Transforming Insurance with Artificial Intelligence

Artificial intelligence (AI) is emerging as a game-changer for the insurance sector, unlocking tremendous potential for enhancing operations and delivering added value. Its diverse applications span across risk underwriting, claims management, fraud detection, and customer relations, fundamentally reshaping the landscape of the industry.

Automation of Underwriting and Pricing Operations

AI is revolutionizing two critical processes in the insurance industry: risk underwriting and pricing. Traditionally labor-intensive and subject to human bias, these processes are now becoming more efficient thanks to AI’s ability to analyze vast datasets in real-time.

By evaluating factors like claims history, social media activity, and geolocation data, AI offers a more precise risk assessment. This innovation reduces the time taken to decide on coverage and set premiums, making it possible for insurers to respond to customer needs almost in real-time.

Optimization of Internal Processes

The integration of AI and robotic process automation (RPA) is streamlining the management of repetitive tasks in insurance. While RPA focuses on automating routine tasks, AI enriches this with the ability to analyze and interpret data, allowing for advanced levels of automation.

This combination alleviates the manual workload, improving both efficiency and accuracy in areas such as processing inquiries, claims, and policy underwriting. For instance, robots enhanced with AI—through technologies like optical character recognition (OCR) or natural language processing (NLP)—can efficiently gather, process, and interpret information. Consequently, this intelligent automation reduces processing times, development costs, and the risk of human error.

Tasks Performed by RPA

• Data entry and transfer: Streamlining operations by copying and pasting information between systems.
• Execution of structured workflows: Automating subscription request processing based on fixed criteria.
• Generation of standardized documents: Issuing contracts and certificates efficiently.
• Verification of mandatory fields: Ensuring forms are completed correctly.
• Data reconciliation: Matching customer lists across databases.
• Database updates: Keeping records current with minimal effort.

Tasks Performed by AI

• Document recognition via OCR: Extracting information from invoices and identification documents.
• Natural language processing (NLP): Analyzing voice or written inquiries.
• Automatic classification: Sorting communications based on urgency or type.
• Anomaly detection: Identifying and flagging potential fraud.
• Decision-making: Automatically approving small claims based on learned criteria.

An example of successful implementation is at Alan, a French health insurance provider. By integrating its platform into clients’ HR systems, Alan automates reimbursement claims processing, reducing health insurance management time to less than two hours per year.

Enhanced Customer Understanding

AI offers insurers the tools to gain deep insights into individual customer needs by analyzing demographic, behavioral, and historical data. This capability allows for more targeted risk assessments and improved accuracy in actuarial models.

Leading companies are increasingly deploying AI to enhance their service offerings:

• Generali France uses AI to create personalized insurance products derived from customer interactions and purchase histories.
• AXA, in collaboration with Microsoft, developed Secure GPT—a generative AI platform that tailors offers and recommends services based on individual risk profiles.
• Progressive, the U.S.’s second-largest motor insurer, utilizes machine learning to analyze driving behaviors for more precise risk assessments, leading to personalized policy offerings.

AI in Claims Management

Claims management encompasses all steps an insurer undertakes when a policyholder reports an incident. AI enhances this process by:

• Automating claim reporting via apps or chatbots.
• Analyzing claim data, including visuals and descriptive texts.
• Estimating repair costs with greater accuracy.

Combatting Fraud with AI

Insurance fraud poses a serious concern, accounting for 10% to 15% of the global insurance market’s total revenue. Given that global premiums were estimated at $7,186 billion in 2023, this trend represents an increasing risk.

A 2025 Deloitte study highlights that relying solely on raising premiums is not a sustainable solution. Instead, it suggests adopting proactive fraud prevention strategies through traditional rule-based detection and advanced AI techniques. There is significant momentum, with 35% of insurance executives identifying fraud detection as a key application for generative AI in the coming year.

In the United States alone, about 10% of claims are estimated to be fraudulent, costing insurers approximately $122 billion in 2024. By implementing AI technologies for claims processing, insurers could potentially mitigate losses by $80 to $160 billion by 2032.

Continuous Customer Support via AI

Virtual assistants, or chatbots, are increasingly becoming an integral part of customer support in the insurance industry. Utilizing AI algorithms, these tools provide around-the-clock assistance while diminishing operating costs by 30% to 40% compared to traditional customer service channels.

With the capability to automate repetitive tasks, such as answering inquiries or managing minor complaints, chatbots also improve response times by up to 35%. The 2024-2025 period has seen a focus on integrating generative AI and advancements in NLP, aiming for more personalized and proactive interactions.

Notable Chatbots in the Industry

• Maya and Jim: Developed by Lemonade, a leading American motor insurer. Maya assists users through policy applications, and Jim manages claim processing by interacting with policyholders to gather necessary information swiftly.

• Zara: Created by Zurich in collaboration with Spixii, this chatbot handles claims filing and related customer interactions. During its initial operational phase, Zara autonomously managed 35% of claims, drastically reducing processing times and achieving impressive customer satisfaction rates.

As AI continues to evolve, its integration into insurance processes stands to reshape the industry, offering more efficient operations, enhanced customer experiences, and robust fraud prevention mechanisms.