銀行風險監(jiān)管能力的工具(編輯修改稿)
2025-06-17 15:28 本頁面
【文章內容簡介】 rules and more on a close monitoring of banks’ risk exposures) opens up a new role for CRs. 向風險性監(jiān)管轉變的國際潮流使信用登記有了新作用。 ? Adequate credit risk databases for banks and bank supervisors are in fact a precondition for risk based regulation and supervision (together with adequate skills among bank supervisors, new effective monitoring procedures and sanctions). 向銀行和銀行監(jiān)管者提供的足夠的信貸信息數(shù)據(jù)實際上是風險性監(jiān)管的前提條件（還包括：監(jiān)管者一定的能力，新的有效監(jiān)控程序和 sanction)。 CR amp。 Risk Based Supervision 信用登記與風險性監(jiān)管 The ongoing debate about the desirable bank capital regulation approach offer a useful example of the role that CR data may play in the definition of a risk based regulation in emerging countries. CR data may in fact help to solve a: 一直以來關于理想的銀行資本監(jiān)管方法的討論為信用登記數(shù)據(jù)在新興國家對風險性監(jiān)管的定義方面所起的作用提供了有用的例子。信用登記數(shù)據(jù)實際上將有助于解決一下問題： ? measurement problem: quantifying the VaR for a banking system without using plex models。 ?測算問題：不使用復雜的模型而能確定銀行體系風險價值的大?。? ? policy problem: indicating how VaRs can be split among Capital and Loan Loss Reserves (an area where Basel 2 does not provide guidance). 政策問題：指出風險價值在資本和貸款損失準備之間是如何劃分的（新巴賽爾協(xié)議未涉及此問題） CR amp。 Bank Capital Regulation 信用登記與銀行資本金監(jiān)管 Recent research at the World Bank (Majnoni, Miller, Powell, 2021) shows that countries with CRs, may apply simple statistical techniques to: 世界銀行最近研究 (Majnoni, Miller, Powell, 2021)表明，實行信用登記的國家可能采用簡單的統(tǒng)計技巧進行如下操作： Visualize the distribution of Credit Losses and the VaR without incurring into model or estimation errors. 將信貸損失和風險價值的分布形象化，而無需使用模型或產(chǎn)生估計錯誤。 ? Split the VaR among Capital and LLR requirements. Selected results, presented in the following slides, show how accurate measures of the distribution of credit losses have been obtained from CR data with simple statistical procedures. 在資本和貸款損失準備要求之間劃分風險價值。接下來的幻燈片中我挑選了一些結果，它們表明了利用信用登記數(shù)據(jù)和簡單的統(tǒng)計程序，得到的信貸損失的分布是相當準確的。 CR amp。 Bank Capital Regulation 信用登記與銀行資本金監(jiān)管 Step 1: extract from the CR all the loans at time t and check how many have defaulted at t+12. 第一步：從信用登記中選出在 t時的所有貸款，然后檢查在 t+12時有多少起違約。 Example: default frequency on 70017 loans from a CR 例：某信用登記中 70017筆貸款的違約頻率 P a n e l A : F r e q u e n c y D i s t r i b u t i o n o f B a n k L o a n s S i z e0 . 0 00 . 1 00 . 2 00 . 3 00 . 4 00 . 5 00 . 6 02117132147162177
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