Telematics in Insurance: Challenges and Limitations

The integration of telematics in the car insurance sector has attracted significant interest due to its potential to disrupt the industry and improve road safety. By capturing actual driving behaviour, telematics offers insurers a data-driven approach to assess risk and price premiums and encourage safer driving practices. A substantial body of literature has explored the applications of telematics in insurance, aiming at enhancing the analysis and understanding of driving behaviour by using more advanced techniques, such as machine learning and deep learning, or introducing new data sources. The results obtained so far are promising. However, few studies have comprehensively addressed the practical challenges and limitations of applying such results in real-world telematics settings. Adopting the perspective of a motor insurance provider, this paper focuses on practical applicability by critically reviewing key contributions in the field. Our aim is to give a high-level overview that not only uncovers the limitations of existing studies but also highlights the potential of using telematics in insurance.