Top 5 Applications of AI in Insurance to Supercharge Your Business

Since the insurance industry has always relied on data to make underwriting decisions and settle claims, it’s no wonder the use of AI in insurance has become a natural evolution. The technology’s ability to process massive amounts of data and glean deeper insights to guide your product offerings is invaluable in today’s hyper-competitive insurance landscape. Struggling to gain more customers through a great experience, 65% of insurance firms plan over 10 million dollar investments in AI technologies. 

Providing AI development services for over a decade, we’ve helped insurance agencies leverage AI capabilities for a broad range of uses to capture game-changing improvements. In this article, we want to discuss the benefits of AI for insurance and its underlying technologies that drive innovation. We’ll also review the most impactful AI applications in the industry that help insurers provide better products.   

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AI in Insurance and Its Core Technologies

Some forms of AI in insurance have been improving the industry for a long time. But they have evolved tremendously over the past few years while new models emerged to bring even more smart automation. Here are the AI technologies most used in insurance to create AI systems:

• Machine learning (ML). The most popular form of AI in insurance, ML, can find patterns and anomalies in data, which helps detect fraud early and assess risk with increased precision. ML-based insurance software can automate decision-making and provide personalized pricing strategies.
• Predictive analytics uses historical data and modeling techniques to predict future events, such as claims frequency and severity in the insurance realm. Insurers use this form of AI in insurance for better and more accurate risk assessment, which allows for setting fairer premium rates.
• Natural Language Processing (NLP). NLP enables insurers to process and understand huge volumes of unstructured data (consider policy documents and claims). Chatbots and virtual assistants powered by NLP techniques enhance customer service by answering queries and guiding customers through the application or claims process.
• Computer vision technology allows insurers to analyze images and videos. This form of insurance AI helps assess damage from accidents or property conditions via photos, which allows for making more informed underwriting decisions.
• Generative AI is a technology that can code, write, design, and produce original audio content. While still in its early days, insurers are already testing Gen AI to improve pricing and underwriting as well as identify hard-to-detect frauds.
• Large Language Models (LLMs). This branch of artificial intelligence can intelligently process, summarize, and categorize text data contained in documents. Using LLMs, insurers can accelerate their claims procedures and provide better and faster customer service. 

Key Applications of AI in Insurance

Insurance is the industry that can gain a lot from artificial intelligence due to the fact that it deals with an immense data load. Apart from discovering new insights, AI in insurance can offer colossal efficiencies and cut the complexities of existing procedures. Here are key areas where AI in insurance industry can bring immediate benefits to companies.  

Risk Assessment and Underwriting

Automating underwriting is one of the major and easier-to-reach targets for insurers looking for machine learning and artificial intelligence use cases. AI insurance software and tools like robotic process automation (RPA) help insurers better understand customer risk profiles by importing accurate information and discovering new risk characteristics. 

In addition to standard data sources (historical claims, third-party data) underwriters typically use to assess the risk, AI in insurance also takes into account abstract sources of information. They examine social media postings and publicly available datasets and even consider social, environmental, and economic factors to assess the potential risk better and predict the foreseeable risks in the future. With AI, insurers can advance underwriting and offer more accurate, competitive, and tailored pricing – a key differentiator in the insurance market.

Fraud Detection and Prevention

Fraud is a major concern and the source of lost revenue for insurance companies and their policyholders. The cost of insurance fraud is 308 billion per year, driving the premium costs for consumers. With malicious content and fraud methods becoming more sophisticated, fraud detection is costly to do and difficult to maintain. A single potential fraud investigation can be a thousand-dollar-worth task.

This is another area where again AI’s capabilities to process tons of data from different sources and find correlations can change the game. Deploying AI in insurance for detecting fraudulent claims and predictive modeling enables insurers to spot and flag unusual patterns and identify false information that indicates fraud. Thus, insurance AI software can improve the accuracy of fraud detection and lower the number of false positives. With artificial intelligence, insurers can save substantial sums of money and combat fraud.

