10 Use Cases for Artificial Intelligence (AI) in Insurance (2024)

First and foremost, you need artificial intelligence to process large amounts of data. When we talk about an economic niche such as insurance, it becomes even more relevant. Many companies are actively testing or piloting AI-based solutions to solve their business problems, and the most innovative companies have already implemented them.

Insurance providers are currently implementing AI technologies to help them select the optimal insurance options based on clients’ “digital profiles”. They help evaluate potential risks, send personalized messages to customers, and perform many other essential tasks.

Customers are supporting insurance companies in their innovation efforts by making it more convenient to interact with them. This article provides examples of how AI can be used in the insurance industry that many of you may find interesting.

Personalized Insurance Policy Pricing

Customized pricing is offered by AI systems that evaluate individual risk profiles based on a variety of factors. It has been said that this helps to attract a wider range of customers and improve risk management.

Example:
Metromile’s pay-per-mile insurance model uses AI to assess driving behavior, adjusting premiums accordingly.

Pay-per-mile insurance customizes your rate based on your driving habits. If you drive less, you should pay less.

Risk Assessment and Underwriting

Risk factors are accurately assessed and outcomes are predicted by AI algorithms processing large datasets. Consequently, it leads to better pricing strategies.

Example:

Swiss Re uses AI for detailed life insurance risk assessments, streamlining the underwriting process. Swiss Re uses AI for detailed life insurance risk assessments.

Customer Service Chatbots

For instance, there could be intelligent chatbots offering 24-hour support services for customer inquiries and enabling them to manage their policies and claims online. To this end, there will be higher customer satisfaction levels while lowering the operational costs significantly.

For instance, in health insurance, bots help patients determine the necessary healthcare specialists based on symptoms and learn about the service format that will suit customers best, be it a video call, face-to-face appointment at the clinic, calling a doctor to your place of residence, or bringing an ambulance.

Example:

Geico’s virtual assistant Kate (mobile’s AI-enabled chatbot) helps customers with policy questions and updates anytime.

Automated Claims Processing

Claims data can be interpreted, policy details verified or payout decisions made through AI-based solutions that employ natural language processing and machine learning. The swift processing allows customers to be more satisfied and ensures they remain committed to insurance companies even as they reduce administrative costs.

Example:

Lemonade’s AI, Jim, reviews claims and cross-references them against policy details, often settling claims in mere seconds.

Fraud Detection and Prevention

Fraud activity such as anomalies in claims data can be detected by AI algorithms. By doing this, millions of dollars can be saved from fraud cases; hence trust is maintained while financial health is upheld.

Example:

One of America’s largest insurance firms, Allstate uses AI tools to scrutinize claims for irregular patterns, successfully identifying fraudulent claims.

Claims Damage Assessment

Computer vision algorithms analyze images and videos for quick and accurate damage assessment in claims. This approach accelerates the claims process, improves accuracy, and enhances customer satisfaction.

If the necessary data is missing in the provided documents, the robot automatically contacts the customers by email and requests the missing information. This approach saves employees time because there is no need to waste time on clarifying phone calls to customers.

Example:

ICICI Lombard utilizes AI for quick assessment of motor insurance claims, using photos and videos of the damage.

Business Process Automation

AI automation handles routine tasks in insurance like data entry, compliance checks, report generation etc., which cuts human resources for complex tasks reducing errors hence cost effective.

Example:

Zurich Insurance has automated many of its data processing tasks, enhancing operational efficiency.

Read more: “Insurer Zurich experiments with ChatGPT for claims and data mining”.

Predictive Analytics

AI uses past data to forecast future trends, from customer behavior to claim probabilities. It enables better strategic planning and financial management.

AI can quickly and efficiently analyze large volumes of data to identify current trends and consumer needs, considering customer behavior patterns and external factors.

Example:

AXA insurance provider leverages predictive analytics to anticipate claims trends and manage their reserves more efficiently.

Modern Technology Implementation is not a Matter of Desire But a Necessity

Modern technologies and software solutions in insurance are necessary components for the development of companies working in this niche. Artificial Intelligence stands out in this regard, as it is not yet widely used, and many business sectors are just beginning to realize its practical potential.

If you want to gain a competitive advantage, it would be better to become the first to apply AI than to wait for all the other players in the market to do so. Eventually, everyone will benefit from digitalization in the insurance business: insurance providers can save resources, and their customers can receive favorable offers and high-quality tailor-made services.

Let our experience help you realize the potential of AI solutions for your business. We are ready to be your trusted technology partner. Contact us and tell us more about your needs!