Guidance · HKMA · 20 Jan 2025
Authorized Institutions must prioritize operational resilience tasks, track progress via self-assessments, and achieve full OR-2 compliance by May 2026. They must ensure Board and senior management oversight by embedding resilience into strategic planning and risk management. Major AIs must define trigger events to update vulnerability maps for emerging risks. All AIs are encouraged to apply good practices for mapping, testing, and remediation commensurate with their scale and risk profiles. Regular reporting on implementation progress and periodic reporting of all vulnerabilities to risk committees and governance parties are required.
55th Floor, Two International Finance Centre, 香 港 中 環 金 融 街 8 號 國 際 金 融 中 心 2 期 55 樓 8 Finance Street, Central, Hong Kong 網 址:www.hkma.gov.hk Website: www.hkma.gov.hk Our Ref.: B1/15C 20 January 2025 The Chief Executive All Authorized Institutions Dear Sir/Madam, Sharing of good industry practices for implementing operational resilience framework I am writing to share observations of good industry practices for conducting mapping exercises and scenario testing to support implementation of operational resilience framework in accordance with Supervisory Policy Manual (SPM) module OR-2 . Through ongoing engagement with the industry to track implementation progress, the HKMA noted that all Authorized Institutions (AIs) have developed operational resilience frameworks and are on track to achieve full compliance with the OR-2 requirements by May 2026. Major retail banks have also taken on board our supervisory feedback to tighten the tolerance limits for disruption, thus enhancing resilience and recovery capability for critical operations that are important to the AI, its customers and the banking sector. Most AIs are now in the second critical stage of their operational resilience implementation, namely the mapping and scenario testing exercises. These exercises enable AIs to identify vulnerabilities and dependencies of each critical operation, thereby facilitating effective remediation. The HKMA acknowledges the challenges involved given the increasing complexity of banking operations, which were discussed at an industry sharing session co-hosted by the HKMA and the Hong Kong Association of Banks (HKAB) in December 2024. …/page 2 1 The SPM module OR-2 on Operational Resilience was issued on 31 May 2022.
Insights from the sharing session and good industry practices observed through various engagements are summarised in the Annex. AIs are encouraged to consider applying the good practices for mapping, testing and remediation of relevant vulnerabilities, in a manner commensurate with the scale and scope of their operations and risk profiles. Going forward, AIs should prioritise the remaining tasks for becoming operationally resilient and track progress through self-assessments, with a view to achieving full compliance with the OR-2 requirements by May 2026. The HKMA will continue to provide guidance and support to the industry in the process. Should your institution have any questions on the above, please contact us at operational.resilience@hkma.iclnet.hk. Yours faithfully, Carmen Chu Executive Director (Banking Supervision) c.c The Chairperson, The Hong Kong Association of Banks The Chairperson, The DTC Association FSTB (Attn: Ms Tanna Chong)
Annex
Good practices for mapping interdependencies and scenario testing This annex summarises a set of good practices for mapping interdependencies and scenario testing noted by the HKMA over the course of its supervision of AIs’ implementation of their operational resilience frameworks. A. Governance
dependencies in defining the end-to-end critical operations. Decision points for continuing the business-as-usual paths and triggering alternative paths for contingency are identified. Interdependencies of the critical operation with any upstream and downstream systems, as well as communication and data exchange between relevant parties, are also captured. These enable the identification of all supporting assets (people, processes, technology, information, facilities, and interconnections and interdependencies) necessary for the delivery of a critical operation.
3. Adopt appropriate tools to construct a comprehensive map
Major AIs utilise the information in their existing risk management frameworks, such as business impact assessments (BIAs), risk and control assessments, IT service chain map, network diagrams and inventory of thirdparty service providers, to capture the known critical supporting assets in the map. Some AIs have also developed a template or guidance note to set out the procedures required for the delivery of critical operation, supporting staff and their functions, physical sites and their alternate locations, system owners, system hosting locations, and recovery time objectives. These details serve as a basis for the development of a comprehensive map and identification of dependencies, ensuring comprehensive coverage of supporting assets in the map.
4. Identify vulnerabilities taking a risk-based approach in the end-to-end map
Based on the preliminary map constructed, critical operation owners would conduct an end-to-end review to identify points that are susceptible to disruption or single point of failure. This is achieved through analysing the data and process flows, conducting technology resilience reviews or by analysing real-life disruptions. It also involves examining the potential impact of different third-parties’ failure to a critical operation. Additionally, some AIs consider emerging risks by assessing the impact of large-scale global incidents on different types of critical operation, and whether similar supporting assets within the critical operation are prone to disruptions, thereby enabling the identification of vulnerabilities in a forward looking manner.
for disruption might be breached, so as to overcome the constraints hindering recovery. Given that it is not possible to test all severe but plausible scenarios for all critical operations at once, major AIs have developed a systematic test plan that takes into account emerging risks and impacts of vulnerabilities. Vulnerabilities that impact multiple critical operations are given the highest priorities. This enables the proper prioritisation and sequencing of the various tests, while ensuring appropriate coverage of each critical operation under each severe but plausible scenario. For instance, some AIs repeatedly tested payment operations due to prior disruptions in these operations, while others prioritised testing of critical operations involving third parties, considering the rising instances of major disruptions caused by third parties.
