AU  - Schüler,Timm
AU  - Supervisor:Balcıoğlu, Hasret 
TI  - Avoidance and detection of financial statement fraud in non-listed enterprises
PY  - 2015///
CY  - Nicosia
PB  - Cyprus International University
KW  - İşletme
KW  - Business administration department
N1  - Includes references(245-255 p.); 1; SCOPE AND OBJECTIVES; 1; OBJECTIVES OF THIS THESIS; 2; METHODOLOGY; 3; STRUCTURE OF THE THESIS; 5; BASIC PRINCIPLES OF FINANCIAL STATEMENT FRAUD; 5; FUNDAMENTALS OF FINANCIAL STATEMENT FRAUD; 5; Definition of Financial Statements Fraud; 7; Consequences of Financial Statement Fraud for Affected Companies; 10; Systematization of the Fraud -Risk; 13; FUNDAMENTALS AND ECONOMIC RELEVANCE OF NON-LISTED ENTERPRISES; 16; INSTITUTIONAL ENVIRONMENT OF NON-LISTED ENTERPRISES  IN GERMANY; 16; GENERAL INSTITUTIONAL FACTORS IN GERMANY; 19; ECONOMIC AND POLITICAL ENVIRONMENT; 20; LEGAL ENVIRONMENT; 25; CONTROL ENVIRONMENT OF NON-LISTED  ENTERPRISES IN GERMANY; 25; RESPONSIBILITY OF THE MANAGEMENT; 25; General responsibility of the Management; 26; Prevention of Financial Statement Fraud by Corporate Compliance; 31; CORPORATE  CODE OF CONDUCTS; 37; DETECTION OF FINANCIAL STATEMENT FRAUD BY INTERNAL CONTROL INSTITUTIONS; 41; RESPONSIBILITIES OF FINANCIAL STATEMENT AUDITORS; 48; STATEMENT OF THE EMPIRICAL RESEARCH; 48; FINANCIAL STATEMENT FRAUD RISK ASSESSMENT WITH DECISION SUPPORT; 48; Pincus (1989): Comparison between risk assessment of financial statement Fraud with and without decision support; 49; Boatsma/Moeckel/Pei (1997): Study concerning the influence of the consequences of a decision on the use of computer-aided decision support; 50; Eining/Jones/Loebbecke (1997): Comparison between different systems for risk assessment of Financial statement fraud; 51; RELEVANCE OF FRAUD TRIANGLE FOR FINANCIAL STATEMENT FRAUD RISK ASSESSMENT; 51; Heimann-Hoffman/Morgan/Patton (1996): Relative weighting of red flags in assessment of Financial statement Frauds; 51; Wilks/Zimbelman (2004): Application of the Fraud Triangle in practice; 53; ALTERNATIVES OF RED FLAG FRAUD RISK ASSESSMENT; 53; Gillets/Uddin (2005): "Reasoned action model " for risk assessment of Financial statement fraud; 54; STUDIES ON THE IDENTIFICATION OF RED FLAGS FOR RISK ASSESSMENT OF FINANCIAL STATEMENT; 54; Romney/Albrecht/ Cherrington (1980): Risk Factors of the three variables attitude/ rationalization, opportunities and incentive on the basis of a field investigation; 54; Albrecht/Romney (1986) : Verification of identified red flags of the study of Romney/Albrecht/Cherrington (1980); 55; Loebbecke/Willingham (1988): Examination how often the red flags of SAS No.53, a previous version of SAS No.99 (redrafted), occurred in 71 cases of financial fraud obtained from the SEC's AAERs from 1960 to 1980; 56; Loebbecke/Eining/Willigham (1989): Survey among partners of an audit firm to gather general experience concerning major financial statement fraud and the presence of the red flags; 57; Campbell/Parker (1992): Identification of 415 AAERs published by the SEC From 1972 to 1989 due to financial statement  fraud; 57; Hackenbrack (1993): Situation based increased risk of financial statement fraud; 58; Dechow/Sloan/Sweeney (1996): Examination of AAERs in order to identify red flags; 59; Weisenborn/Norris (1997): Analysis  whether the 87 red flags from the study by Alberecht/ Romney (1986) could be observed in cases of financial statement fraud; 59; Beasley/Carcello/Hermanson/Lapides (2000): Examination of factors from the field of corporate governance are adequate tools to assess the risk of financial statement fraud; 60; Majid/Gul/Tsui (2001): Applicability of Loebbecke/Eining/Willingham (1989) red flags in Hong Kong; 61; Terlinde (2005):Avoidance and detection of financial statement fraud in German public auditor practice; 62; Moyes/Lin/Landry (2006/2005): Suitability of the red flags listed in SAS No. 99 for risk assessment of Financial statement fraud; 63; Brazel/Jones /Zimbelman (2006): Non-Financial measurements for financial statement fraud detection; 63; Hernández/Groot (2007): Examination of attitudes of corporate managers causing auditors to assess the risk of financial statement fraud as high; 64; STUDIES ON THE CREATION OF MODELS/DECISION SUPPORT FOR RISK ASSESSMENT OF FINANCIAL STATEMENT FRAUD; 64; Bell/Szykowny/Willingham (1991): Logit model for risk assessment of Financial statement of Financial statement fraud; 65; Persons(1995):  Logit model for risk assessment of