premiebasert

Premiebasert is a theoretical framework in insurance economics and risk modeling that emphasizes premium-based signals as the central input for risk assessment and pricing. In this framework, policyholder premium flows, rather than solely claimed losses, are analyzed to infer risk profiles, forecast future behavior, and guide product design. The term combines "premium" with "based," signaling a shift from traditional claims-centric models toward premium-driven analytics.

Core concepts include analyzing premium trajectories, lapse and retention patterns, coverage mix, and premium elasticity. The approach often employs longitudinal data, time-series analysis, and machine learning to map premium payment behavior to risk outcomes, while incorporating standard actuarial baselines and exposure measures.

Applications include dynamic pricing, customer segmentation, product design, retention strategies, and regulatory reporting. By focusing on premium signals, premiebasert aims to identify early indicators of policyholder risk and to tailor pricing and offers accordingly.

Limitations involve data availability and quality, privacy concerns, model risk, and regulatory acceptance. There is also a risk that premium-based signals reflect unequal access to insurance or consumer heterogeneity, which could bias outcomes if not carefully managed.

History and usage note: Since the early 2020s, the term has appeared in theoretical articles and pilot projects as an emerging concept rather than a widely adopted standard. It is described in speculative and experimental discussions within insurance analytics literature.

See also: Actuarial science, dynamic pricing, insurance analytics, behavioral pricing.