8. Adopt an outcome-based testing approach
Once the test objectives are established, many AIs would determine the most suitable type of testing, considering the distinct objectives served by different types of tests. To assess whether a critical operation can be delivered within the tolerance for disruption, major AIs adopted various types of tests in isolation or in combination, including scenario tests (e.g. ransomware attack, third-party disruption, system failure), business continuity tests, simulation exercises (e.g. core banking system migration impacting multiple critical operations), and disaster recovery tests (e.g. loss of data centre). Some of them utilise a paper-based format to facilitate more thorough validation of recovery procedures and their operability, while others employ a table-top format, which enables the testing of real-time responses from relevant parties within a condensed timeframe.
9. Design dynamic and stressful testing scenarios to simulate potential disruptions
In designing a testing scenario, some major AIs would increase the severity of disruption over time with a view to testing the AI’s tolerance limit and identifying vulnerabilities under stressed situations. Some AIs also developed a storyline to simulate the different stages of a real-life disruption (e.g. limited information on the outage of a critical third-party service provider initially, followed by more updates on the root cause and impacts at a later stage). Substorylines are also included to illustrate the need to involve relevant stakeholders as the disruption starts to impact more lines of business (e.g. IT
team fixes payment processing system slowness, while the payment team initiates manual operation as the issue persists). Furthermore, more mature AIs would combine multiple severe but plausible scenarios to create even more stressful assumptions, such as concurrent disruptions from multiple sources impacting the same critical operation. 10.Engage appropriate stakeholders (including third parties and intragroup arrangements) in the testing exercise Some AIs involve the senior management of their external system vendors in planning and conducting the testing exercise on whether the vendors’ tolerance limit is within the AIs’ tolerance level in respect of a particular critical operation. Some AIs engage their intragroup functions to ensure that the intragroup arrangements are effective in supporting the continuous delivery of critical operations. AIs that face challenges in engaging third parties in scenario testing have adopted alternative approaches to assess third-party resilience, such as reviewing their resilience plans and testing outcomes. Where such information is limited or unavailable, the AIs concerned would assume that the third party did not meet their resilience requirements, identify this as a gap, and review whether substitutes or workarounds are available. 11.Evaluate testing results to identify areas for improvement and refine testing approach to enhance effectiveness Major AIs evaluate their testing results and continually refine their testing approach to more effectively uncover potential vulnerabilities. This process involves a thorough evaluation of testing results, carefully examining the underlying assumptions to identify gaps and weaknesses. For example, some AIs have refined their testing approach or adjusted their assumptions, such as transitioning from a paper-based to a table-top exercise, or performing live system tests from weekends to weekdays. Some AIs retested the scenarios to track improvements over their vulnerabilities. D. Remediation of vulnerabilities 12.Manage vulnerabilities for remediation Major AIs have made progress in remediating vulnerabilities identified ahead of 31 May 2026. This is achieved by assessing the impact of vulnerabilities on single or multiple critical operations and making prioritisation accordingly.
Additionally, some AIs classify vulnerabilities in different tiers to formulate a suitable remedial strategy, seek appropriate funding and continuously track remediation progress. Some AIs established dashboards to track different types of vulnerabilities and remediation, as well as introducing heat maps to track operational resilience posture. This involves recording whether each critical operation could remain within the defined tolerance for disruption under each severe but plausible scenario. Taking into account any vulnerabilities being addressed throughout a period, the dashboards and heat maps are also updated to reflect the latest remediation status and operational resilience posture. Periodic reporting of all vulnerabilities is made to risk committees and other governance parties. 13.Derive suitable remediation strategy Major AIs have formulated suitable strategies in line with the type and nature of vulnerabilities identified. For instance, AIs remediated their technologyrelated vulnerabilities by tightening recovery timeframes, enhancing requirements for technology-related tests, and acquiring additional recovery capacity. In other cases, AIs with data-related vulnerabilities revisited the recovery timeframe for their Secure Tertiary Data Backup (STDB) to ensure it is within the tolerances for disruption. Meanwhile, certain AIs with processrelated vulnerabilities have enhanced their manual processes by refining the scenario-based response and recovery plans to support the delivery of critical operations.
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