Two research papers explore novel approaches to fairness in insurance pricing, addressing the tension between actuarial and solidarity fairness. The first paper introduces an \"alpha-Fair Individual Solvent Premium\" ($\alpha$-FISP) framework, which allows for a tunable continuum between actuarially fair and solidarity-based pricing while ensuring solvency. The second paper focuses on discrimination-free pricing by using privatized sensitive attributes, enabling fair pricing even when direct access to sensitive data like gender or race is restricted due to privacy or regulatory concerns. AI
IMPACT These papers introduce novel algorithmic frameworks for insurance pricing that balance fairness and solvency, potentially influencing future actuarial practices and regulatory approaches.
RANK_REASON The cluster contains two academic papers published on arXiv detailing new methodologies for insurance pricing.
- alphaXiv
- arXiv
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- cs.LG
- DagsHub
- Discrimination-free Insurance Pricing with Privatized Sensitive Attributes
- Gotit.pub
- Hugging Face
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- scite Smart Citations
- Tianhe Zhang
- U.S.
- α-Fair Insurance Pricing: A Fairness Continuum
- α-FISP
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