信用危險을 反映한 最適 預金保險料의 推定에 關한 硏究

Abstract

예금보험제도는 다른 금융안전망에 비해 유인부합적이어서 시장친화적이라는 장점이 있으나 예금보험료라는 직접적인 비용을 부담해야 하고, 이 제도를 적용하는 과정에서 보험의 일반적인 역기능중 하나로서 도덕적 해이를 유발할 수 있다. 도덕적 해이를 방지하기 위한 대안으로서 부보금융회사의 개별 신용위험에 기초하여 예금보험료율을 차등화하는 방법이 제안되고 있다. 또한 예금보험기금의 무한적립에 따른 부작용을 해소하기 위해 신용위험에 기초한 목표기금제도가 제안되고 있다. 본 논문의 목적은 차등보험과 목표기금을 고려하여 은행과 상호저축은행의 개별 신용위험에 보다 민감한 최적 예금보험료율과 목표기금을 추정하는 것이다. 신용위험에 민감한 차등 예금보험료율은 개별은행과 상호저축은행에 대한 신용손실을 기준으로 하여야 하는데, 신용손실을 추정하기 위한 신용위험요소를 각각 다음과 같은 방법론으로 추정한다. 부도율은 대상금융회사의 대부분이 비상장사라는 현실을 감안하여 KMA 모형을 비상장기업으로 확장 적용한 최영수와 장욱 (2007)의 방법론을 사용하여 추정하고, 부도시손실율은 Jokivuolle and Peura (2003)의 방법론으로 내재부도시손실율을 추정하여 사용한다. 그리고 금융권역의 미예상손실을 추정하는 방법으로는 CreditMetrics (1997) 모형을 사용한다. 예금보험료를 추정하는 실증분석 대상은 은행과 저축은행을 대상으로 한다. 실증분석기간은 2003년부터 2009년까지 7년간 기간을 대상으로 한다. 신용위험의 추정은 다양한 분야에 활용될 수 있다. 국내 예금보험기금의 추정은 신용위험에 기반을 두고 이루어져야 할 것이다. 본 논문은 부보금융회사의 개별 신용위험에 기초하여 보다 신용위험에 민감한 예금보험료율을 추정하는 방법론을 제시한다. |Although deposit insurance system has a merit of being incentive-compatible and thus being market-friendly compared to other financial safety net participants, it charges direct costs to insured financial institutions in the form of premiums and can give rise to moral hazard, a common adverse effect of any insurance systems. As a measure to prevent such moral hazard, the risk-based premium system whereby the insurer applies different premium rates to different member institutions based on their respective credit risk levels has been suggested. In addition, the credit risk-based target fund system has also been suggested as a way to resolve side effects of accumulating deposit insurance fund without setting a ceiling. The purpose of this paper is to estimate the optimal deposit insurance premium rate and target fund ratio that are sensitive to the credit risk of individual member institutions. The methodologies used to estimate the risk-based premium rate and target fund ratio that are sensitive to credit risks are as follows: In order to estimate the credit loss of a financial institution, the methodology of Choi Young Su and Jang Wook (2007) which expanded the application of KMA model to unlisted companies to estimate the expected default frequency(EDF) was used. To estimate the expected loss given default(LGD), the methodology of Jokivuolle and Peura (2003) was used. Lastly, CreditMetrics(1997) model was used to estimate unexpected loss in the financial sector. The subjects of empirical analysis to estimate deposit insurance premiums are banks and mutual savings banks. The period of empirical analysis is 7 years from 2003 to 2009. The outcome of the empirical analysis is summarized as follows: Firstly, the result of EDF estimation of banks and mutual savings banks revealed that the average EDF of banks during the sample period was 3% which is a relatively high figure. This is attributed to the fact a few banks showed extremely high figures while most banks showed a low EDF of less than 1%, indicating a low probability of default. The average EDF of mutual savings banks during the sample period was on a similar level with domestic banks at 3%. However, the EDF of mutual savings banks shows an even distributed with little deviation compared to those of banks. Secondly, the result of LGD estimation of banks and mutual savings banks showed that the LGD of banks during the sample period was 32% which was higher than that of mutual savings banks at 24%. Thirdly, the result of EL calculation of banks and mutual savings banks by using the EDF, LGD, and EAD suggested that the EL of banks during the sample period was relatively low at 0.9% of insured deposits while the EL of mutual savings banks showed an even lower rate of 0.7% of insured deposits. Lastly, the credit Var, which will determine the target fund ratio for banks and mutual savings banks, was estimated using the CreditMetrics methodology(1997). The result showed that the amount of maximum probable loss of banks is 1.282% of insured deposits and the amount of maximum probable loss of mutual savings banks is 8.670% of insured deposits within the 99% confidence level. Estimation of credit risks can be utilized in various areas. Estimation of domestic deposit insurance fund should be based on the level of credit risks. This paper suggests a methodology for calculating deposit insurance premium rates that is more sensitive to credit risks since it is based on the credit risk portfolio of individual member financial institutions.