No disaster is more illustrative of the need to understand risk accumulation for the marine insurance market than the Tianjin explosion of 2015. This disaster still marks the biggest single loss in history for marine, with damages estimated at a cost of USD 2-3 billion in total. Just a few months ago, Dieter Berg, president of the International Union of Marine Insurance (IUMI), spoke out about the increasing, immediate need for insurers to manage “unthinkable” risks.
The big challenge that stands between insurers and managing these cargo risks more effectively is access to reliable real-time information about the location and condition of the insured cargo. The data certainly exists, but it is very fragmented - everybody in the supply chain has their own data, in their own legacy systems, being used for their own needs, with little or no connection between the links in the chain.
Without access to this real-time data and accurate historic exposure accumulation, insurers are exposing their portfolios to large events as well as having to use buffers in their pricing to account for uncertainty. Buffers that are proving insufficient. Additionally, overcapacity in the market has made applying this buffer almost impossible, as premiums are at an historical low.
The Internet of Things and technologies like blockchain, machine learning and artificial intelligence have made it possible, for the first time ever, to adopt a real-time view of cargo risks.
With access to real-time information, underwriters could immediately limit their exposure by:
- Determining the true nature of the risk and therefore the appropriate line size to write on a new policy
- Calculating much more accurately the appropriate limit for a policy and limit the risk of over-insuring
- Take appropriate action to mitigate risk
With continued growth in world trade, the accumulation observed in the Tianjin disaster might be unavoidable, so it is vital that insurers are better prepared. By leveraging real-time cargo data, underwriters who are able to adopt real-time tools and data into their practice can be confident they will not be overexposed and they will be able to react more quickly to mitigate the impact on their bottom line.