The paper characterizes a five-attack space for AI-agent insurance and proves joint incentive compatibility by adding common-control aggregation, interface escalation fees, and model-identity menus to a base runtime, plus a two-parameter premium family.
Capital Allocation to Business Units and Sub-Portfolios: the Euler Principle
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
abstract
Despite the fact that the Euler allocation principle has been adopted by many financial institutions for their internal capital allocation process, a comprehensive description of Euler allocation seems still to be missing. We try to fill this gap by presenting the theoretical background as well as practical aspects. In particular, we discuss how Euler risk contributions can be estimated for some important risk measures. We furthermore investigate the analysis of CDO tranche expected losses by means of Euler's theorem and suggest an approach to measure the impact of risk factors on non-linear portfolios.
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Proposes a time-consistent counterfactual actuarial runtime for AI agents establishing four structural results on toll definition, no-splitting boundaries, authority premiums, and runtime gating.
Introduces a deterministic runtime contract and authority frontier primitive for pricing and gating side-effect actions of AI agents, with empirical instantiation across four environments showing domain-specific reserve requirements.
citing papers explorer
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Gaming-Resistant Insurance Contracts for Autonomous AI Agents: Strategy-Proof Toll Mechanism Design
The paper characterizes a five-attack space for AI-agent insurance and proves joint incentive compatibility by adding common-control aggregation, interface escalation fees, and model-identity menus to a base runtime, plus a two-parameter premium family.
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Foundations of a Time-Consistent Counterfactual Actuarial Runtime for Autonomous AI Agents
Proposes a time-consistent counterfactual actuarial runtime for AI agents establishing four structural results on toll definition, no-splitting boundaries, authority premiums, and runtime gating.
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Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents
Introduces a deterministic runtime contract and authority frontier primitive for pricing and gating side-effect actions of AI agents, with empirical instantiation across four environments showing domain-specific reserve requirements.