Uncovering Seasonal Trends in Motor Insurance Claims: A Gender-Based Analysis

Research output: Contribution to journalArticlepeer-review

Abstract

The seasonal dynamics of motor insurance claims are shaped by a complex array of factors, including distinct gender-based trends among drivers. This study explores these intricate patterns by analysing insurance claims across various seasons, with a particular focus on the differences between male and female drivers. Utilising a comprehensive dataset and advanced machine learning techniques, the research highlights significant seasonal fluctuations in claim behaviours across genders. Notably, malicious damage claims spike in February for both genders, with additional surges in December and January. Miscellaneous accidents remain stable, pointing to a need for continuous preventive measures. Meteorological events are most frequent in summer, with July marking the peak for both genders, while hydrological events exhibit similar seasonal trends, and climate events show minor peaks. Geophysical events remain steady, emphasising the importance of resilience strategies. These preliminary insights offer valuable implications for improving insurance risk assessments, shaping policy development, and refining pricing strategies. By increasing the precision and equity of insurance models, this study aims to promote safer driving practices, ultimately lowering costs and ensuring more affordable premiums for all policyholders.

Original languageEnglish
Pages (from-to)118-125
Number of pages8
JournalJournal of Cultural Analysis and Social Change
Volume10
Issue number3
DOIs
Publication statusPublished - 25 Nov 2025
Externally publishedYes

Keywords

  • Catastrophic events
  • Claims events
  • Gender
  • Machine learning
  • Seasonal trends

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