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How is AI redefining the customer experience in the insurance industry?

Updated on 03/06/2025
DialOnce Visual IVR Impact on Insurance

For a long time, the insurance industry was seen as fairly traditional and largely untouched by technological innovation. But today, artificial intelligence (AI) is profoundly reshaping the sector. Whether it's setting prices, supporting customers, detecting fraud, or preventing risks, AI is emerging as a true driver of transformation. But what does this transformation actually mean in practice for insurers and policyholders alike?

What are the new expectations of policyholders?

Policyholders now expect far more than just an insurance contract. They want a seamless experience, quick responses, and services tailored to their specific needs. More autonomous and digitally connected, they compare offers, seek relevant advice, and expect to interact easily whether online or with a human advisor.

Loyalty to an insurance provider is no longer a given. Customers are becoming more demanding: beyond price, they value clear coverage, simple processes, and high-quality support. They expect a service that adapts to their pace and expectations without friction.

To meet these evolving demands, insurers must rethink their approach by putting customer experience at the heart of their strategy. One of the most powerful enablers of this shift is artificial intelligence. According to a KPMG study, 73% of insurance industry leaders see AI as a strategic opportunity to make customer support smarter, faster, and above all more aligned with what today’s policyholders truly expect.

How is artificial intelligence concretely transforming the insurance industry?

1. Faster and more personalized policy subscription

Artificial intelligence enables insurance companies to analyze millions of data points within seconds including policy histories, past claims, health information, online behavior, and even geolocation. By cross-referencing these data, insurers can assess individual risk levels with precision and offer highly personalized pricing. According to Accenture, 7 out of 10 French consumers are willing to share sensitive data such as health records, physical activity, or driving behavior, if it results in more favorable insurance rates and customized coverage.

By integrating an AI agent into an omnichannel orchestrator that centralizes all communication channels (phone, website, email), insurers can deliver a smoother customer experience. The AI agent guides users step-by-step, tailors its questions based on responses and historical data, and can even auto-generate a policy proposal. Available 24/7, it responds instantly to requests, eliminating delays and queues, and significantly enhancing the user experience.

By automating repetitive tasks such as information requests, quotes, or simple claims AI-powered tools help reduce the burden on call centers and free up valuable time for advisors. Leveraging collected and analyzed data, AI can also suggest complementary products or personalized coverage based on each customer’s profile, delivering the right message at the right time through the right channel. This ability to anticipate needs enhances both the relevance of the offer and the overall customer relationship.

At the same time, policyholders benefit from faster processing and 24/7 responses, significantly improving their overall experience. Together, these improvements make the subscription journey smoother, more transparent, and fully aligned with the expectations of today’s increasingly connected customers.

This technological shift is illustrated by GMF, part of the Covéa Group, which implemented a Visual IVR system to handle high volumes of incoming requests. This interface allows policyholders to manage their queries independently and continuously, reducing inbound calls and streamlining the overall experience.

2. Automated and optimized claims management

Artificial intelligence plays a role from the very first stages of claims handling. Thanks to natural language processing, it can understand requests whether written or spoken and extract key information. This allows AI to automate repetitive tasks such as file sorting, document verification, or keyword recognition in statements, enabling a faster and more reliable first-level analysis. As a result, the initial processing is smoother, and overall handling times are significantly reduced.

When integrated into systems like a mailbot or a visual IVR, the experience becomes seamless for both customers and advisors. This is exactly what AXA Assistance Santé implemented by adding a Visual IVR to improve accessibility for its Angel teleconsultation service, directing part of the calls to self-service digital solutions.

AI can automatically sort incoming claims, ensure all required documents are provided, send confirmation messages, and even generate a preliminary compensation estimate all in real time.

This approach eliminates unnecessary back-and-forth and reduces overall processing time. For policyholders, it means saving time, gaining clearer visibility into the status of their claim, and experiencing less stress during what is often a difficult moment.

For internal teams, it’s also an opportunity to shift from a purely operational role to one with greater added value. With AI tools, advisors are now better equipped to analyze sensitive cases, quickly grasp the stakes of complex claims, and deliver more accurate responses. This "augmented advisor" empowered by new technologies can rely on automated suggestions, smart summaries, or contextual alerts to respond more efficiently and personally. Altogether, this enables a claims process that is more human, more efficient, and less stressful for everyone involved.

 

3. Enhanced fraud detection

Artificial intelligence now enables insurers to continuously monitor vast volumes of data, drawing from both internal systems (claims history, customer profiles, reported behaviors) and external sources (public records, partner databases, etc.). Using algorithms designed to detect unusual patterns and identify inconsistencies, AI can quickly flag potentially fraudulent activities—and even anticipate certain attempts before they are fully carried out.

This level of vigilance is essential given the growing scale of insurance fraud. In 2023, the total amount of detected insurance fraud in France reached €695 million, according to the French Insurance Fraud Prevention Agency (ALFA), marking an increase of over 18% compared to the previous year. These schemes take many forms: completely fabricated claims, exaggerated damages, or even fake invoices generated using tools like ChatGPT. In the face of increasingly sophisticated tactics, insurers must be able not only to respond swiftly, but also to proactively prevent risky behavior before it escalates.

That’s why many insurance companies are now equipping themselves with advanced AI tools capable of detecting suspicious behavior by cross-referencing multiple sources of information and identifying repeated patterns or inconsistencies in claims. These systems can also generate dynamic risk profiles, allowing them to flag in real time any patterns that resemble known fraud cases. When an anomaly is detected, an augmented advisor steps in supported by a rich analytical environment that enables deeper case review and more informed decision-making. This collaboration between intelligent technologies and human expertise allows insurers to act faster, with greater accuracy, and with a stronger impact on both fraud prevention and detection.

Trusted AI: a central challenge for the insurance industry

The insurance industry is fundamentally built on the reliability of the advice provided to policyholders. In this context, the integration of artificial intelligence must go hand in hand with a high level of transparency, rigor, and oversight. This is where the concept of “trusted AI” comes into play an approach aimed at ensuring that deployed systems are explainable, auditable, and compliant with regulatory expectations.

One of the emerging tools in this field is the use of the "LLM-as-a-Judge"  to evaluate the outputs of other AI systems. These models serve as continuous quality control agents, capable of detecting bias, errors, or inappropriate responses from customer-facing AI agents. By ensuring ongoing performance monitoring, they help maintain system reliability and protect users.

In a sector where even minor misinterpretations can have serious consequences for policyholders, trusted AI becomes an essential safeguard. It not only secures the use of AI, but also strengthens the credibility of these technologies in the eyes of the public, institutions, and regulatory bodies.

What’s next? Toward even smarter insurance

In the future, artificial intelligence could unlock innovations that are still underexplored in the insurance industry. One such development is the emergence of conversational AI agents equipped with advanced emotional analysis capabilities. These systems could adjust their tone and messaging in real time based on the emotional state of the policyholder particularly useful during stressful situations like claims reporting enhancing empathy without compromising operational efficiency.

Another promising avenue is the predictive prevention of incidents through the integration of contextual data such as weather forecasts, geolocation, or subtle signals from connected devices. For instance, AI could send a personalized alert to a car insurance policyholder ahead of a hailstorm, giving them time to protect their vehicle and avoid potential damage.

Looking further ahead, AI systems could evolve toward a model of supervised decision-making autonomy, where entire customer journeys are managed by AI agents, with final validation by a human advisor. This hybrid approach would pave the way for ultra-responsive service delivery while preserving human oversight and accountability.

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