Sound Practices for Stress-testing and Liquidity Risk Management

Our Ref: B1/15C
4 August 2011
The Chief Executive
All authorized institutions
Dear Sir/Madam,
Benchmarking: Stress-testing Practices and Liquidity Risk Management The Hong Kong Monetary Authority (“HKMA”) recently completed a benchmarking exercise on (i) the stress-testing practices and (ii) the liquidity risk management of selected authorized institutions (“AIs”). The aim was to assess the effectiveness of AIs’ risk management practices in these two areas and to identify sound practices which it would be helpful to share with the industry. While the majority of the AIs covered in the benchmarking exercise have put in place reasonable policies and procedures to guide their stress-testing and liquidity risk management activities and operations, deficiencies were noted in some areas where stronger governance, stricter control processes, more prudent business assumptions, and greater discipline in respect of the taking of risk-mitigating actions, would ensure the more effective implementation of the relevant policies and procedures. In this regard, Annex 1 and Annex 2 set out some observed sound practices in relation to stress-testing and liquidity risk management respectively for your reference. Please note that the benchmarking exercise was focused on the practical aspects of the effective implementation of risk management techniques and control procedures adopted by the industry. AIs should in parallel take steps to achieve compliance with the recommendations set out in the relevant chapters of the HKMA’s Supervisory Policy Manual 1 and those made by the Basel Committee on Banking Supervision (BCBS) 2 . ....../2

LM-1 (Liquidity Risk Management); LM-2 (Sound Systems and Controls for Liquidity Risk Management); IC-5 (Stress-testing) Principles for Sound Stress Testing Practices and Supervision (May 2009)

Should you have any questions on the above, please feel free to approach your usual supervisory contact at the HKMA. Yours faithfully, Karen Kemp Executive Director (Banking Policy) Encl.

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Annex 1 - Sound Practices for Stress-testing

Annex 1 – Sound Practices for Stress-testing
Governance

1. Dedicated committees are assigned to manage the overall stress-testing
   programme with clear mandates to (i) design stress-testing scenarios that suit the institution’s risk profile, (ii) review stress-testing outputs from an enterprise-wide perspective and in the context of the prevailing macro market environment, (iii) recommend necessary risk monitoring and mitigating measures, and (iv) provide independent views and advice to senior management and the Board of Directors. The committees typically include senior representatives from risk management, treasury, front office, and research departments. With a balanced representation, the committees can ensure that the opinions of all relevant parties are heard and all potential issues thoroughly deliberated.
2. Mechanisms are in place to encourage the taking of specific actions to
   address the potential risks signalled by stress-testing outputs. (For example “de-risking” of trading book or banking book positions following a breach of stress-testing triggers set by a committee with responsibility for managing all or part of the stress-testing programme. Other possible courses of action include, but are not limited to, reducing the relevant market and credit risk limits and establishing medium-to-long term risk mitigation plans.) Moreover, adequate compliance reviews are in place to ensure that stress-testing outputs that exceed the institution’s risk appetite (see paragraph 8 below) must be addressed and cannot be dismissed by management as implausible and thereby delay necessary de-risking or risk-mitigation action. Stress-testing approach
3. In addition to commonly adopted stress-testing approaches such as
   sensitivity tests, an enterprise-wide and scenario-based approach is employed. Under this approach, stress scenarios are applied consistently across all business units within the AI, and all of its subsidiaries in the case of group-wide stress- testing, to generate consistent and coherent outputs for the entire enterprise. The outputs should provide a comprehensive view across the credit, market, interest rate and liquidity risks of the AI on a consolidated basis.
4. Forward-looking stress scenarios are developed based on observed or
   projected macro financial environments that are remote but plausible (e.g. the bursting of asset bubbles in the property, stock, or commodity markets). These scenarios take into consideration an AI’s exposures, e.g. exposures to specific countries or industries in the case of country or industry specific stress scenarios. For instance, an AI with significant cross-border claims on a particular country should construct stress-testing scenarios specific to

