The loss potential for supply chain disruption is large and runs into the billions. A new, promising risk assessment approach can lead to the loss reduction we have been longing for.
Recent events have shown the vulnerability of optimized, high-throughput global supply chains. Very localised events such as the EVER GIVEN accident in the Suez Canal described earlier in this issue have direct – and supposedly unpredictable – effects on the global flow of goods: namely, empty shelves for consumers.
What to do? Are there solutions? Can a traditional risk analysis still cope with the high complexity? And can such a loss event be quantified based on data, such as the duration of the shipping blockade or the share of the global market flow of goods at the Suez Canal per day?
Risk Engineering at Swiss Re Corporate Solutions deals with these and similar questions, pursuing the development of holistic solution concepts. The motto is “create value beyond risk transfer”. One example of this is the Swiss Re FLOAT flood assessment tool.
Visualising the risk assessment
Events such as Hurricane Harvey in 2017, where a large proportion of flooded sites were outside official flood zones, highlight a gap between current flood zones and actual loss experience. Here, Swiss Re FLOAT offers a cost-effective way to assess flood risk with drones and collect site-specific elevation data. The collected data set is transformed using 3-D game engines – known from video game development. By linking the drone and game technologies, a simple but realistic visualisation of flood risk can be created. The companies receive an interactive application that allows them to comprehensively spatially assess the impact of different flood levels on their site.
Initial successes have already been achieved with this. In one case, the risk manager of a client was able to dispose of a six-figure budget for flood protection measures at short notice after showing the simulation to the CFO. This contributed significantly to the preparation of a detailed flood protection plan. According to our natural hazard models, this reduced the statistically expected annual loss at the site by over 60%.
But the added value for our client goes even further: the site is the only one in the group that produces essential components for the company’s cash cow product. Since the “residual risk” of flooding was assessed as a threat to the company, the group management decided to build up further production capacities at other locations with a lower probability of flooding.
This was an example from the natural catastrophe sector, where we work very closely with natural hazard modellers as well as underwriters. In the risk analysis, we create an overall view and focus on the most exposed locations for floods, windstorms and earthquakes. If necessary, we extend our consideration beyond the reported site business interruption values – including internal supply relationships (interdependencies).
Data, data, data
Data plays a major role in our business model. We have for example developed our text-mining algorithm (PARSE – Property Account Risk Screening Engine), which we use to transfer the data into a database. Unfortunately, the data is often unstructured and partly only provided as text files. We also use this to give underwriting an initial overview of the risk assessment right from the start and to determine focal points together with the risk engineers. This is a promising approach that is currently still in its infancy. The data is often unstructured and partly provided as text files.
Our global industry expert group Automotive for example successfully implemented a pilot project last year. We digitised supplier lists and were able to determine the critical nodes and locations where supply bottlenecks are to be feared if they fail, for example after a fire or an explosion.
Focus on serial approaches
Some of these approaches are not yet ready for series use. Data protection and data ownership must first be clarified. We expect to be able to carry out several “deep dives” and pilot projects with customers, their suppliers and possibly other stakeholders over the next few years. We still have a long way to go before this conceptual approach can be transformed into a scalable, partially automated process. After all, there is still no generally recognised data standard for tangible locations (physical location assets).
In addition to isolated approaches, the use of address lists is popular. It is still common practice to digitally sketch supply chains (supply chain mapping) based on address lists (sometimes several thousand suppliers with postal addresses). We are currently investigating whether and how the resulting geo-coded lists (longitude and latitude) can create added value for all parties involved. Swiss Re Corporate Solutions Risk Engineering has filed a patent for this at the end of 2021.
Conclusion: The loss potential for supply chain disruptions is large. We assume that in the automotive industry alone, the insurance gap amounts to 1 billion EUR or more. Our goal is to establish the relevant data points with the right partners in concept development (co-creation). Once all parties involved feel clear added value, we are confident that the light at the end of the tunnel will soon shine brightly.
This article is a part of our latest Spotlight publication focusing on supply chain issues. Read the publication and learn more about how you can protect your business from changes and unpredictable supply chain disruptions.
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Head Risk Engineering Services EMEA
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