DOI QR코드

DOI QR Code

Development of the Financial Account Pre-screening System for Corporate Credit Evaluation

분식 적발을 위한 재무이상치 분석시스템 개발

  • Received : 2009.09.23
  • Accepted : 2009.10.14
  • Published : 2009.12.01

Abstract

Although financial information is a great influence upon determining of the group which use them, detection of management fraud and earning manipulation is a difficult task using normal audit procedures and corporate credit evaluation processes, due to the shortage of knowledge concerning the characteristics of management fraud, and the limitation of time and cost. These limitations suggest the need of systemic process for !he effective risk of earning manipulation for credit evaluators, external auditors, financial analysts, and regulators. Moot researches on management fraud have examined how various characteristics of the company's management features affect the occurrence of corporate fraud. This study examines financial characteristics of companies engaged in fraudulent financial reporting and suggests a model and system for detecting GAAP violations to improve reliability of accounting information and transparency of their management. Since the detection of management fraud has limited proven theory, this study used the detecting method of outlier(upper, and lower bound) financial ratio, as a real-field application. The strength of outlier detecting method is its use of easiness and understandability. In the suggested model, 14 variables of the 7 useful variable categories among the 76 financial ratio variables are examined through the distribution analysis as possible indicators of fraudulent financial statements accounts. The developed model from these variables show a 80.82% of hit ratio for the holdout sample. This model was developed as a financial outlier detecting system for a financial institution. External auditors, financial analysts, regulators, and other users of financial statements might use this model to pre-screen potential earnings manipulators in the credit evaluation system. Especially, this model will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings and to improve the quality of financial statements.

Keywords

Earning Manipulation;Management Fraud Detection;Financial Account Pre-screening;Corporate Credit Rating;Financial Ratio Analysis

References

  1. 이명곤, 이화득, "회계실패의 원인과 해결 방안," 회계저널, 제13권, 제2호, 2004, pp. 181-224.
  2. 고종권, 윤성수, "이익조작지수를 이용한 회계부정 적발," 회계와 감사연구, 제43호, 2006, pp. 219-244.
  3. 김문철, 황문호, "분식회계기업의 적발," 회계저널, 제16권, 제3호, 2007, pp. 1-34.
  4. 김정애, "기업지배구조가 회계부정에 미치는 영향," 회계와 감사연구, 제45호, 2007, pp. 297-324.
  5. 노준화, 배길수, "회계실패사례 분석 및 회계실패 방지를 위한 개선방안: 경영환경, 회계환경, 감사환경 및 감리환경을 중심으로," 회계저널, 제13권, 제2호, 2004, pp. 155-180.
  6. 노태협, 유명환, 한인구, "러프집합이론과 사례기반추론을 결합한 기업신용평가모형," 정보시스템연구, 제14권, 제1호, 2005, pp. 41-65.
  7. 박종성, "피감사회사 특성과 감사인 특성을 이용한 감리지적 예측," 회계학연구, 제24권, 제1호, 1999, pp. 1-32.
  8. 신택수, 홍태호, "부도확률맵과 AHP를 이용한 기업 신용등급 산출모형의 개발," 정보시스템연구, 제16권, 제3호, 2007, pp. 1-20. https://doi.org/10.1057/palgrave.ejis.3000668
  9. 윤중옥, 김명환, "감리지적기업의 회계특성에 관한 연구 -감리비지적기업과 비교를 중심으로," 회계연구, 제6권, 제2호, 2001, pp. 45-60.
  10. 이주민, 김승연, 하은호, 노태협, "AHP 모형을 활용한 소상공인 신용평가시스템 구축," 정보시스템연구, 제16권, 제3호, 2007, pp. 109-132.
  11. 이천현, "분식회계 실태와 효율적 제제방안," 형사정책, 제16권, 제1호, 2004, pp. 197-236.
  12. 전성빈, 김영일, "도산예측모형의 예측력 검증," 회계저널, 제10권, 제1호, 2001, pp.151-182.
  13. 최관, 박종일, 조현우, "이사회 및 감사위원회의 특성과 회계부정 간의 관계에 관한 실증분석," 회계와 감사연구, 제48호, 2008, pp. 351-389.
  14. 최관, 백원선, "감리지적기업의 이익조작에 관한 실증적 연구," 회계학연구, 제23권, 제2호, 1998, pp. 133-161.
  15. 최관, 최국현, "회계부정기업의 특성에 대한 연구: 감리지적기업을 중심으로," 회계학연구, 제28권, 제2호, 2003, pp. 211-243.
  16. 최재화, 최순재, "신경망기법을 이용한 경영자사기 위험성 측정에 관한 연구", 경영학연구, 제26권, 제1호, 1997, pp. 17-36.
  17. Altman E. I., "Financial Ratios, Discriminant Analysis and the Prediction on Corporate Bankruptcy," Journal of Finance, Vol. 23, No. 4, 1968, pp. 589-609. https://doi.org/10.2307/2978933
  18. Beneish, M. D., "The Detection of Earnings Manipulation," Financial Analysis Journal, Vol.55(September/October), 1999, pp. 24-36. https://doi.org/10.2469/faj.v55.n5.2296
  19. Beneish. M. D., "Detecting GAAP Violation: Implication for Assessing Earnings Management among Firms with Extreme Financial Performance," Journal of Accounting and Public Policy, Vol. 16(Fall), 1997, pp. 271-309. https://doi.org/10.1016/S0278-4254(97)00023-9
  20. Deshmuah, A. and Talluru, L., "A Rule-Based Fuzzy Reasoning System for Assessing the Risk of Management Fraud," International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 7, No. 4, 1998, pp.223-242. https://doi.org/10.1002/(SICI)1099-1174(199812)7:4<223::AID-ISAF158>3.0.CO;2-I
  21. Elliot, R. and Willingham, J., Management Fraud: Detection and Deterrence, Petrocelli, New York, 1980.
  22. Fanning, K. and Cogger, K., "Neural Network Detection of Management Fraud Using Published Financial Data," International Journal of Intelligent Systems in Accounting, Finance & Management, Vol. 7, No. 4, 1998, pp.21-41. https://doi.org/10.1002/(SICI)1099-1174(199803)7:1<21::AID-ISAF138>3.0.CO;2-K
  23. Han, I., Chandler, J., and Liang, T., "The Impact of Measurement Scale and Correlation Structure on Classification Performance of Inductive Learning and Statistical Methods," Expert Systems with Application, Vol. 10, No. 2, 1996, pp. 209-221. https://doi.org/10.1016/0957-4174(95)00047-X
  24. Karim, K. E. and Siegel, P. H., "A Signal Detection Theory Approach to Analyzing the Efficiency and Effectiveness of Auditing to Detect Management Fraud," Managerial Auditing Journal, Vol. 13, No. 6, 1998, pp. 367-375. https://doi.org/10.1108/02686909810222384

Acknowledgement

Supported by : 덕성여자대학교