of the Iranian Auditing Standards, it is the fraudulent act of one or more managers, employees, or third parties to derive unfair advantage and any intentional or unlawful conduct. Financial statements are a means of transmitting confidential management information about the<br ...
متن کاملFinancial Statement Fraud Detection by Data Mining
-------------------------------------------------------------------ABSTRACT---------------------------------------------------------------------Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will ...
متن کاملDetecting Corporate Financial Fraud using Beneish M-Score Model
Detecting financial fraud is an important issue and ignoring this issue may cause financial and non-financial losses to individuals and organizations. The aim of this study is to test the ability of Beneish M-Score Model for detecting financial fraud among companies listed on Tehran stock exchange. The research sample consists of 137 companies listed on Tehran Stock Exchange for a period of 11 ...
متن کاملDetection of Financial Statement Fraud Using Evolutionary Algorithms
In this paper, a fuzzy rule-based classifier (FRBC) system was developed and used in two Evolutionary Algorithm Models to detect patterns of financial statement fraud and assess the effectiveness of a subset of SAS No. 99 red flag variables. Each FRBC was evolved by using Generic Algorithm(GA) and MARLEDA – a modern estimation of distribution algorithm (EDA) – and trained with a data collection...
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: Akrual
سال: 2021
ISSN: ['2502-6380', '2085-9643']
DOI: https://doi.org/10.26740/jaj.v13n1.p119-131