that country (e.g. negative GDP shock, credit crunch). The remote but plausible scenarios should assist in the identification of the AI’s vulnerabilities and the need for mitigating measures.
5. Reverse stress-testing techniques are being developed and incorporated into
AIs’ stress-testing programmes. In reverse stress-testing, an AI identifies scenarios and circumstances that would render its business model unviable. This is different from scenario based stress-testing which tests for outcomes arising from changes in circumstances. The vulnerabilities identified from reverse stress-testing should be reviewed and addressed by the senior management team.
6. In addition to quantitative measures, “expert judgement” is used when
developing stress scenarios. By incorporating the use of expert judgement, the AI can mitigate the risks arising from the rigid adoption of quantitative measures (e.g. estimated probabilities of stress events), especially in view of recent observations that statistical relationships used to derive probabilities tend to break down in stressed conditions. The design of stress parameters should take into account the inherently pro-cyclical nature of the financial markets. In times of strong economic growth, elevated asset prices or rapid credit expansion, more severe stress parameters are usually adopted.
7. Tailor-made stress-testing scenarios are constructed for specific assets,
liabilities, or hedging strategies to which an AI is heavily exposed. An example is the stress-testing of unexpectedly large credit spread movements affecting complex structured credit products, taking into consideration the correlation relationship as implied by different structured products and the basis risk, or incomplete hedge, of existing hedging strategies.
8. Risk tolerance levels are defined in different terms to give management
different perspectives of the nature of stress impact. For instance, stress-testing results can be expressed in terms of their impact on an AI’s capital adequacy ratio, common equity, leverage ratio, risk weighted assets, and annual profit and loss. Stress-testing readiness
9. Control procedures are established to ensure that the stress-testing database,
models, and outputs are flexible and reliable. For example, if computer programmes or calculation models are used to generate stress-testing outputs, proper control procedures such as user acceptance test and version control, together with periodic validity checks on data sources and on the reasonableness of the output, should be in place.
10. Stress-testing infrastructure, including the database, models and application
tools, is designed to be flexible enough to execute ad hoc stress-testing on short notice. Data on risk positions should be coherently defined and

categorised with sufficient granularity to facilitate flexible aggregation and grouping of risks. This will enable an AI to construct tailor-made stress scenarios relatively swiftly based on observable signs of stress conditions (e.g. the recent European sovereign debt problem). Procedures for retrieval and aggregation of position data are also clearly documented and regularly tested. The ability to generate stress-testing results within a short period of time allows senior management to formulate critical mitigation plans, which could prove to be crucial in times of crisis.

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Annex 2 - Sound Practices for Liquidity Risk Management

Annex 2 – Sound Practices for Liquidity Risk Management
Governance

1. The Board of Directors determines and articulates the “liquidity risk tolerance”
   for the AI both qualitatively and quantitatively. For the latter, various types of limits including liquidity ratio limits, cash-flow mismatch limits under both normal and stressed conditions, concentration limits on the holdings of liquid assets, as well as concentration limits on funding sources are established. The limits are further supported by clearly documented assumptions or methodologies for the quantification of factors such as behavioural maturity and contingent liquidity commitments (more details in paragraph 5).
2. Liquidity costs are allocated to business lines according to their respective risk
   taking activities so that business incentives are aligned with the AI’s liquidity risk tolerance. Liquidity cost is calculated based on the cost of maintaining high quality liquid assets and raising longer tenor funds. The possibility of substantial increases in the cost of maintaining adequate liquidity during stressed environments is fully taken into account by drawing reference to past financial crises, including the global financial crisis of 2008. Liquidity costs are allocated to the products, commitments, and risk positions of the AI based on their terms (behavioural patterns are considered when contractual terms are hard to determine, for example, due to optionality). Liquidity costs are applied to both on- and off-balance sheet items, including undrawn commitments. Risk identification, measurement, monitoring and control
3. Net cash-flow mismatches along different time horizons are measured:
   day-by-day for the near term (e.g. up to the seventh business day) to ensure management has a clear picture of the most imminent funding needs, and by time buckets for the medium to long term. Limits (in amount and/or in ratio, with the latter supplemented by a specified minimum amount or “floor” for short tenor limits) are applied to day-by-day cash-flow mismatches for the near term and also on a cumulative basis (e.g. net cash inflows should exceed HK$50 million or 3% of gross cash outflows for each of the first 3 days, and positive cumulative cash-flow for the first 7 business days. 1 ).
4. Cash-flows are monitored by individual currency when AIs’ exposures to FX
   liquidity risk in respect of that currency are significant. Quantitative criteria are established to define “significant exposures”. These tools enable prudent monitoring of cash-flow mismatch and mitigate the risk that foreign exchange swap markets may become dysfunctional during crises, thus impairing an AI’s ability to switch surplus liquid assets denominated in one currency into the currencies required.

