Includes CD

Includes references(245-255 p.)

'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'

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