AI: How Leading Insurers Adapt to the New Norm of Extreme Storms

The 2024 Atlantic hurricane season brought unprecedented changes to Florida’s insurance market.

The impact of inclement weather has caused home and flood insurance rates to balloon over 400% in the last five years alone. Most recently, Hurricanes Helene and Milton led to housing supply and demand volatility, as data indicates Tampa’s housing supply is up 58%, while demand shrunk 10%.

Related: NOAA Confirms It Has Been a Busy Weather Year

As extreme weather-related events grow in intensity, so does the risk for insurers. Hurricane Helene, for example, caught many by surprise––most of the damage occurred outside of the typical parameters in a catastrophe area. Many were unprepared for this type of fallout, totaling an estimate of $30.5 to $47.5 billion in damages from the disaster, $20 billion to $30 billion of which is uninsured, according to CoreLogic. These natural disasters compel the insurance industry to adopt new technology and strategies to manage rising risks and costs effectively.

Without accurate analytics and dependable industry data, insurers could lose billions of dollars due to one single catastrophic event. This industry longs for certainty and precision, and in today’s climate, insurers must have the proper methods and tools in place to be ever adaptive. Determining risk and adequate pricing for storms as devastating as these remains fundamental to insurance providers.

Related: Analysis Shows Wider Florida Flooding From Milton: 185,000 Buildings Hit

With Hurricane Milton, many observed a shift in preparedness. Not only did Milton follow a traditional storm model, but carriers were already assembling business partners for an immediate response to local policyholders. However, due to the crossover in damages from the two hurricanes happening within weeks of each other, many insurers still leaning on heavily manual processes struggled to meet the requirements of speed, accuracy, and transparency demanded by those whose lives were impacted by the disasters.

As trusted partners in times of crisis, insurance providers play a distinct role in supporting people through the aftermath of natural disasters. Without automated, streamlined claims processing, insurers could unwittingly prolong the time it takes to settle claims accurately and transparently, and for customers dealing with severe property damage or destruction, any additional wait time could be devastating.

AI for Enhanced Value

Ensuring accurate and transparent policy quotes is foundational to delivering on this commitment, setting the stage for rapid claims settlements during times when they are most needed. Generative AI transforms the underwriting landscape by leveraging the extensive data at insurers’ disposal to identify risk patterns and forecast potential claims with remarkable efficiency.

Moving away from siloed, legacy systems and time-intensive manual operations, and instead embracing digital platforms and automated workflows embedded with gen AI, enables property and casualty teams to support customers more effectively. With advanced technologies taking over mundane, easily automated tasks and thus freeing team members’ time to focus on more strategic, value-adding, customer-facing activities, insurers build their reputation for service excellence in processing a highly demanding volume of natural disaster claims with care and empathy.

Related: Most Homeowners Worried About Impact of Natural Disasters and Climate Change, New Survey Shows

For instance, the frequency of environmental changes may cause some insurance companies to raise rates or become more selective of whom they are distributing new policies. Consequently, this can become a humanitarian issue as it leads to less affordability and accessibility for individuals living in certain regions. An AI-first strategy that provides actionable insights, predictive analytics, and scenario planning into climate impact not only opens doors to underserved markets but also strengthens insurance inclusivity, creating new revenue streams by expanding access to coverage.

Moreover, revenue streams are maintained by strong customer experiences. Tailored policies that reflect individual risk profiles enhance customers’ understanding of their coverage, reducing the number of disputes. This transparency facilitates speed and accuracy, providing customers with much needed relief and the right support to rebuild their lives.

Optimizing Predictability & Outcomes

The likelihood of these billion-dollar natural disasters increasing each year remains high. Insurers must be well-equipped with solutions that will improve the precision of AI-driven catastrophe modeling to help predict and mitigate future losses. AI powered by vast data sets develop a nuanced understanding of location-specific risks. For example, by filtering historical imaging data, AI could predict the potential impact of at-risk properties in the path of a hurricane.

Alternatively, specific building features, such as roof type or construction materials, directly influence the level of damage sustained from natural events whether it be hail, heavy snow, or a hurricane. Leveraging machine learning and AI models, insurers can offer location-specific recommendations on materials, irrigation, and drainage solutions. As they focus on “Prevent and Protect” strategies, gen AI can help insurers better educate their customers on extreme weather preparation. These insights empower policyholders to better protect their properties, reducing potential damage and associated claim costs. The more precise the picture of risk, the better insurers and insureds can prepare to minimize damages and costs.

The data insights used for risk assessment and pricing will only evolve to bring greater certainty into these situations by integrating real-time insights from weather patterns, sea-level rise, and other climate variables into claims processing. An insurer will be able to use gen AI to instantly determine loss impact and create a claim before the insured can view the property and file a claim themselves. With the use of synthetic data on the rise, the industry will continue to innovate, allowing insurers to train large learning models, preserve privacy, and test scenarios, but most importantly, it benefits policyholders as well.

Saye is an insurance claims leader at Genpact, a global professional services firm. He has more than 30 years of property/casualty experience.