The example provided is for illustration purposes only. AIs with different funding models may adopt different limit structures.

5. The behavioural and contractual assumptions applied in cash-flow projections
   to each applicable asset, liability and off-balance sheet item are properly documented. Assumptions used in cash-flow projections are back-tested on a periodic basis and the results are presented to senior management or risk management committees for review.
6. Effective management information systems are put in place to enable the timely
   generation of accurate cash-flow analysis and other liquidity risk management reports, both on a regular basis and upon the request of users (e.g. the senior management and the regulators). Specifically, detailed information including cash-flow analysis under normal and stressful conditions, analysis of deposit run-offs, the amount and distribution of high quality assets that can be liquidated under different degrees of market liquidity squeeze, the amount of assets eligible for obtaining lender of last resort (LOLR) support, and the projection of regulatory ratios under different scenarios, etc. should be made available expeditiously when needed.
7. Regular basic qualitative review of the AI’s resilience to liquidity squeezes is
   conducted, including reviewing, and when necessary testing, the AI’s ability to access the wholesale funding markets, its eligibility to obtain LOLR support from the HKMA, and the readiness of its shareholder controllers, or its head office in the case of AIs incorporated overseas, to provide liquidity support in case of need. Intraday liquidity risk management
8. Review is undertaken of intra-day liquidity reports generated at various
   predefined times throughout the day to assess cash-flows needs and the adequacy of the AI’s intraday liquidity resources (e.g. securities available for intra-day repo).
9. The respective levels of intra-day liquidity needs, during both normal and
   stressed market conditions, are regularly reassessed, taking into account potential outflows that may arise from each of the AI’s trading positions (e.g. collateral posting, highly leveraged trades whose cash flows vary significantly with market conditions) and business commitments (e.g. corresponding banking services). This review is sometimes included as part of the AI’s stress-testing and scenario analysis (see paragraph 10). Stress-testing and scenario analysis
10. The impact of significant cash outflows under market-wide and institution
    specific stress scenarios is analyzed. Different assumptions are tailored for each scenario. For instance, stress assumptions on second round effects including failure to receive expected cash inflows due to the default of interbank counterparties and unexpected requests for the posting of additional

collateral as a consequence of market illiquidity (and/or volatility) are considered in the market-wide scenarios but not necessarily in the institution specific scenarios.
11. Reasonable assumptions are applied with respect to key parameters based on
relevant market and/or institutional experience. For instance, deposits are classified according to customer behaviour: corporate deposits are in general more sensitive to market changes than retail deposits and therefore a higher run-off rate is assumed. A similar rationale applies to other characteristics such as non-connected versus connected deposits, non-pledged versus pledged deposits, etc. Management is made responsible for reviewing and approving the assumptions periodically.
12. The cash inflows expected to be generated from the sale of liquid assets are
fairly incorporated by applying prudent assumptions on factors including (i) the haircuts expected as a result of the fire-sale of the assets, (ii) the time expected to be required for disposing of the assets in an orderly manner, and (iii) the time lag between the settlement date and the trade date of the assets in question.
13. Regular reporting of stress-testing results to the senior management is required.
Limit excesses in stress-testing are formalised as one of the triggers for the AI’s contingency funding plan. Maintenance of liquidity cushion
14. A reasonable amount of liquidity cushion is maintained by setting floor limits
on the holding of very high quality liquid assets which the management believe would remain liquefiable even under very stressful scenarios (an example of high quality liquid assets includes government paper issued by countries with high sovereign credit ratings). The list of high quality liquid assets is subject to periodic review and approval by the senior management. The floor limits are set at a level sufficient to cover the imminent cash outflows anticipated in stressful scenarios. Contingency funding plan
15. Detailed and prescriptive policies and procedures on a contingency funding
plan (CFP) are maintained and comprehensive assessment on the feasibility of the CFP conducted, drawing on experiences in respect of stresses on markets and/or institutional liquidity during past financial crises. Both qualitative and quantitative early warning indicators are employed to determine different levels of remedial action including the triggering of the CFP. The CFP is tested periodically, including but not limited to the ability to conduct timely cash-flow analysis and the readiness of unencumbered assets which can be disposed of swiftly to generate liquidity. The clarity and effectiveness of the escalation procedures is also tested through regular drills.