기업의 조세부정예측모형에 관한 연구 (A Study on Tax Fraud Prediction Model of Listed Firms)

서지정보

· 발행기관 : 한국회계학회
· 수록지 정보 : 회계저널 / 25권 / 3호 / 445 ~ 484페이지
· 저자명 : 박현재, 김갑순

초록

본 연구는 국내 기업의 회계자료 및 기업특성을 이용하여 조세부정 정도를 추정하는 모형을 제시하고, 예측모형의 구체적인 활용방안을 설명하였다. 구체적으로, 2000년부터 2013년까지 세무조사로 적발되어 전자공시시스템(DART)에 공시한 12월 결산 상장법인과 대응표본을 대상으로 100회 무작위추출에 의한 단계적 로짓분석(stepwise logistic regression)을 실시하여 조세부정 예측모형을 추정하였다.
최종 예측모형에는 유효세율, 부채비율, 수출비율, 매출액, 회계이익과 과세소득의 차이, 재벌여부, 감사인 규모의 7개 변수가 포함되었다. 분석결과, 국내 상장기업들은 유효세율, 부채비율, 매출액이 높을수록 조세부정 가능성이 높았으며, 반면 수출비율, 회계이익과 과세소득의 차이가 낮을수록 조세부정 가능성이 높은 것으로 나타났다. 또한 재벌에 소속되어 있으며 외부감사인이 Non-Big4인 경우에 조세부정 가능성이 높았다. 본 연구의 예측모형은 모든 기업을 비부정기업으로 가정하는 단순전략과 비교하여 총기대오류비용을 크게 감소시킬 수 있는 것으로 나타나 비용효율적임을 제시하였다.
재무제표와 기업특성 자료만을 필요로 하는 본 연구의 예측모형은 과세당국, 학계, 외부감사인, 투자자들이 특정 기업의 조세부정 가능성을 일차적으로 평가하는데 유용할 것으로 기대된다.

영어초록

Tax fraud affects the national budget to reduce the tax revenues of the country. Lisowsky(2010) is, U.S. Treasury(1999) with reference to the report, it reported that tax revenues that the federal government will be lost in the tax evasion has reached 10 billion dollars a year. In Korea, there is a trend that is collected additionally the number of tax audits and the amounts collected additionally associated with increased offshore tax evasion annually. Domestic and foreign tax authorities are making various efforts to prevent such these tax fraud. U.S. Internal Revenue Service(IRS) in 2000 to tax fraud transactions(tax shelter) dedicated to agencies(the Office of Tax Shelter Analysis, OTSA) established by the tax fraud monitoring and there. Even concluded in the domestic Foreign Account Tax Compliance Act(FATCA) from September 2015 agreed to strengthen offshore tax evasion blocked by the U.S. Internal Revenue Service(IRS) through the financial information exchange.
Many studies theoretically explain and empirically analyze relevance of between of corporate tax burden level, financial characteristics, corporate governance, book to tax income differences and tax avoidance. In addition, previous studies related to tax evasion has focused to analyze the differences between the various properties compared to the corporate tax fraud caught by the companies. However, can be utilized in practice, decisions regarding models and tax evasion about to estimate the extent of tax evasion of specific companies, remains a substantial portion unsolved problem.
In this study, while presenting a predictive model that can determine whether to tax fraud, the specific manner of utilization of the model is trying to explore. In particular, an attempt to estimate a more sophisticated predictive models, comprehensive consideration tax avoidance and financial characteristics that it has been confirmed that affect the tax evasion, ownership and governance structure characteristics, the external auditor of the properties are in the previous research did. Specifically, the effective tax rate, company size, profitability, ratio of assets investment, debt ratio, export ratio, sales, financial constraints, discretionary accruals, research and development expenses, of the difference between profit and taxable income on eleven numbers of financial characteristic variables, ownership interest rate, foreign interest rates, jaebul, whether three of ownership and characteristic variables of the governance structure, the auditor scale of one of the external auditor of the characteristic variables to the consideration stepwise logistic regression was utilized to derive the final predictive model. In order to eliminate the estimated arbitrariness of the estimation model, 50 percent of the entire sample to predict the estimation sample in the random sampling method, and the remaining 50 percent and holdout samples. Further, in order to solve one of the reliability issues due to random sampling, 100 times and randomly, and extracted the available variables in predictive model. By using the validation sample in order to verify the suitability of the estimated prediction model, to derive the tax fraud probability of tax fraud corporate and non-fraud corporate, tax fraud probability of tax fraud company has verified whether significantly higher. Further, we is trying to verification of the economic efficiency of tax fraud estimation model by comparing the total expected cost when using the predictive model or not by the methodology of Beneish(1997), Ko and Yoon(2006). This study develops a model to detect tax fraud using a sample of firms identified as tax fraud by the Financial Supervisory Service of Korea and characteristics of corporate for the period from 2000 to 2013. We find seven useful variables: tax expense/pretax book income(ETR); debt/total asset(LEV); export proceeds/total sales(EXPORT); log(total sales)(SALES); book-tax difference/total asset(BTD); jaebul(GROUP); auditor size(BIG4). Results suggest that Korean firms are more likely to manipulate taxable income when ETR, LEV, SALES are more larger and EXPORT, BTD are more smaller and these firms are GROUP and audited by Non-Big4. Compared with a naive strategy of classifying all firms as non-manipulators, our estimation model is expected to significantly reduce costs of misclassification.
Tax regulator, academic, external auditors, investor, and other users of financial statements might use our model to screen potential tax fraud, to which they can allocate additional resources for more in-depth analysis.

참고자료

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