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5 Ways Generative AI Can Boost CAT Claims Readiness and Response

Written by
Amrish Singh
how to use generative AI in claims

Wildfires. Hurricanes. Tornadoes. CAT season is coming, and this year may be particularly tough on insurers. Don’t be caught unprepared. Generative AI can help you keep up with the coming claims demand.

The Challenges Ahead

Data from the National Oceanic and Atmospheric Administration (NOAA) shows that mega-disasters have surged in the last few years. In 2022, there were no fewer than 18 disasters that caused losses of at least $1 billion.

Given the recent trend, it seems likely that 2023 will be another year with high natural disaster losses. AccuWeather’s forecast for 2023 calls for 11 to 15 named storms, which is on par with the 30-year average of 14 named storms, and AccuWeather’s 2023 U.S. wildfire forecast predicts there will be 60,000 to 75,000 wildfires. Meanwhile, peak tornado season is already underway, and USA Today says the first three months of 2023 say the highest tornado count on record.

Of course, it only takes one disaster to cause massive damage and numerous claims. When policyholders are experiencing a catastrophe, they want immediate assistance from their insurers. That’s difficult under normal conditions, but it’s even more challenging when human resources are scarce and budgets are tight. Don’t expect claimants to be understanding. They’re paying for coverage, and if they feel underwhelmed when they need help the most, they’re likely to switch carriers.

How Generative AI Can Help

When claims surge, insurers need to respond with speed and care, and they need to do so with limited resources. That’s where generative AI comes in.

Generative AI is a radically new approach to machine learning that utilizes algorithms to analyze images, text, music, or even complex data sets, based on the information it has been trained on. This technology is particularly proficient in tasks such as content generation, data augmentation, and anomaly detection, owing to its ability to model complex patterns and distributions. 

Here are five ways to use generative AI in your claims management: 

1. Provide FNOL support in different languages, improving customer experience. 

When claimants are stressed because of storm or fire damage, they are frustrated by language barriers. At the same time, when your claims team is stretched thin, you might have a hard time delivering support in every language that’s needed. Generative AI can help. 

Generative AI tools can convert text from one language to another. They can convert speech to text. This means a claimant can answer questions in their preferred language and the responses can be turned into English text, which the claims professional can then read.

2. Summarize claims statements, saving file handlers time.

When claims professionals are overwhelmed with high volumes, they need to cut to the chase. Unfortunately, distressed claimants don’t always know which details are important, and they may repeat themselves or provide information that isn’t relevant to the claim. While this is understandable, it can make it more difficult for your team to wade through the information.

Generative AI can help by taking long documents and summarizing the key points. This is possible with claimant statements as well as other documents. Insurers receive the full transcript along with the summarized version. 

3. Auto-triage claims, deploying immediate assistance. 

Some claims require an immediate response. In water claims, for example, prompt action is needed to mitigate the loss. However, when claims professionals are overwhelmed, they may not be able to give new claims immediate attention. A lag of a day, or even just a few hours, could allow the situation to get worse.

AI can help by performing automated triage. During the completion of the First Notice of Loss, the AI-powered system can match claim details with available service providers and deploy help immediately. 

4. Extract claims data, developing better processes and forecasting.

According to Financial Times, Zurich is experimenting with how it can use ChatGPT, a popular generative AI program, in claims and modeling. The insurer wants to use generative AI to extract data from claims descriptions and other documents.

Using AI to extract claims data could have both long-term and short-term benefits. In the short-term, data extraction could help claims professionals assess the claim and speed up the claims process. In the long term, the data could be used to improve underwriting, which is what Financial Times says Zurich is trying to do. 

5. Dramatically reduce insurance fraud, potentially saving billions.

Fraud detection is another AI application with both immediate and long-term benefits. The Coalition Against Insurance Fraud estimates that insurance fraud results in losses of at least $308.6 billion each year. Fraud detection is especially important following CAT events when fraudulent claims and contractor charges are common, as Business Insurance Magazine reports. If insurers can make a dent in fraud, they stand to gain billions. This is yet another area where generative AI and related AI-powered analysis capabilities can help.

The Possibilities Are Endless

Generative AI tools have progressed by leaps and bounds, and the possibilities for the insurance sector are near endless. According to Insurance Business, Chubb is experimenting with the use of AI in many applications, including underwriting, claims, marketing, analytics, customer interface and customer service.

Do you want to see how an AI-powered platform can transform your claims response? Liberate provides everything you need to build end-to-end automations without using an expensive and time consuming rip and replace strategy. Learn more.