핵심위험지표(KRI)를 이용한 운영리스크관리 및 감독기법 연구

Abstract

Basel II의 도입으로, 은행들은 운영리스크 수준을 모니터링하고 계량화하는 기준을 수립하기 위하여 핵심위험지표(KRI : Key Risk Indicator)를 인식하고 수집 및 모니터링하기 시작하였다. 운영리스크 고급측정법(AMA)을 도입한 은행들이 사용하는 KRI의 개수가 100개가 넘어, 이렇게 많은 KRI로는 은행의 운영리스크 수준을 체계적이고 합리적으로 모니터링하고 관리하기에는 어려운 수준에까지 이르게 되었다. 또 KRI의 정의가 은행마다 서로 다르고, 수집 지표도 상이함에 따라, 감독당국 입장에서 은행들의 운영리스크 수준의 추이를 살피고 그 수준을 비교하는 것은 더욱 어려운 일이었다. 본 논문에서는 운영리스크 관리 및 감독의 도구로서 KRI를 활용한 운영리스크지수(Operational Risk Index : ORI)를 제안하고자 한다. 동 지수는 계량화가 어려운 개별 은행의 운영리스크 측정 및 관리에 사용될 수 있을 뿐 아니라 감독당국의 운영리스크 감독에도 효과적으로 사용될 수 있을 것이다. 동 지수의 실증분석에는 고급측정법 승인을 받거나 승인 심사 중인 6개 시중은행의 KRI 데이터를 사용하였다. 주요 KRI는 바젤위원회에서 제시한 운영손실사건 유형별로 2007∼2009년 대형은행 운영손실사건의 특징을 대변할 수 있는 30개의 KRI를 선별하였다. 내․ 외부 사취에 할당된 KRI는 13개, 집행․ 전달․ 처리절차 손실유형에는 10개, 고객․ 상품․ 영업실무에는 4개, 영업중단 및 시스템 장애 유형에는 2개, 고용관행 및 사업장 안전 유형에 1개를 할당하였다. 실증분석 결과, 리만브라더스 파산 이후 운영리스크 지수(ORI)는 하향 추세를 보이고 있으며, 특히 금융위기를 경험한 2009년 상반기 이후 시중은행들의 운영리스크 관리와 감독당국의 감독강화로 운영리스크지수가 하락함을 알 수 있었다. 또한, 운영리스크지수는 운영 손실사건에 6개월 선행하고, 회귀분석 결과 결정계수가 35%로 산출되어 설명력이 있음을 보여주었다. 한편, 개별 은행의 운영리스크지수는 은행의 포트폴리오 특성과 밀접한 관련이 높은 것으로 나타났다. |With the introduction of the Basel II framework, banks have begun to recognize, collect, and monitor Key Risk Indicators (KRIs) to monitor their operational risk levels and establish a standard for measuring banks’ operational risk level. However, those using the Advanced Measurement Approaches (AMA) for Operational Risk were using well over a hundred KRIs and the sheer size of KRIs limited the banks’ ability to exercise a simple monitoring of their operational risk level. Moreover, the different definitions of KRIs and the disparity in the type of indicators collected and used by banks made it difficult for the regulator to monitor the development of banks’ operational risks and perform a sector-wide comparison. The purpose of this paper is to propose a new Index of Key Risk Indicators for the regulator to effectively and systematically measure, manage, and supervise operational risks. To compute an index of KRIs, standards were established for a unified definition of KRIs, common KRIs selected that would be manageable, and data collected. As a result, thirty core KRIs of identical definitions were collected from six large Korean banks using the AMA model. The KRIs were collected to account for each type of operational risk categorized by Basel II, resulting in the allocation of 13 KRIs for Internal and External Fraud, 10 for Execution, Delivery, and Process Management, 4 for Clients, Products, and Business Practices, 2 for Business Disruption and System Failures, one for Employment Practices and Workplace Safety, and none for Damage to Physical Assets. The number of core KRIs assigned to each type of operational risk is intended to mimic the observed pattern of the actual operational losses experienced by large banks during the 2004～2009 periods. Our empirical analysis found an overall downward trend in the banking industry’s operational risk index (ORI) since the bankruptcy of Lehman Brothers. In particular, banks’ ORI fell after the first half of 2009 following their tightened management of operational risks and stronger supervision by the regulator. The empirical result also suggests that ORI lead actual operational loss events by six months, and a regression analysis produced a 35% coefficient of determination supporting the explanatory power of the model. Further, the operational risk index of individual banks was found to be closely associated with the banks’ portfolio characteristics.

Keywords: Advanced Measurement Approach (AMA); Basel II; Key Risk Indicators (KRI); Operational Risk; Operational Risk Types; With the introduction of the Basel II framework, banks have begun to recognize, collect, and monitor Key Risk Indicators (KRIs) to monitor their operational risk levels and establish a standard for measuring banks’ operational risk level. However, those using the Advanced Measurement Approaches (AMA) for Operational Risk were using well over a hundred KRIs and the sheer size of KRIs limited the banks’ ability to exercise a simple monitoring of their operational risk level. Moreover, the different definitions of KRIs and the disparity in the type of indicators collected and used by banks made it difficult for the regulator to monitor the development of banks’ operational risks and perform a sector-wide comparison. The purpose of this paper is to propose a new Index of Key Risk Indicators for the regulator to effectively and systematically measure, manage, and supervise operational risks. To compute an index of KRIs, standards were established for a unified definition of KRIs, common KRIs selected that would be manageable, and data collected. As a result, thirty core KRIs of identical definitions were collected from six large Korean banks using the AMA model. The KRIs were collected to account for each type of operational risk categorized by Basel II, resulting in the allocation of 13 KRIs for Internal and External Fraud, 10 for Execution, Delivery, and Process Management, 4 for Clients, Products, and Business Practices, 2 for Business Disruption and System Failures, one for Employment Practices and Workplace Safety, and none for Damage to Physical Assets. The number of core KRIs assigned to each type of operational risk is intended to mimic the observed pattern of the actual operational losses experienced by large banks during the 2004～2009 periods. Our empirical analysis found an overall downward trend in the banking industry’s operational risk index (ORI) since the bankruptcy of Lehman Brothers. In particular, banks’ ORI fell after the first half of 2009 following their tightened management of operational risks and stronger supervision by the regulator. The empirical result also suggests that ORI lead actual operational loss events by six months, and a regression analysis produced a 35% coefficient of determination supporting the explanatory power of the model. Further, the operational risk index of individual banks was found to be closely associated with the banks’ portfolio characteristics.

Keywords: Advanced Measurement Approach (AMA)