Personalized Customer Experiences

Insurance firms are especially susceptible to client attrition because of the industry’s very customer-focused nature. Today’s consumers expect attention to their needs in real-time, anywhere, and anytime, making this mission nearly impossible without using AI in insurance. So, what can this technology do to help insurers improve and personalize the customer experience?

First, AI insurance solutions can create more dynamic client segments based on different factors (demographics, risk profile, etc.) that reflect their needs and expectations. Having a better understanding of your customer’s pains and demands, you can design more relevant and customized insurance offerings. This also allows you to provide personalized communication and support. Second, AI-based recommendation engines offer the best products for each client based on their preferences, just like Netflix does. Such AI insurance services increase customer experience and satisfaction, generating more revenue for insurers.

Claims Processing and Management

Claims processing is one of the key areas benefiting from AI in insurance. Customers measure the efficiency of the insurer by how fast and accurately they can set a claim. Manual claims processing can be slow and prone to errors, but with AI in insurance claims, providers can streamline many of the time-consuming tasks. 

Source: Scale

Insurance claims AI tools can analyze policyholder-provided data and compare it with policy details to validate the claim while simultaneously checking it for fraud. From the submission of photos of damage via an app to the repair of a car and payment of the claim amount, AI helps insurers throughout the whole process. 

Basically, it takes the standard and repetitive tasks in claims management out of your team, reducing the chances of human error and improving accuracy. Plus, the time needed for handling AI insurance claims can be reduced from a few days to several hours or even minutes. Beyond time and money savings, companies can thus enhance customer satisfaction, detect fraudulent claims early in the process, and check if claims fit legal norms.

Chatbots and Customer Service

Good customer service is paramount for every industry. Customers expecting round-the-clock, instant support won’t take long to stop using companies with poor customer service. That’s why using and developing chatbots is among the common use cases of AI in insurance. Virtual assistants and AI-powered chatbots can provide immediate responses to consumer queries and concerns or offer policy information 24/7 and without human intervention. In addition to improving customer experience, they also cut your teams’ workload.

Apart from handling routine queries regarding insurance, AI chatbots are capable of assisting policyholders with claims submission and guidance so that they can report incidents anytime and anywhere. This way, AI in insurance helps deliver best-in-class and more accessible customer service while lowering business costs and improving team productivity.

AI and Insurtech Startups

Along with the rise of AI in insurance, the industry has been disrupted by agile, data-driven insurtech startups and new AI-led products and insurance AI services. Insurtech startups such as Lemonade, GetSafe, and Metromile combined AI and insurance to successfully challenge legacy companies. Traditional systems are losing their value as the modern market rewards agile providers that leverage artificial intelligence and other latest technologies to offer the right experience to the right people. Here are a few examples of insurtech companies that showed how AI in insurance can make a difference:

• Lemonade is a pioneer in the insurtech landscape that uses artificial intelligence to automate end-to-end insurance processes and power new data strategies. Thanks to this, they saved operational costs that allowed them to offer lower prices, increase their customer base, and become a top choice for younger generations. 
• GetSafe uses AI in insurance tools to help consumers choose the best coverage for their needs. Their system compiles data regarding the customer’s existing policy, if there’s any, and compares it with other policies that may fit them better.
• Metromile is another insurtech that leverages telematics and artificial intelligence to offer pay-per-mile auto insurance. Installing devices into vehicles, Metromile collects information on speed, mileage, and driving habits and then uses AI to analyze these data and design customized insurance premiums. 

AI in Insurance: Final Thoughts

As you can see, the developments of AI in the insurance industry are driving positive changes, and those agencies that adapt quickly, as seen in the example of insurtechs, stand to gain market share and customers. Insurance agencies should act now to achieve a much-needed competitive edge. 

For this, a strategic plan and the right people with relevant AI expertise are the two critical requirements for a successful implementation of AI solutions. Relevant Software can help with both. You can hire our AI engineers to build custom or integrate existing AI in insurance tools, while our business analysts will help you align technology solutions with your business goals and strategies. Contact us to start your AI-driven transformation with the right people.