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August 22, 2025RisksOpen Access

Algorithmic Bias Under the EU AI Act: Compliance Risk, Capital Strain, and Pricing Distortions in Life and Health Insurance Underwriting

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Authors

SMSiddharth MahajanRARavi AgarwalMGMihir Gupta

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Overview

Analysis highlights compliance risk and pricing distortions in insurance underwriting, indicating potential capital strain.

Key Points

  • Premiums for bottom-income quintiles exceed fair benchmarks by 5.8% in life insurance and 7.2% in health insurance, demonstrating a significant compliance challenge.
  • Adversarial debiasing mitigates up to 82% of bias gaps, while increasing capital requirements by 4.1% of own funds, revealing a trade-off for insurers.
  • Assessment utilized 12.4 million insurance quotes across Europe, applying gradient-boosted decision tree models and Shapley Additive Explanations for analysis.
  • Findings underscore the necessity for insurers to adopt proactive measures for bias mitigation and compliance with regulatory scrutiny.

Cite This Study

Mahajan et al. (2025) studied this question.

synapsesocial.com/papers/68af55c6ad7bf08b1eadbc58https://doi.org/10.3390/risks13090160
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1<p>An Analytical Study of Algorithmic Bias Mitigation Frameworks in Multi-State Personal Lines Insurance for Regulatory-Ready Artificial Intelligence Underwriting</p>2026
  2. 2Algorithmic Fairness as a Risk-Management Problem in Banking and Insurance: Regulatory Frameworks, Model Governance, and Fairness-Aware Credit Scoring2026
  3. 3Fairness Assessment and Ethical Governance of Insurance AI: A Patch Approach for Vulnerable Groups2025
  4. 4From bias to business insight: evaluating machine learning approaches for fair and explainable health insurance underwriting2026
  5. 5Systemic Data Bias in Real-World AI Systems: Technical Failures, Legal Gaps, and the Limits of the EU AI Act2026 · 1 citations