Supervisory Policy Manual CA-B-3: Countercyclical Capital Buffer Geographic Allocation of Private Sector Credit Exposures

Our Ref : B9/128C B1/15C B1/21C 25 September 2015 The Chief Executive All locally incorporated authorized institutions Dear Sir / Madam, Supervisory Policy Manual (SPM) CA-B-3 “Countercyclical Capital Buffer (CCyB) – Geographic Allocation of Private Sector Credit Exposures” I am writing to inform you that, following consultation with the two industry Associations, the Monetary Authority (“MA”) is issuing the above SPM module today as a statutory guideline by notice in the Gazette under section 7(3) of the Banking Ordinance. The Banking (Capital) Rules (BCR) (as amended by the Banking (Capital) (Amendment) Rules 2014) provide for regulatory capital requirements in respect of the CCyB. An earlier SPM module (CA-B-1 “Countercyclical Capital Buffer (CCyB) – Approach to its Implementation”) explains the MA’s approach towards implementing the CCyB as part of the capital adequacy framework for Authorized Institutions (AIs) incorporated in Hong Kong. The SPM module CA-B-3 issued today provides further guidance to AIs on how to determine the geographic allocation of private sector credit exposures for the purposes of calculating their “AI￾specific CCyB ratio” under the BCR. As set out in section 3O(1) of the BCR and explained in Section 2 of SPM CA-B-1, an AI must determine its own specific CCyB rate as the weighted average of the applicable jurisdictional CCyB rates in respect of jurisdictions (including Hong Kong) where the AI has private sector credit exposures. The weight to be attributed to a given jurisdiction’s applicable CCyB rate is calculated by reference to the ratio of the AI’s aggregate risk-weighted amount for its non-bank private sector credit exposures in a jurisdiction (RWAj) to the sum of the AI’s RWAj across all jurisdictions in which the AI has private sector credit exposure.

2 The new module sets out the MA’s expectations on how an AI should allocate its non-bank private sector credit exposures, and the corresponding risk-weighted amount (RWA), to different jurisdictions on an ultimate risk basis (as required under section 3O(2) of the BCR), in order to determine RWAj for the AI’s non-bank private sector credit exposures in each jurisdiction. The module covers:

1. Determining RWAj. As described in Section 2.1 of the module, for each jurisdiction, RWAj is the sum of two components as follows:  Banking book and trading book exposures for which RWA for credit risk is calculated under the BCR (Section 2.2 of the module). As a general approach (see para. 2.2.1 of the module), an AI should first determine the geographic location of its banking book and trading book non-bank private sector credit exposures for which credit risk RWA is calculated under the BCR by identifying in which jurisdiction the obligor(s) corresponding to each exposure is/are located (if possible on an ultimate risk basis – see para. 2 below). For each identified jurisdiction, the AI should then aggregate the RWA of all non-bank private sector credit exposures whose obligors are located in that jurisdiction. Special cases which include exposures to “pools” of underlying exposures which are located in multiple jurisdictions (i.e. collective investment schemes, securitisation exposures, pools of retail exposures under IRB) and specialised lending are dealt with in para. 2.2.2 of the module.  Trading book exposures for which a market risk capital charge for specific risk is calculated under BCR Part 8 (Section 2.3 of the module). An AI should first identify in which jurisdiction the obligor(s) is/are located (if possible on an ultimate risk basis – see para. 2 below) in respect of the AI’s interest rate exposures (non-securitization and securitization) and equity exposures which are subject to a market risk capital charge for specific risk. The AI should then apply a different procedure for the purposes of allocating the RWA for specific risk to the various jurisdictions concerned, depending on whether the AI calculates a market risk RWA based on the standardized (market risk) approach (STM approach) or on the internal models approach (IMM approach).
2. Ultimate risk basis. As mentioned above, an AI is expected to identify the geographic location of its obligors, where possible, on an “ultimate risk basis”. This means allocating exposures to the jurisdiction where the risk ultimately lies (i.e. where the “ultimate obligor” resides). Section 3 of the module provides guidance on how to apply this principle. On-line access to the SPM module CA-B-3 is available to AIs under the icon for “Supervisory Policy Manual” on the HKMA’s public (http://www.hkma.gov.hk) and private (http://www.stet.iclnet.hk) websites.

3 Should you have any questions regarding the enclosed module, please feel free to contact Mr Noel Sacasa (njsacasa@hkma.gov.hk) or Ms Carita Wan (carita_pm_wan@hkma.gov.hk). Yours faithfully, Karen Kemp Executive Director (Banking Policy) Encl. c.c. The Chairman, The Hong Kong Association of Banks The Chairman, The DTC Association FSTB (Attn. Mr Jackie Liu)