RT Journal Article
T1 Sustainability risk in insurance companies: a machine learning analysis
A1 Oquendo Torres, Freddy Alejandro
A1 Segovia Vargas, María Jesús
AB Sustainable development constitutes a global challenge today, and the sustainable development goals (Agenda 2030) will probably set the course for the coming decades. This paper discusses sustainability in insurance companies by combining two aspects: a social approach (the environmental impact) and a business approach (the prediction of claims due to climate change). Our objective is to analyse the impact of physical risk in a home insurance portfolio and to measure in economic terms the effect of climate change in the future, by applying machine learning methodologies. Two data sources are used: a Spanish insurance portfolio with 31,998 policies and claims from 2017 to 2022, and daily meteorological variables from 290 Spanish weather stations from 2000 to 2022. Two climate scenarios are considered: RCP 4.5 (medium impact) and RCP 8.5 (high impact). On average for the period 2023–2052, the results reveal that claims will increase by 105% for the 4.5 scenario and by 129% for the 8.5 scenario. Our paper makes a clear contribution to sustainability by analysing climate risks and their impact on an insurance portfolio. It shows the grave consequences of climate change for the insurance sector's solvency and the political implications for the financial system in general.
PB Wiley
SN 1758-5880
YR 2024
FD 2024-09-18
LK https://hdl.handle.net/20.500.14352/109485
UL https://hdl.handle.net/20.500.14352/109485
LA eng
NO Oquendo-Torres, F.A. & Segovia-Vargas, M.J. (2024) Sustainability risk in insurance companies: A machine learning analysis. Global Policy, 00, 1–18. Available from: https://doi.org/10.1111/1758-5899.13440
NO Ministerio de Ciencia e Innovación (España)
DS Docta Complutense
RD 16 abr 2025