How AI can help predict natural disasters, and how insurance companies can save
Almost every day for the last fifty years, some disaster has occurred related to weather, climate, or water hazard, according to the World Meteorological Organization (WMO). Analysts at Swiss Re, an insurance and reinsurance company, pegged the economic loss from natural catastrophes in 2020 to be around $190B worldwide. However, if a few hurricanes had taken a slightly different path they warned, the damages could have easily reached $300B. Collectively, these natural disasters have caused more than $5,200B in losses since 1980 and are only getting worse and more frequent.
While we might be facing more catastrophic events, prediction models and improved technology might be some of the main ways we can protect ourselves, our families, and our property. Over the last 50 years, the number of disasters has increased over a factor of five, but thanks to early warning systems, the number of deaths have only increased threefold.
Some of the main instruments we have at our disposal to fight the damage and danger of these increasing natural disasters are emerging tools such as data collection, data processing, AI, and social networks. Insurance companies are taking notice because these tools have the potential to reduce damage before a major natural disaster, potentially saving them hundreds of thousands of euros. Increasing our preparedness and resilience to natural hazards and disasters will be a complicated and multipronged effort to improve risk and impact assessment and increase investments in risk reduction, preparedness and response.
What technologies are being used
Observation: Access to and the ability to process and transmit data is at the core of better prediction methods. Earth observation technology, street-level imagery, and IoT-connected devices give us a way to look at the world around us that would have been previously unfathomable. Then, using data mining and processing techniques, machine learning, cloud computing, and predictive analytics, we can interpret that information and hopefully make predictions to where and when disasters might strike. Governments and associations like the World Meteorological Organization and insurance companies are experimenting with these technologies to what kinds of predictions are working and how accurate they can get.
Communication: Predicting upcoming natural disasters is only helpful if you are able to disseminate warnings with enough notice for people to take protective steps. By 2023, 73% of people across North America, Latin America, Asia, and the Pacific are expected to be internet users, and 74% mobile users. Mobile devices and the internet are, of course, the most effective way to reach massive amounts of people in a concise period. Paired with other technologies such as TV and radio, organizations should be able to disperse information and help the public not only improve their chance of surviving a natural disater, but hopefully prevent millions of dollars worth of potential damages. As more tools are brought into the bubble of smart homes, families might soon even be able to turn off their water or electricity remotely if they receive a warning from their insurance company. Or the warnings could come from the homes themselves if they, for example, have a humidity detection instrument in the foundation that could connect to a basement sump pump and notify the homeowners if too much water or moisture was building up.
How this can be useful for insurance
When these grand-scale natural disasters occur, insurance companies are left scrambling, trying to figure out how to help their clientele as quickly as possible while simultaneously avoiding overpaying and possibly bankrupting themselves.
There are two main ways that insurance companies would be able to use these technologies to help their companies. One, would be preventative, taking note when bad weather is approaching and warning policyholders to minimize potential damage. Grupo Catalana Occidente in Spain has tried to implement such a plan to warn clients of heavy rain or strong winds. However, weather prediction is still far from an exact science, so this is not always a reliable option. Often insurance companies also don’t have the most advanced analytical tools at their disposal, nor the advanced skill sets to use them.
The other option for how insurance companies can use technology is by speeding up the claims and payment process. MAPRE, for example, uses databases to identify affected areas after a natural disaster and compile a list of clients living in the area. That list is then passed to claims, where the company can proactively reach out to clients and start collecting and processing information regarding the clients' policy.
If insurance companies can take a bit of the initiative of starting the claims processing process, it would not only help things go faster, possibly saving time for everyone involved, but it is a huge act of customer care that will lead to stronger customer relationships. For any number of reasons, people might not be able to immediately reach out and start their claims process after a natural disaster. If you are worried about your friends and family being safe, the last thing you want to do is worry about paperwork.
While insurance companies have been slow to explore and implement many of these technologies, they are starting to make progress. Evidence from numerous countries and economies have shown that these technologies can help insurers provide a more accurate, comprehensive, and timely assessment and policy payout for their customers. As companies can reduce costs through preventative measures, they can reinvest in further projects that will build stronger trust and customer relationships. As these observation and monitoring technologies become more widespread and cost-efficient, their potential use case will only grow and improve.
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