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Using AI in Non-Life Insurance

Example uses of AI in the non-life insurance industry

The applications of AI in non-life insurance are extensive and varied, encompassing a ranging from claims processing to virtual assistants and customer support. Here are examples of AI in non-life insurance:

Claims Processing Automation

Using AI, claims processing in insurance is automated, extracting and validating data from claim documents to expedite settlements and enhance operational efficiency. For instance, vehicle insurers streamline assessment and settlements for damages using this technology.

Customer Support and Virtual Assistance

AI-powered virtual assistants offer real-time support to insurance customers, handling inquiries, claims updates, and policy-related questions, thereby improving customer interactions and easing the workload on support teams. For example, a freight insurance provider can deploy a virtual assistant on their website to guide customers through the claims process.

Image & Video Analysis

In insurance, AI can analyze images and videos to assess damages, such as those from property incidents, facilitating quicker claims processing and accurate loss evaluation. For instance, a property insurance company employs image analysis to estimate damages, ensuring swift and precise settlements for policyholders.

Customer Profiling

AI enables the creation of customer profiles in insurance, aiding in customer segmentation, behavior prediction, and personalized marketing while prioritizing data privacy. This approach empowers insurers to enhance analytical capabilities and customer engagement while maintaining strict privacy compliance standards, ensuring the protection of sensitive information.

Leverage AI in non-life insurance to optimize operations, enhance risk assessment, and deliver personalized services, ensuring efficiency and competitiveness in the industry

How much does it cost for non-life insurers to implement AI?

Different AI tools cost differently, and some of them have a "pay-per-use" model. The total cost would depend on the type of AI tool being used and the number of end-users. However, banks should also take into account the availability of base systems and their ability to connect to AI tools. This would also be an additional investment to those who do not have the necessary base systems in place.


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