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ResPoNet: A Residual Neural Network for Efficient Valuation of Large Variable Annuity Portfolios

Author

Listed:
  • Heng Xiong

    (Economics and Management School, Wuhan University, Wuhan 430072, China
    Ningbo National Institute of Insurance Development (NIID), Wuhan University, Ningbo 315100, China)

  • Jie Xu

    (Economics and Management School, Wuhan University, Wuhan 430072, China
    Guangzhou Futures Exchange, Guangzhou 510630, China)

  • Rogemar Mamon

    (Department of Statistical and Actuarial Sciences, The University of Western Ontario, London, ON N6A 3K7, Canada
    Division of Physical Sciences and Mathematics, University of the Philippines Visayas, Miag-ao, Iloilo 5023, Philippines)

  • Yixing Zhao

    (School of Finance, Guangdong University of Foreign Studies, Guangzhou 510006, China)

Abstract

Accurately valuing large portfolios of Variable Annuities (VAs) poses a significant challenge due to the high computational burden of Monte Carlo simulations and the limitations of spatial interpolation methods that rely on manually defined distance metrics. We introduce a residual portfolio valuation network (ResPoNet), a novel residual neural network architecture enhanced with weighted loss functions, designed to improve valuation accuracy and scalability. ResPoNet systematically accounts for mortality risk and path-dependent liabilities using residual layers, while the custom loss function ensures better convergence and interpretability. Numerical results on synthetic portfolios of 100,000 contracts show that ResPoNet achieves significantly lower valuation errors than baseline neural and spatial methods, with faster convergence and improved generalization. Sensitivity analysis reveals key drivers of performance, including guarantee complexity and contract maturity, demonstrating the robustness and practical applicability of ResPoNet in large-scale VA valuation.

Suggested Citation

  • Heng Xiong & Jie Xu & Rogemar Mamon & Yixing Zhao, 2025. "ResPoNet: A Residual Neural Network for Efficient Valuation of Large Variable Annuity Portfolios," Mathematics, MDPI, vol. 13(12), pages 1-22, June.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:12:p:1916-:d:1674370
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