Financial statement of Financial statement fraud; 66; Fanning/Cogger/Srivastava (1995): Artificial Neural Networks (ANNs) for risk assessment of financial statement fraud; 67; Hansen/Mc Donald/Messier/Bell (1996): "Generalized qualitative response model" for risk assessment of Financial; 68; Green/Choi (1997): ANN for risk assessment of financial statement fraud concerning revenue and accounts receivable; 69; Beneish (1997): Probit model to differentiate between aggressive accruers and GAAAP violators; 70; Deshmukh/Talluru  (1998): " Rule-based fuzzy reasoning system" (rule-based fuzzy decision support) for risk assessment of financial statement fraud; 70; Summers/Sweeney (1998): Logit model for the risk assessment of financial statement fraud  based on insider trading information and financial ratios; 71; Fanning/Cogger (1998):Several classical and modern mathematical models for risk assessment of financial statement fraud; 72; Lee/Ingram/Howard(1999): Logit model for risk assessment of Financial statements fraud; 74; Bell/Carcello (2000): Logit model for risk assessment of financial statement fraud; 74; Apostolou/Hassell/Webber (2000): Decision model for risk assessment of financial statement frauds; 75; Apostolou/Hassell/Webber (20001): Advanced decision model for risk assessment of financial statement fraud; 76; Spathis/Doumpos/Zopounidis (2002): "Multi Criteria Decision Aid" Model for risk assessment of financial statement fraud; 77; Lin/Hwang/Becker (2003 ): Fuzzy Neural Network (FNN) for risk assessment of financial statement fraud; 78; Kaminski/Wetzel/Guan (2004): Discriminant function for risk assessment of financial statement fraud; 80; COMPOSITION AND ACCOMPLISHMENT OF THE EMPIRICAL STUDY IN GERMANY REGARDING FIANCIAL STATEMENT FRAUD IN NON-LISTED ENTERPRISES; 80; REPRESENTATIVE OF THE SURVEY; 81; ABOUT THE REPORTING PERSON; 87; GENERAL EXPERIENCED WITH FINANCIAL STATEMENT FRAUD IN NON-LISTED ENTERPRISES; 93; DETAILS ABOUT INDIVIDUAL FINANCIAL FRAUD CASES; 110; RED FLAGS IDENTIFIED IN FINANCIAL STATEMENT FRAUD CASES; 116; DETAILS RESEARCH QUESTIONS AND PROPOSITIONS; 197; CLUSTER ANALYSIS; 197; FINANCIAL STATEMENT FRAUD SCHEMES CLUSTERED; 236; RESULTS OF THE EMPIRICAL STUDY; 242; LIMITATION OF THE STUDY AND FUTURE AREAS OF RESEARCH; 243; COMPARISON OF THE RESULTS WITH INTERNATIONAL RESEARCH STUDIES; 245; REFERENCES
N2  - 'ABSTRACT Given the current state of the economy and recent corporate scandals, financial statement fraud is still a top concern for enterprise executives and shareholders. In fact, the German regulations, designed to prevent and detect financial statement fraud, have exposed fraudulent practices that previously may have not been detected. No industry is immune to fraudulent financial statements and the corresponding negative publicity. The pertinent literature especially focusses on listed companies regarding the prevention and the detection methods. Nevertheless, there are other institutional corporate structures besides the listed entities with significant incentives for the commitment of financial statement fraud. Non-listed enterprises in Germany are either not or just to a limited extent subject to an institutional control environment. Considering the impact of a lacking regulatory compliance mechanism like the external audit, this would imply that nonlisted enterprises are able to provide falsified financial information to economic stakeholders in an easier way in comparison to listed companies. Currently, the attention to those corporate structures is appreciably limited. As a result, the thesis will investigate the major institutional impacts, incentives as well as prevention and detection instruments for financial statement fraud by non-listed enterprises. In order to understand the different incentives for financial statement fraud in the German institutional environment and the corresponding prevention and detection instruments in different types of non-listed enterprises a survey will be performed with German fraud experts that are confronted with financial statement fraud in everyday working life. Survey participants provide comprehensive details about financial statement fraud cases that they observed in the past. A hierarchical cluster analysis is carried out with the scientific objective to discover how similar and different the fraud schemes are to one another in terms of the surveyed red flags. Key words: Financial statement fraud, Germany, non-listed enterprises'
ER  -