The following types of results support the assessment of insurance risk and response to global warming

According to the World Property and Casualty Report, artificial intelligence- and price-calculating machines, leveraging cloud computing power, can be used as important tools for data analysis, weather forecasting and loss assessment. Through cloud technology, insurers can manage, process and access vast amounts of data – data that can be used in valuable AI and ML models. Creating such models allows insurers to predict the exact location of potential weather-related risks and provide customers with options to take before, during or after a natural disaster.

“Many new technologies hold the promise of reducing the risk of climate change. Validated solutions and claims, with the help of automated digital and video cameras, can show the power that helps get cars off the road,” writes Ryan Vigus, Senior Vice President at CSAA Insurance Group. in an email interview with Digital Insurance. “Additionally, AI-powered risk management platforms use machine vision and geospatial imaging to anticipate, mitigate and manage risks. We monitor, invest and implement technology that we believe can help our customers understand climate risks and act on them.” something to solve this problem. to protect themselves from the problems caused by climate change.”

Digital also offers the opportunity to provide insurance and loss or analysis on a large scale, in case of natural disasters. A raincoatThe Puerto Rican Insurtech, offers parametric insurance – so called because it pays immediately when a certain parameter is reached, such as wind speed – through digital solutions that create large individual claims in response to hurricanes, floods and earthquakes.

The company was born after the 2017, category-five hurricane Maria that devastated Puerto Rico – millions were left without electricity, water or aid for months, even years. Jonathan González, CEO and founder of Raincoat, returned to Puerto Rico to help his mother, who was one of the many victims of the hurricane. After waiting almost a year for a money changer to show up to assess the damage to her home, González knew there had to be a faster way for those affected to receive help.

“I started researching with my team and what we found was that there was this idea called ‘parametric insurance,'” explains González. “But what we’ve been confused about is that we haven’t seen the appeal at the consumer level.”

After meetings with major insurance companies, government officials and regulators about this issue, González realized that the problem comes from the lack of a suitable model of the risk of such an event.

“You have to know how to detect events in real time. You have to combine all that in some kind of data. So suddenly, it stopped being a financial issue and started being a software issue… And that’s where it got to us,” says González. “We can consolidate these programs into a unified group … and offer this to insurance companies or brokers or governments as a way for them to build themselves and build themselves.”

Raincoat model solutions first provide an assessment of the magnitude of natural disasters, and then determine the rates of lost wages based on the damage that occurred in the area. Their hurricane model estimates how the wind will affect an area, and therefore, how the hurricane will affect the area. Raincoat’s digital platform also alerts policyholders of all events in real-time with personalized policy and payment notification information.

Another insurtech that embraces the power of AI technology is Zesty.aiA property risk analysis platform that provides insurers and consumer customers with the most accurate data on more than 200 billion pieces of data, including property value or condition, as well as potential risks from natural disasters such as wildfires, hurricanes and hurricanes or floods.

By partnering with national and regional insurance companies, reinsurers and MGAs, uses its technology to understand asset requirements and create predictive models for climate risk. The company uses AI technology, such as computer vision, with aerial photos, satellite images, building permits, weather location data, traffic history and data from sensors to map the hazards and features of each location.

“Our goal is very valuable,” explains Attila Toth,’s CEO and founder. “How hard is that roof? How is that roof? What is the roof like?’s disaster model “Z-FIRE” uses aerial images taken after wildfires to repair damaged, partially affected or abandoned properties in wildfires. Z-FIRE’s aerial images, which can be updated daily, can detect human-made features, such as the amount of vegetation around the site and its impact.

“Our method is based on science, but it is also based on understanding what happened in the past. The past is not always 100% predictive of the future, but if you can build a very large database at the level of each property from 1,500 per person. wildfires that started years ago 100 years in California, about 20 years outside of California, so you have a good chance of taking the future,” says Toth.

On the Verisk weather panel, Carlos Martins, Senior Vice President of Verisk Claims Solutions, also discusses the use of aerial photography in the insurance industry and how such technology can be used after a natural disaster – especially to deal with fraud cases.

“Insurers have never been better positioned, thanks to advances in technology to be able to respond in the event of an accident,” says Martins. “Fortunately, many insurers have invested in technologies and tools, analytics to detect this type of activity and request and know when they need to send a special investigator, for example, to investigate a loss.”

According to Martins, insurers have access to two important types of aerial imagery: “Blue sky imagery,” which provides financial information prior to an accident, and “aerial imagery,” captured by drones and airplanes for insurers to assess. . property damage within 24 hours of the incident. Through photos and videos, adjusters can take measurements and measurements, test equipment and assess damage within hours of an event – compared to the process of traditional claims, which can take a long time. This is a very important tool for fraud detection.

Martins also said that image metadata, or the information embedded in the image, could be used to alert insurers to “an image being submitted by an unscrupulous contractor, or an informal operator, [that] it is reviewed to highlight inappropriate activities,” explains Martins.[Insurers] they did not have the modern equipment and tools to deal with the dangers that may arise in the coming season. “