IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i3p658-d1049124.html
   My bibliography  Save this article

Quantum Computing in Insurance Capital Modelling

Author

Listed:
  • Muhsin Tamturk

    (Department of Mathematics, University of Leicester, Leicester LE1 7RH, UK)

Abstract

This paper proposes a quantum computing approach for insurance capital modelling. Using an open-source software development kit, Qiskit, an algorithm for working on a superconducting type IBM quantum computer is developed and implemented to predict the capital of insurance companies in the classical surplus process. With the fundamental properties of quantum mechanics, Dirac notation and Feynman’s path calculation are shown. Furthermore, custom quantum insurance premium and claim gates are investigated in order to build a quantum circuit with respect to initial reserve, premium and claim amounts. Some numerical results are presented and discussed at the end of the paper.

Suggested Citation

  • Muhsin Tamturk, 2023. "Quantum Computing in Insurance Capital Modelling," Mathematics, MDPI, vol. 11(3), pages 1-13, January.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:658-:d:1049124
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/3/658/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/3/658/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dickson,David C. M., 2016. "Insurance Risk and Ruin," Cambridge Books, Cambridge University Press, number 9781107154605.
    2. Muhsin Tamturk & Dominic Cortis & Mark Farrell, 2020. "Examining the Effects of Gradual Catastrophes on Capital Modelling and the Solvency of Insurers: The Case of COVID-19," Risks, MDPI, vol. 8(4), pages 1-13, December.
    3. Muhsin Tamturk & Sergey Utev, 2019. "Optimal Reinsurance via Dirac-Feynman Approach," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 647-659, June.
    4. Claude Lefèvre & Stéphane Loisel & Muhsin Tamturk & Sergey Utev, 2018. "A Quantum-Type Approach to Non-Life Insurance Risk Modelling," Risks, MDPI, vol. 6(3), pages 1-17, September.
    5. Nie, Ciyu & Dickson, David C. M. & Li, Shuanming, 2011. "Minimizing the ruin probability through capital injections," Annals of Actuarial Science, Cambridge University Press, vol. 5(2), pages 195-209, September.
    6. Tamturk, Muhsin & Utev, Sergey, 2018. "Ruin probability via Quantum Mechanics Approach," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 69-74.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhsin Tamturk & Dominic Cortis & Mark Farrell, 2020. "Examining the Effects of Gradual Catastrophes on Capital Modelling and the Solvency of Insurers: The Case of COVID-19," Risks, MDPI, vol. 8(4), pages 1-13, December.
    2. Muhsin Tamturk & Sergey Utev, 2019. "Optimal Reinsurance via Dirac-Feynman Approach," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 647-659, June.
    3. Guo, Fenglong, 2022. "Ruin probability of a continuous-time model with dependence between insurance and financial risks caused by systematic factors," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    4. Ramsden, Lewis & Papaioannou, Apostolos D., 2019. "Ruin probabilities under capital constraints," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 273-282.
    5. Jin, Ting & Zhu, Yuanguo, 2020. "First hitting time about solution for an uncertain fractional differential equation and application to an uncertain risk index model," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    6. Griffin, Philip S., 2020. "General tax structures for a Lévy insurance risk process under the Cramér condition," Stochastic Processes and their Applications, Elsevier, vol. 130(3), pages 1368-1387.
    7. Claude Lefèvre & Stéphane Loisel & Muhsin Tamturk & Sergey Utev, 2018. "A Quantum-Type Approach to Non-Life Insurance Risk Modelling," Risks, MDPI, vol. 6(3), pages 1-17, September.
    8. Anita Behme & Philipp Lukas Strietzel, 2021. "A $$2~{\times }~2$$ 2 × 2 random switching model and its dual risk model," Queueing Systems: Theory and Applications, Springer, vol. 99(1), pages 27-64, October.
    9. Emilio Gómez-Déniz & José María Sarabia & Enrique Calderín-Ojeda, 2019. "Ruin Probability Functions and Severity of Ruin as a Statistical Decision Problem," Risks, MDPI, vol. 7(2), pages 1-16, June.
    10. Krystecki, Konrad, 2022. "Parisian ruin probability for two-dimensional Brownian risk model," Statistics & Probability Letters, Elsevier, vol. 182(C).
    11. M. Mercè Claramunt & Maite Mármol & Xavier Varea, 2023. "Facing a Risk: To Insure or Not to Insure—An Analysis with the Constant Relative Risk Aversion Utility Function," Mathematics, MDPI, vol. 11(5), pages 1-13, February.
    12. Luca Regis, 2017. "Special Issue “Actuarial and Financial Risks in Life Insurance, Pensions and Household Finance”," Risks, MDPI, vol. 5(4), pages 1-2, December.
    13. Eisenberg, Julia & Krühner, Paul, 2018. "The impact of negative interest rates on optimal capital injections," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 1-10.
    14. Loeffen, R. & Palmowski, Z. & Surya, B.A., 2018. "Discounted penalty function at Parisian ruin for Lévy insurance risk process," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 190-197.
    15. Yong-Jun Liu & Wei-Guo Zhang, 2018. "Fuzzy portfolio selection model with real features and different decision behaviors," Fuzzy Optimization and Decision Making, Springer, vol. 17(3), pages 317-336, September.
    16. David Landriault & Bin Li & Mohamed Amine Lkabous, 2019. "On occupation times in the red of L\'evy risk models," Papers 1903.03721, arXiv.org, revised Jul 2019.
    17. He, Yue & Kawai, Reiichiro & Shimizu, Yasutaka & Yamazaki, Kazutoshi, 2023. "The Gerber-Shiu discounted penalty function: A review from practical perspectives," Insurance: Mathematics and Economics, Elsevier, vol. 109(C), pages 1-28.
    18. Maria Mercè Claramunt & Maite Màrmol, 2020. "Refundable deductible insurance," Working Papers hal-02909299, HAL.
    19. Esther Frostig & Adva Keren-Pinhasik, 2020. "Parisian Ruin with Erlang Delay and a Lower Bankruptcy Barrier," Methodology and Computing in Applied Probability, Springer, vol. 22(1), pages 101-134, March.
    20. Braun, Alexander & Ben Ammar, Semir & Eling, Martin, 2019. "Asset pricing and extreme event risk: Common factors in ILS fund returns," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 59-78.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:658-:d:1049124. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.