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Record W4414243261 · doi:10.3390/jrfm18090516

The Impact of Climate Change on the Insurance Industry: Perceptions of Industry Experts and Corporate Responses

2025· article· en· W4414243261 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Sustainable Development
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeInsurance industrySustainabilityProduct (mathematics)PerceptionRisk managementQualitative research

Abstract

fetched live from OpenAlex

The impact of climate change is posing substantial risks for contemporary businesses and individuals. In response, insurance companies are adapting old and adopting new strategies and practices. This study aims to identify operational and structural changes that insurance companies implement in response to risks posed by climate change. The overarching goal of this study is to understand the perceptions of industry experts about how climate change impacts the insurance industry, and identify corporate responses to the pressures stemming from climate change and the rising societal awareness of its impact. Using qualitative research methods, we gathered primary data from eight interviews with senior executives involved in sustainability initiatives within the insurance industry, along with secondary data on Singapore’s three largest insurance companies. Our findings indicate that industry experts view climate change as a significant external force influencing corporate strategies and operational frameworks. Further, insurance companies are investing in environmentally friendly businesses, changing product portfolios, and developing collaboration with administrative and regulatory bodies. Implications of these findings for managers and policymakers are discussed, along with directions for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.200

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.269
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it