New Framework Aims to Address Systemic Bias in Insurance Pricing Models
Original framing: “Framework could deliver fairer insurance deals for customers” — Phys.org
The issue of proxy discrimination in insurance has deep roots in historical redlining and racialized underwriting practices that date back to the 19th century. These practices were not accidental but were designed to exclude certain groups from fair access to financial services, a legacy that persists in modern algorithms.
The new insurance framework is a step toward addressing algorithmic bias, but it must be situated within a broader systemic transformation.
Historical patterns of exclusion, such as redlining, have embedded inequities into the very structure of insurance markets. Cross-cultural models, particularly those rooted in communal risk-sharing, offer alternative approaches that challenge the profit-driven logic of Western insurance. Scientific and regulatory tools are necessary but insufficient without the inclusion of marginalized voices and the integration of Indigenous and community-based knowledge. A holistic solution requires redefining risk not as a commodity to be extracted, but as a shared human experience to be managed collectively. This shift demands not only new algorithms but new narratives—one that centers equity, accountability, and the dignity of all people.