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In insurance, what truly makes the difference is how the company responds when something goes wrong. A single poorly handled claim can cause customer trust to collapse. During a claim, the customer often feels frustrated, while the advisor faces the pressure of resolving the issue quickly and effectively without creating new friction points.
With artificial intelligence (AI) and AI agents, claims handling is no longer limited to managing dissatisfaction, it becomes an opportunity to strengthen customer satisfaction and the overall relationship. The goal goes beyond providing an answer: it now includes understanding the context, anticipating needs, and delivering a seamless journey across every channel. This shift transforms a stressful exchange into a more controlled and human interaction, supported by enhanced digital assistance.
Effective claims handling starts with quickly understanding the situation, gathering the right information, and acting without delay.
Outside business hours, a customer should never have to wait to report an issue or access essential information. Integrating an AI agent into insurance processes ensures continuous availability and immediate first-level support, even in the evening or on weekends. Accessible 24/7 across all entry points (website, IVR, Google Business profile, mobile app...), it identifies the channel, retrieves the context, and starts a smooth, frictionless conversation without complex authentication.
Customers can report an incident, share information, or check the status of their claim at any time, without waiting until the next day. When used by the customer, the AI agent instantly guides them to the right information or the right person, ensuring no request remains unanswered when urgency is high. This responsiveness reassures the customer and reinforces the feeling of being truly supported from the very first contact.
Requests related to claims and complaints are often complex, vaguely expressed and vary widely from one customer to another. With intent analysis, the topic, the type of request and the level of support needed are identified from the start, without forcing the customer to repeat themselves or move from one department to another.
Supported by a structured intent and solution framework, combined with an advanced NLU engine and generative AI, this new generation of conversational chatbot contextualizes and understands the customer's real intent, even when it is implicit or poorly formulated. It identifies the request precisely, applies disambiguation when needed and automatically collects the required information.
This fine-grained understanding allows the system to handle the request directly and, depending on the situation, enables the generative AI chatbot to respond instantly or route the customer to the right service without mistakes or unnecessary transfers. The customer journey becomes clearer, processing times are reduced and internal teams naturally experience a lighter workload.
When a customer reports an issue and intent analysis has been correctly performed, the integrated AI agent can then handle the request directly. It can check eligibility, display claim status, indicate missing documents, suggest an automatic solution or compensation when conditions are met, or trigger a follow-up on a pending process. The conversational AI agent handles most simple and frequent requests on its own and prevents unnecessary back-and-forth. This accelerates resolution times and improves response quality.
When human expertise is required, the AI chatbot orchestrates the next steps by directing the customer to the most appropriate channel (chat, phone call, form) and passing the full context to the advisor. This allows the advisor to focus on higher-value situations that require human judgment, deeper analysis or personalised support.
In a context where policyholders expect fast and reliable answers, transparency has become essential. AI agents play a central role by delivering consistent, up-to-date and easy-to-understand explanations, all adapted to each customer’s specific situation. They help users see the different stages of their case, anticipate processing times and understand the real status of their request. Customers no longer feel the need to contact a service repeatedly to obtain basic information, which reduces the workload for internal teams. This increased visibility helps build a climate of trust and limits frustration caused by uncertainty, which is often the source of escalations or repeated complaints.
When a claim is handled in a smooth, personalised and proactive way, a moment initially perceived as negative can quickly become much more reassuring. This is often the moment when the customer realises that the insurer is not simply providing an answer but is genuinely trying to understand their situation. The AI agent captures what the customer is attempting to express, identifies signs of frustration, hesitation or doubt, and enables intervention before the relationship begins to deteriorate. By directing the customer immediately to the right information or to the right person, the AI agent prevents them from feeling left alone in the process. By clarifying intentions, it enriches the understanding of the context and prepares a seamless transition to human support. Advisors then gain a much clearer view of the situation. They know what level of support to provide, what tone to adopt and which elements to explore further. Instead of offering a generic response, they adjust their approach to the customer’s reality, their actual needs and their level of understanding.
This level of personalisation transforms the interaction. A claim is no longer perceived as a simple task to be processed but as an opportunity to strengthen the relationship. The customer feels understood, heard and supported. Trust grows, and so does the perceived quality of service.
