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    IMF Paper Examines Approaches for Surveillance of Cyber Risk

    February 10, 2020

    IMF published a paper that offers a range of analytical approaches for the surveillance of cyber risk in the financial sector. The paper describes analytical approaches, including tools and data sources, for monitoring and analyzing cyber risk, including various approaches to stress testing. These approaches are key indicators that can be collected and tracked through time, event studies, value-at-risk, custom surveys, structured presentation via a cyber risk assessment matrix, and financial-cyber network maps. The paper illustrates these analytical approaches by applying them to Singapore, with the appendix to the paper providing example templates for data collection. The paper argues that, even in the absence of cyber-event data, the models estimated in other contexts can be applied regularly in a given jurisdiction.

    Cyber risk is an emerging source of systemic risk in the financial sector and possibly a macro-critical risk too. It is poses a growing threat to financial stability; therefore, public agencies will need to do more to better understand and assess its financial stability implications. As an advanced economy with a complex financial system and rapid adoption of fintech, Singapore serves as a good case study. The quantitative results of the Singapore analyses and descriptions of the public and private-sector cyber-security initiatives in Singapore, should provide a reference for surveillance work. These approaches can serve as a checklist for those with responsibility for surveillance of cyber resilience and for other jurisdictions seeking to improve their institutional arrangements. The paper concludes by presenting directions for future work.

    The value-at-risk of 4.7% of the gross revenues consumes a significant amount of the capital budget for operational risk. BCBS recommended capital requirements for operational risk of about 11% of gross income for banks with gross income up to EUR 1 billion, which is intended to cover unexpected loss from many sources besides cyber risk and possibly at a higher level of confidence than 95%. This suggests that for these banks, even just the 95th percentile of cyber risk consumes about two-fifth of the capital budget for operational risk over one year. However, many questions still remain. For example, further work needs to estimate the size of systemic risk from cyber-attacks to the financial sector. The paper also states that MAS conducts stress tests and industry-wide exercises for financial institutions to assess their resilience to cyber threats from two complementary perspectives. While the focus of stress tests is on the adequacy of capital and liquidity buffers to weather the impact of cyber-attacks, industry-wide exercises test their business continuity and crisis management plans to respond and recover from cyber-attacks. 

    The assessment in the paper finds that limited data availability is a key challenge in assessing and monitoring cyber risk. Except where regulations require it, financial institutions are reluctant to disclose cyber-security incidents, given the potential regulatory or legal sanctions. Data may also become obsolete quickly, given the rapid pace of change in the information technology sector. Despite these challenges, the paper finds that some data and methods are readily available to analyze cyber risk. Key indicators can be collected and tracked, event studies can be conducted, survey estimates can be requested, statistical models estimated in other contexts can be applied in data-poor environments, and quantitative results can be presented in a standardized format. This quantitative work complements more qualitative ongoing work on cyber risk surveillance approaches and policy frameworks for the financial sector.

    Additionally, the paper points out that the financial-cyber network map is a recent idea that has yet to be applied in practice. When such data become available, specialized contagion risk models may need to be developed to analyze such data. For example, contagion could be modeled over a two-layer network, where one layer represents the financial links and the other layer represents the information and communications technology links. Similarly, concentration analysis for outsourcing arrangements has been described. In applications, such analysis needs to distinguish between concentration risk and the desirable concentration that arises when many financial institutions use the same reputable third-party providers.


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    Keywords: Asia Pacific, Singapore, Banking, Insurance, Securities, Cyber Risk, Systemic Risk, Operational Risk, Data, Stress Testing, Concentration Risk, Outsourcing Risk, IMF

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