Artificial Intelligence in Insurance Industry

The insurance industry is probably not the first area of human endeavor one thinks about when somebody mentions words like “innovation,” “artificial intelligence,” and “high tech”. However, once this industry embraces the change of AI, you will see this comprehensive integration is not less competitive than other industries.

Previously, we have discussed about AI in Healthcare, AI in Supply Chain which showed an enormous opportunity of AI in the 21st century. Insurance sector, is a promising sector with endless opportunities. Insurance is, in very simple terms, an industry built around risks. Insurance companies greatly depend on their ability to predict risks from one person, company, or organization. The more information they have about them and the more accurate this information is, the more likely they are to make a correct prediction, either saving themselves money or earning extra revenue. In recent years, technology-enabled innovation in insurance is highly welcomed, as in 2016, USD 1.7B across 173 deals was funded on these new insurance technologies (Deloitte, 2017).

The emergence of AI technologies means that insurance companies should scramble for the ways of implementing them in their work to get the much-needed edge over the competition. But how exactly do these innovations change the industry? Let’s have a look at some major areas that Artificial Intelligence embarks to Insurance sector.

Behavior-based premium pricing

One of the most obvious examples of insurance industry technology that completely changes the way things are done are telematics and wearable sensors collecting information about customers. The resulting avalanche of new data created by these devices will allow carriers to understand their clients more deeply, resulting in new product categories, more personalized pricing, and increasingly real-time service delivery. For example, a wearable that is connected to an actuarial database could calculate a consumer’s personal risk score based on daily activities as well as the probability and severity of potential events.

Currently, financial models are mostly built based on statistical samplings of past performance — that is, companies study the client’s record and build their predictions upon it. This new approach allows for real-time, current information to be received and used. No longer will careful drivers have to pay extra for the less careful ones because the offers can be individualized for each and every customer. The benefits of pricing client’s premium based on behavior are numerous for both insurers and insureds:

  • Encouraging better driving habit
  • Lowering claims costs for insurers
  • Changing carrier to customer relationships from reactive to proactive

(Read more: Health Insurance Claim: Machine Learning for Fraud Detection)


The insurance industry already actively uses chatbots — they help build up the initial communication with the customer without having to resort to human employees whose efforts may be better applied elsewhere. This approach allows for moving the entire interaction between the company and the client online, dramatically decreasing operational costs and thus lowering the price of premiums. And any company that only works with its customers online has to rely on machine learning to prevent fraud and guarantee that every customer gets individualized experience.

Utilizing AI and machine learning, chatbots can interact with customers seamlessly, saving everyone within an organization time – and ultimately saving insurance companies money. A bot can walk a customer through a policy application or claims process, reserving human intervention for more complex cases.

Faster claims settlement

Two of the most important factors defining the efficiency of an insurance business is how fast it manages to settle claims, and how successfully it does it. Introduction of AI dramatically boosts both of these factors. Insurance companies have massive amounts of data. On its own, data doesn’t provide much benefit. AI can process data quickly, helping insurers to automate and accelerate the claims process which is faster than the best human supervisor can ever hope to achieve, as it rarely takes the less than a few weeks, resolving in better insights.

(Related: How Insurers Accelerate Recovery Post-Covid-19 through Digital Adoption)

Decreased fraud occurrence

It is physically impossible for human insurers to gather and process all the information about policyholders that can be an indication of fraud. Companies that rely on AI solutions are capable of processing virtually unlimited amounts of such information, which means that claims are settled not just faster than it is done traditionally, but also with a much lower percentage of fraud. Additional use of machine learning for fraud detection also means that AI learns to improve their results over time, getting the ability to notice the telltale signs of fraud more efficiently as they encounter its new and new instances.

For more readings on technology application across industries, please visit:


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Author Nguyen Thi Ngoc Phuong