IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v6y2018i1p13-d133289.html
   My bibliography  Save this article

Dread Disease and Cause-Specific Mortality: Exploring New Forms of Insured Loans

Author

Listed:
  • Valeria D’Amato

    (Department of Economics and Statistics, University of Salerno, University campus, Via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy)

  • Emilia Di Lorenzo

    (Department of Economic and Statistical Sciences, University of Napoli Federico II, via Cintia, complesso Monte S, Angelo, 80126 Naples, Italy)

  • Marilena Sibillo

    (Department of Economics and Statistics, University of Salerno, University campus, Via Giovanni Paolo II, 132, 84084 Fisciano (SA), Italy)

Abstract

The relevance of critical illness coverage and life insurance in cause-specific mortality conditions is increasing in many industrialized countries. Specific conditions on the illness and on death event, providing cheapest premiums for the insureds and lower obligations for the insurers, constitute interesting products in an insurance market looking to offer appealing products. On the other hand, the systematic improvement in longevity gives rise to a market with agents getting increasingly older, and the insurer pays attention to this trend. There are financial contracts joined with insurance coverage, and this particularly happens in the case of the so-called insured loan. Insured loans are financial contracts often proposed together with a term life insurance in order to cover the lender and the heirs against the borrower’s death event within the loan duration. This paper explores new insurance products that, linked to an insured loan, are founded on specific illness hypotheses and/or cause-specific mortality. The aim is to value how much the insurance costs lighten with respect to the traditional term insurance. The authors project cause-specific mortality rates and specific diagnosis rates, in this last case overcoming the discontinuities in the data. The new contractual schemes are priced. Numerical applications also show, with several graphs, the rates projection procedure and plenty of tables report the premiums in the new proposed contractual forms. The complete amortization schedule closes the work.

Suggested Citation

  • Valeria D’Amato & Emilia Di Lorenzo & Marilena Sibillo, 2018. "Dread Disease and Cause-Specific Mortality: Exploring New Forms of Insured Loans," Risks, MDPI, vol. 6(1), pages 1-21, February.
  • Handle: RePEc:gam:jrisks:v:6:y:2018:i:1:p:13-:d:133289
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/6/1/13/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/6/1/13/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Doblhammer, Gabriele & Kytir, Josef, 2001. "Compression or expansion of morbidity? Trends in healthy-life expectancy in the elderly Austrian population between 1978 and 1998," Social Science & Medicine, Elsevier, vol. 52(3), pages 385-391, February.
    2. Baione, Fabio & