巴賽爾銀行監理委員會(BCBS)於2010年9月所公布的第三版巴賽爾資本協定(Basel III)中,首度將流動性風險由原本的Basel II第二支柱納入第一支柱作量化管理,其中針對橫跨銀行資產面與負債面的資金流動性建立兩個最低的監理準則,「流動性覆蓋率」(Liquidity Coverage Ratio, LCR)與「淨穩定資金比率」(Net Stable Funding Ratio, NSFR)被要求高於100%,BCBS並明文要求各國從2012年開始觀察Basel III流動性風險管理措施的可行性與影響。本文以BCBS於2010年12月公布之流動性風險監理架構為基礎,整理蒐集我國4家公股行庫、4家民營銀行及1家外商銀行共9家銀行的資產負債表等相關公開資訊,用以建置前述比率,期能提供監理機關作為施政參考。 Basel III之流動性風險架構係針對個別銀行作「個體審慎衡量」,未針對整體金融系統風險作「總體審慎衡量」,因此,本文參考鍾經樊(2011)之考量信用風險、銀行間傳染風險與流動性風險的金融系統風險量化模型,以4家公股行庫、3家民營銀行共7家樣本銀行來衡量本國銀行的系統風險損失分配,並調整相關模型參數─存款提領比率、銀行倒閉門檻及流動性風險損失門檻作銀行損失的情境分析。 結果顯示9家本國銀行的流動性覆蓋率及淨穩定資金比率均高於100%,但彼此差異甚明顯,代表本國銀行儘管皆以存貸為主要業務,但彼此所採取之經營策略不盡相同。此外,在系統風險量化模型之實際計算結果顯示若該銀行之淨穩定資金比率越低,越可能發生流動性風險損失;若該銀行之流動性覆蓋率越低,則會大幅提升倒閉的可能,反之,代表該銀行越穩健,越能在規模如2008年金融海嘯的壓力情境中繼續經營。
In the Basel III Accord issued by the Basel Committee on Banking Supervision (BCBS) in 2010, banks’ liquidity risk management is included into Pillar I from Pillar II and is subject to quantitative supervision thereafter. The Committee has developed two minimum liquidity standards, which are Liquidity Coverage Ratio (LCR) and Net Stable Funding Ratio (NSFR). Based on the Basel III framework for liquidity risk measurement, we attempt to get the two liquidity standards for 9 Taiwanese systemically important banks via public information. Even though the Basel III Accord has implemented the so-called microprudential regulation to measure liquidity risk for every individual bank, to some extent, it neglects the macroprudential measures. Hence, we make references to Chung (2011) attempting to build up a systemic risk model with credit risk, interbank contagion risk and liquidity risk involved altogether. By modifying several parameters such as deposits’ run-off rates and banks’ insolvency hurdle rates, we make the scenario analysis of multi-risk losses for 7 Taiwanese domestic banks. The empirical assessment shows that while the LCRs and NSFRs meet the supervisory requirements, or higher than 100%, for the 9 sample banks, they differ a lot with each other. Notwithstanding comparable business among banks, their operating strategies really differ. In addition, we find out that the higher the banks’ NSFRs are, the less likely they are to suffer from liquidity loss. Similarly, the higher the banks’ LCRs are, the more resilient they will be to survive the stressed events such as 2008 financial crisis. Under our reasonable assumptions, the scenario analysis helps to evaluate the financial health for the 7 sample banks and understand how the loss distribution and the VaRs change taking credit risk, interbank contagion risk and liquidity risk into account.