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A Intelligent Diagnostic Model that base on Case-Based Reasoning according to Korea - International Financial Reporting Standards

K-IFRS에 따른 사례기반추론에 기반한 지능형 기업 진단 모형

  • 이형용 (한성대학교 사회과학대학 경영학부)
  • Received : 2014.11.12
  • Accepted : 2014.11.26
  • Published : 2014.12.30

Abstract

The adoption of International Financial Reporting Standards (IFRS) is the one of important issues in the recent accounting research because the change from local GAAP (Generally Accepted Accounting Principles) to IFRS has a substantial effect on accounting information. Over 100 countries including Australia, China, Canada and the European Union member countries adopt IFRS (International Financial Reporting Standards) for financial reporting purposes, and several more including the United States and Japan are considering the adoption of IFRS (International Financial Reporting Standards). In Korea, 61 firms voluntarily adopted Korean International Financial Reporting Standard (K-IFRS) in 2009 and 2010 and all listed firms mandatorily adopted K-IFRS (Korea-International Financial Reporting Standards) in 2011. The adoption of IFRS is expected to increase financial statement comparability, improve corporate transparency, increase the quality of financial reporting, and hence, provide benefits to investors This study investigates whether recognized accounts receivable discounting (AR discounting) under Korean International Financial Reporting Standard (K-IFRS) is more value relevant than disclosed AR discounting under Korean Generally Accepted Accounting Principles (K-GAAP). Because more rigorous standards are applied to the derecognition of AR discounting under K-IFRS(Korea-International Financial Reporting Standards), most AR discounting is recognized as a short term debt instead of being disclosed as a contingent liability unless all risks and rewards are transferred. In this research, I try to figure out industrial responses to the changes in accounting rules for the treatment of accounts receivable toward more strict standards in the recognition of sales which occurs with the adoption of Korea International Financial Reporting Standard. This study examines whether accounting information is more value-relevant, especially information on accounts receivable discounting (hereinafter, AR discounting) is value-relevant under K-IFRS (Korea-International Financial Reporting Standards). First, note that AR discounting involves the transfer of financial assets. Under Korean Generally Accepted Accounting Principles (K-GAAP), when firms discount AR to banks before the AR maturity, firms conventionally remove AR from the balance-sheet and report losses from AR discounting and disclose and explain the transactions in the footnotes. Under K-IFRS (Korea-International Financial Reporting Standards), however, most firms keep AR and add a short-term debt as same as discounted AR. This process increases the firms' leverage ratio and raises the concern to the firms about investors' reactions to worsening capital structures. Investors may experience the change in perceived risk of the firm. In the study sample, the average of AR discounting is 75.3 billion won (maximum 3.6 trillion won and minimum 18 million won), which is, on average 7.0% of assets (maximum 38.6% and minimum 0.002%), 26.2% of firms' accounts receivable (maximum 92.5% and minimum 0.003%) and 13.5% of total liabilities (maximum 69.5% and minimum 0.004%). After the adoption of K-IFRS (Korea-International Financial Reporting Standards), total liabilities increase by 13%p on average (maximum 103%p and minimum 0.004%p) attributable to AR discounting. The leverage ratio (total liabilities/total assets) increases by an average 2.4%p (maximum 16%p and minimum 0.001%p) and debt-to-equity ratio increases by average 14.6%p (maximum 134%p and minimum 0.006%) attributable to the recognition of AR discounting as a short-term debt. The structure of debts and equities of the companies engaging in factoring transactions are likely to be affected in the changes of accounting rule. I suggest that the changes in accounting provisions subsequent to Korea International Financial Reporting Standard adoption caused significant influence on the structure of firm's asset and liabilities. Due to this changes, the treatment of account receivable discounting have become critical. This paper proposes an intelligent diagnostic system for estimating negative impact on stock value with self-organizing maps and case based reasoning. To validate the usefulness of this proposed model, real data was analyzed. In order to get the significance of this proposed model, several models were compared to the research model. I found out that this proposed model provides satisfactory results with compared models.

