Like many businesses, health insurers face the challenge of dealing with an increasing number of customer interactions. In particular, it is becoming increasingly difficult for service staff to respond to all inquiries promptly, consistently and with appropriate care. However, this is essential, especially in the case of customer complaints, in order to counteract greater annoyance and potential customer churn. In a project with a large German health insurance company, we investigated and demonstrated how modern text-based systems can be used in combination with artificial intelligence methods to support service employees in analyzing customer complaints in a (partially) automated manner, classifying them according to subject matter, and filling in the corresponding form fields in the existing CRM system.

After intensive analysis of the in-house mail routing process and discussions with stakeholders within the organization, a centralized solution for all inbound channels was identified as suitable. Customer communications received by mail, e-mail, online customer portal or fax were analyzed using machine learning and the identified customer complaints were assigned directly to the responsible person. Both structured and unstructured elements were taken into account. The prototype we implemented recognized more than 95% of the complaints, whereas less than 3% of the regular communication was incorrectly classified as a complaint.

Cooperation partner: German insurance company

Project period: May 2018 - September 2018