Green Insurance: A Roadmap for Executive Management
Bibliographic record
Abstract
Anthropogenic climate change is accelerating, and severe and widespread consequences are expected in many areas. Although the insurance sector is not closely associated with any of the sustainability dimensions, expectations may change rapidly. Against this background, we analyze the role of insurers, especially in the property and casualty areas, in addressing the environmental and climate risk challenges and developing a truly sustainable, environmentally friendly business model—green insurance. Building on the Principles of Sustainable Insurance set by the United Nations, we develop a comprehensive roadmap along the insurance value chain for executive management to design their company’s sustainability efforts, with special focus on property and casualty. The roadmap indicates actions to be taken as well as metrics to be managed in product development, marketing and sales, risk management and underwriting and operations and claims management towards green insurance. The existing products, risk appetite and operational processes must be reviewed to support sustainability goals and include the full portfolio of activities, including claims. The time to act is now, the sustainability journey is complex and the proposed business model transformation should provide benefits for early movers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.027 | 0.027 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.055 | 0.025 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".