최근 재무제표분석을 통하여서 기업을 진단하려고 하는 다양한 학문적인 연구와 실질적인 적용이 실행되고 있다. 특히, 최근 새롭게 변경된 회계기준인 한국채택 국제회계기준(K-IFRS: Korea - International Financial Reporting Standards)에 따라서 제무제표분석에도 변화가 발생하고, 그에 따라서 기업 진단도 새롭게 변화되어야 하는 상황이 되었다. 이에 현재, 금융권에서도 관심을 갖고 있는 매출채권 처리의 변화에 따라서 발생하는 재무제표상의 진단 및 분석을 반영하여서 처리하는 새로운 진단모형의 필요성이 대두되었다. 특히, 최근 모뉴엘이라는 기업의 매출채권을 이용한 금융스캔들의 영향으로 이러한 연구가 더욱 활발하게 진행되고 있다. 매출채권은 일반적 상거래에서 발생하는 신용채권 으로서, 기업이 만기까지 보유하거나 만기 전에 양도가 가능한 금융 상품이다. 기업이 매출 채권을 할인하여 양도할 경우에 매출채권 할인을 매각거래로 처리하고, 할인료에 해당하는 금액을 매출채권처분 손실로 처리하며, 해당 거래를 우발 채무로 공시하였다. 그러나, K-IFRS 하에서는 모든 위험과 보상이 이전되지 않는 한 매출채권 할인을 차입거래로 인식한다. 이는 기업 부채의 증가로 기업가치에 영향을 미치게 된다, 이 논문에서는 매출채권 할인이 실질적으로 기업가치에 부정적인 영향을 미치는지 추정하는 지능형진단시스템을 제안한다. 본 논문에서는 매출채권 할인이 주가에 미치는 영향을 인공지능기법인 사례기반추론(case based reasoning)과 자기조직화지도 (self-organizing maps)기법을 통하여 진단 모형을 구축하였다.

Keywords

References

  1. Aamodt, A. and E. Plaza, "Case-based reasoning;Foundational issues, methodological variations, and system approaches," AI Communications, Vol.7, No.1(1994), 39-59.
  2. Ahn, H., K.-j. Kim, and I. Han, "Simultaneous optimization model of case - based reasoning for effective customer relationship management," Journal of Intelligence and Information Systems, Vol.11, No.2(2005), 175-195.
  3. Chun, S.-H. and Y.-J. Park, "A new hybrid data mining technique using a regression case based reasoning: Application to financial forecasting," Expert Systems with Applications, Vol.31, No.2(2006), 329-336. https://doi.org/10.1016/j.eswa.2005.09.053
  4. Hwang, Y.,"A Hybrid Forecasting Framework based on Case-based Reasoning and Artificial Neural Network," Journal of Intelligence and Information Systems, Vol.18, No.4(2012), 43-57.
  5. Kim, K.-j. and H. Ahn, "Development of web-based Intelligent recommender systems using advanced datamining techniques," Journal of Information Technology Applications & Management, Vol.12, No.3(2005), 42-56.
  6. Kim, J. A. and J. S. Choi, "A case study on the accounting for the assignment of account receivable under K-IFRS in export financing," Korean Accounting Journal, Vol. 23, No.2(2014), 317-343.
  7. Lee, H., K. Kim, and W.-S. Beak, Accounting Principles, Shinyoungsa, 2011.
  8. Lee, H.-Y., "A recommendation model that combines self-organizing maps and case-based reasoning: a case of online community recommender systems," The e-Business Studies, Vol.9, No.1(2008), 309-327. https://doi.org/10.15719/geba.9.1.200803.309
  9. Lee, I. H. and K.-s. Shin, "A Study on Forecasting Accuracy Improvement of Case Based Reasoning Approach Using Fuzzy Relation," Journal of Intelligence and Information Systems, Vol. 16, No. 4(2010), 67-84.
  10. Korea Accounting Standards Board, Korea - International Reporting Standards, 2011.
  11. Korea Accounting Standards Board, Major differences between Korea - Generally Accepted Accounting Principles and Korea - International Reporting Standards, 2011.
  12. Park, J., "Value Relevance of Accounts Receivable Discounting and Its Impact on Financing Strategy under K-IFRS," Ph.D. Dissertation, Dept. of Management Engineering, Korea Advanced Institute of Science and Technology, 2014.
  13. Petersohn, H., "Assessment of clusteranalysis and self-organizing maps," International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol.6, No.2(1998), 139-149. https://doi.org/10.1142/S0218488598000124
  14. Burke, R., "The wasabi personal shopper: A casebased recommender system," Proceedings of the 11th International Conference on Innovative Applications of Artificial Intelligence, (1999), 844-849.
  15. Stahl, A. and R. Bergmann, "Applying recursive CBR for the customization of structured products in an electronic shop," Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning, Lecture Notes in Computer Science, Vol.1898(2000), 297-308.
  16. Kohonen, T., "Self-organized formation of topologically correct feature maps," Biological Cybernetics, Vol.43, No.1(1982), 59-69. https://doi.org/10.1007/BF00337288
  17. Van Setten, M., M. Veenstra, A. Nijholt, and B. van Dijk, "Case-based reasoning as a prediction strategy for hybrid recommender systems," Proceedings of the Second International Atlantic Web Intelligence Conference, Lecture Notes in Computer Science, Vol.3034(2004), 13-22.