An Approach to Quantifying Operational Resilience Concepts, Accessible Data

Figure 1. LISCC Firms and Reported Key FMU Relationships

This figure depicts a network map of the eight LISCC banks and the FMU connections they reported in their public Resolution Plans. The network map contains 60 unique FMUs clustered in a network around the eight LISCC banks. Most of the FMUs are interconnected with multiple banks, and some of the banks are connected with each other. Filled circles are banks, and empty circles are FMUs.

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Figure 2. LISCC Firms and Reported Key Payment FMUs: Links Thickened by Estimated Volume

This figure depicts a network map of the eight LISCC banks and the payment system FMU connections they reported in the public Resolution Plans. This network map is much smaller than the one depicted in Figure 1, and contains four unique payment FMUs clustered in a network around the eight LISCC banks. All of the FMUs are interconnected with multiple banks. None of the banks are connected with each other in this network, because this type of interbank connection was not reported in their Resolution Plans. The lines linking the banks and the FMUs are thickened according to an estimate of how much payments activity is being supported by each connection. Filled circles are banks, and empty circles are FMUs.

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Figure 3. Disruption Scenarios

This figure depicts the same network map shown in Figure 2. However, in this image, the network map depicts four different “disruption scenarios” in which banks’ access to some or all of the depicted payment FMUs in the network is hypothetically cut off. In Disruption Scenario 1, the firms’ connections with the Fedwire Funds Service are disrupted. The figure illustrates impact size (determined by line thickness) from this disruption varying by firm. In Scenario 2, the banks’ connections with both critical USD same day payment channel, CHIPS and Fedwire, are impacted. In Scenario 3, the disruption is expanded to include both same day payment channels and the FedACH system. In Scenario 4, the most severe scenario, the disruption impacts firms’ ability to interact with any of the key reported USD payment system FMUs. The image uses filled circles to depict a disrupted node and empty circles to indicate a node that has not been disrupted.

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Figure 4. Event Severity and Total Disruption Size

Figure 4 depicts the disruption size resulting from each scenario depicted in Figure 3. The x-axis indicates the event severity (i.e. the events depicted in Figure 3) and the y-axis indicates the total disruption to the network in dollars. The figure shows three upward sloping curve lines. The figure illustrates increasing event severity resulting in an increasingly large disruption. Different dashed lines indicate scenarios in which different levels of pre-event mitigation are employed. Increasing levels of mitigation results in lower levels of disruption, shifting the disruption curve downward. With no mitigation, the estimated disruption from the most severe scenario was approximately 1.4 trillion USD.

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Figure 5. Event Severity and Resilience of System

Figure 5 depicts the overall level of resilience in the model resulting from each scenario. The x-axis indicates the event severity (i.e. the events depicted in Figure 3) and the y-axis indicates the total resilience of the network in percentage of dollars. The figure shows three downward sloping curve lines. The figure illustrates increasing event severity resulting in less resilience. Different dashed lines indicate scenarios in which different levels of pre-event mitigation are employed. Increasing levels of mitigation results in higher levels of resilience, shifting the disruption curve upward. With no mitigation, the estimated disruption from the most severe scenario resulted in a resilience level of roughly 50%.

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Figure 6. Time Variant Model of Actual Expected Resilience

Figure 6 provides an illustration of resilience over a theoretical window of time for which the disruption event continues. The x-axis indicates time measured in hours, and the y-axis indicates the total resilience of the network in percentage of dollars. The figure shows a line indicating a fall in resilience to approximately 50% as the disruption event begins, and an increase in resilience to approximately 75% after hour 14, indicating a partial recovery. The curve shown in Figure 6 could be duplicated for the various levels of disruption and mitigation hypothesized by the model, but this curve represents event severity 4 with no mitigation. Figure 6 also includes a line depicting the “Hypothesized Maximum Tolerance for Disruption”, which is shown at roughly 49% resilience. This indicates a threshold at which the level of resilience would be considered unacceptable, either due to financial stability concerns or some other criteria. The threshold shown here is only for illustrative purposes, but in a model where an actual Tolerance for Disruption was defined, a breach of that threshold would represent the need for additional mitigation.

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Figure 7. Time Variant Model of Actual Expected Disruption Size

Figure 7 provides an illustration of disruption size in dollars over a theoretical window of time for which the disruption event continues. The x-axis indicates time measured in hours, and the y-axis indicates the total disruption to the network in dollars. The figure shows a line indicating an increase in disruption size to approximately 1.4 trillion USD after hour 11, indicating the point at which the disruption has continued for at least one business day. After hour 14, the size of the disruption falls to approximately 7 trillion, indicating a partial recovery. After the event has continued for over 24 hours, the size of the disruption increases to over 2 trillion, indicating multiple days of halted transactions. Figure 7 also includes a line depicting the “Hypothesized Maximum Tolerance for Disruption”, which is shown at roughly 1.5 trillion. The curve shown in Figure 7 could be duplicated for the various levels of disruption and mitigation hypothesized by the model, but this curve represents event severity 4 with no mitigation.

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Last Update: July 01, 2022