How does analytics AI optimize claims management?

In a study published by Accenture in August 2022, the potential impact of artificial intelligence (AI) in claims management in the insurance industry is highlighted, Revealing that an unsatisfactory customer experience in claims management could jeopardize up to $170 billion in insurance premiums over the next five years. This underscores the growing importance of AI as a disruptive technology capable of improving claims management processes, accelerating assessments, increasing the accuracy of decisions, and optimizing the customer experience. Insurance, of course, is an example, but this is a major concern for many businesses. Therefore, this article aims to highlight the different use cases of the analytical AI in the claims management

Optimizing business processes through automation: AI optimizes claims management as it helps structure business processes while reducing human intervention. AI thus makes it possible to automate the routing of complaints, allocate tasks to dedicated teams and offer live updates on the progress of each claims. This automation not only saves time, but also ensures fast and efficient handling of complaints. For example, Saretec has been able to absorb 50% of its email processing time using InboxCare, and spend more time solving complex tasks.

Customizing the answers: Personalization is a key element in the effective management of complaints as customers expect companies to recognize their specific needs and offer tailored solutions. Moreover, thanks to analytical AI, companies are able to collect and analyze customer data, facilitating personalized complaint resolution. The exploitation of this technology now makes it possible to provide personalized support, responding more accurately and efficiently to individual customer concerns. What is more, it is important to allow employees to act directly on the message in their mailbox (thanks to templates). It is a good way to adapt your response according to the context that changes regularly (current customer satisfaction, logical link with a recent conversation etc).

Manage multi-intention : With advanced NLU capabilities (to learn more about how our AI works: Article ), the AI of allows to understand the multi-intention. Indeed, during the same message containing different claims intentions, our AI allows to analyze all of them. This is how Manutan a également fait le choix d’InboxCare to manage the different types of emails received (quotes, change of address, etc.)

Multi-intention requires language comprehension technology, which will have to dissociate several requests. For example, if the customer requests a change of address on their account, information about new offers and a question about the progress of a project, these three topics must be separated. 

Automatic categorization and routing : The analytical AI is able to instantly analyze the content of incoming messages to identify the type of complaint and underlying intentions as previously said. This not only allows for an accurate categorization of complaints, but also ensures that each case is routed to the right department or the person best suited to handle it. This ability to sort and route claims automatically and intelligently significantly reduces processing times, improves operational efficiency and increases customer satisfaction by ensuring that concerns are addressed quickly and in the right hands. In addition, this automation reduces the risk of human error, allowing for more consistent and reliable complaint management, and subject-based prioritization.

Analyse de formulaires en texte libre : Elle permet également l’analyse optimale de formulaires en texte libre. Au-delà de la simple lecture de texte brut, cette technologie permet d’extraire efficacement de la donnée, et de transformer de la donnée non structurée en données structurées. Prenons l’exemple d’un formulaire laissant la possibilité de réponses libres aux participants . L’IA va justement pouvoir, par l’analyse,  catégoriser ces réponses reçues, et ainsi permettre de mieux exploiter ces données.

Therefore, we realize that analytical AI makes it possible to process complaints efficiently, through its automation. Similarly, thanks to the personalization of responses and the optimization of operational processes, analytical AI proves to be a key asset for optimal complaint management. Moreover, IAs like that of with InboxCare, leads to accurately process different intentions in the same email, and extract structured data from free text.

If you too want to optimize your claims management with AI, Contact us  !