Interconnected exposures

Russell Group’s Suki Basi explains why (re)insurers and corporates alike need to have a much deeper knowledge on the impact of trade disruption.

Covid-19 has already disrupted global trade significantly, with our analysis showing that Covid-19 is expected to wipe off $3tn from global trade in 2020.

It is because of this that we strongly believe that trade needs to be incorporated into traditional (re)insurance analysis.

Given that all large-scale organisations trade in goods and services in countries across the world, it makes sense to need to know what this trade is, where it operates and what the impact might be on any organisation.

In our final article for The ReInsurer, I will explain why this has not occurred and how our approach can help (re)insurers and corporates alike.

Typically, when risk exposure is analysed, it is done so at a policyholder, reinsured and/or asset level, which largely ignores the key role that trade plays in driving up exposures and losses. For example, if a ship sinks carrying goods valued at $6mn, (re)insurers would register the loss of the ship and the numerous cargo claims, but wouldn’t have connected the losses together to register further claims within the supplychain as a result of this loss.

However, if trade were incorporated within traditional analysis, then the allocation of trade through the transportation system incorporating airports, terminals, ports, ships, aircraft, and land-based vehicles, would enable trading risk and exposures to be known in real-time. This would enable corporates and their (re)insurers to make better decisions and operate more sustainable businesses.

For example, from the analysis of trade data, we calculate that the top five ports in Germany for Siemens’ exports and imports in a typical year are:

The analysis reveals that Siemens has $7bn of export trade that it relies on being shipped through the ports of Bremerhaven and Hamburg. This figure increases to $10bn when the import of goods through its supply chain is included for the same two ports. If we were to extend the analysis of these ports beyond Siemens to other trading companies and goods, we can determine who is also reliant on these ports. So if, for example,

Bremerhaven were to be impacted by an event, then we can calculate the “knock-on” effects for other businesses that are connected to this port, either directly through trade or indirectly, as their partners trade through this port. The question you may well ask, is so what? What is the importance of such a data set?

Well, such timely data enables trade exposure for exporting and importing companies to be known, and then used to drive realtime decisions so that business can be more resilient and sustainable to future disruptions. For (re)insurers this data enables the interconnectedness of exposure and the utilisation of capital, product classes such as marine cargo, credit, business interruption and supplychain to be better understood.

I would like to conclude by stressing that interconnectedness is the biggest risk of our times. The biggest impact of analysing trade is that it reinforces just how linked all organisations are.

It is through that interconnectedness that both corporates and their (re)insurers will be able to have an accurate and timely knowledge of their trading risk and exposure. In other words, they will know their connected trading risk and exposure.