Nargiza Mirzabekova
Data-driven approach to predict policy cancellation and improve customer retention in the insurance industry.
Rel. Gianvito Urgese. Politecnico di Torino, Corso di laurea magistrale in Digital Skills For Sustainable Societal Transitions, 2024
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
There is no promising success for insurers without customer satisfaction. Economic downturns and competition create increasing obstacles for the insurance industry. In the age of AI, companies rapidly adopt emerging advanced technologies to optimise their growth strategies. This thesis examines how data analysis and machine learning can help in policy cancellation prediction. The goal is to provide insurers with actionable insights for creating proactive retention practices and winning customer loyalty. This study analyses over 7,300 policy records from a real insurtech startup that serves as a digital intermediary between insurance companies and clients. The startup provides a simplified and smooth experience to get the right coverage.
The data was collected from the insurance provider dashboard, payment platform and customer relationship management system
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
