TY - JOUR
T1 - Uncovering Seasonal Trends in Motor Insurance Claims
T2 - A Gender-Based Analysis
AU - Buthelezi, Sandile
AU - Hungwe, Taurai
AU - Seeletse, Solly Matshonisa
AU - Mbirimi-Hungwe, Vimbai
N1 - Publisher Copyright:
© 2025 by Author/s.
PY - 2025/11/25
Y1 - 2025/11/25
N2 - 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.
AB - 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.
KW - Catastrophic events
KW - Claims events
KW - Gender
KW - Machine learning
KW - Seasonal trends
UR - https://www.scopus.com/pages/publications/105023854382
U2 - 10.64753/jcasc.v10i3.2389
DO - 10.64753/jcasc.v10i3.2389
M3 - Article
AN - SCOPUS:105023854382
SN - 2589-1316
VL - 10
SP - 118
EP - 125
JO - Journal of Cultural Analysis and Social Change
JF - Journal of Cultural Analysis and Social Change
IS - 3
ER -