Conformal Risk Sharing: Certified Cost Allocation with Participation Guarantees

2026-06-04

AI Summary

This study addresses the problem of cost allocation under minimal distributional assumptions with limited data, aiming to provide individualized upper bounds on participants’ obligations to ensure no one incurs substantial losses due to participation. To this end, we formalize for the first time the “certified allocation” problem and propose a framework that integrates interpretable risk-sharing strategies with split conformal calibration. The method calibrates allocation intensity on a training set and leverages an independent calibration set to produce distribution-free, finite-sample guarantees on individual obligation caps under the assumption of exchangeability. This approach effectively reduces burdens on high-risk individuals while safeguarding other participants from significant harm. Experiments on both synthetic and real-world datasets—including precipitation and energy cooperatives—demonstrate that our method substantially lowers extreme obligations while tightly controlling adverse effects on the remaining participants.

Abstract

Sharing the financial impact of rare adverse events across a group can soften extreme individual burdens, but any participant made worse off by the arrangement has reason to leave. A credible mechanism must therefore provide each agent with a trustworthy cap on their future obligation and should be deployed only if the aggregate harm across participants is bounded. We formalise this as the Certified Allocation Problem: from finite data and without distributional assumptions, find a redistribution rule, produce obligation caps for every participant, and verify that no participant is made materially worse off. We propose Conformal Risk Sharing, which solves this problem by pairing an interpretable sharing policy with split conformal calibration. The sharing intensity is tuned on training data, while held-out calibration data produces distribution-free per-agent guarantees (valid under exchangeability). Experiments on synthetic and real-world data, including precipitation and energy-cooperative data, confirm that the framework can substantially reduce extreme obligations for high-risk agents while controlling harm to others.

Problem

• Certified Allocation
• Risk Sharing
• Obligation Caps
• Distribution-Free Guarantees
• Participation Guarantees

Innovation

• Conformal Risk Sharing
• Certified Allocation
• Distribution-free guarantees
• Split conformal calibration
• Participation guarantees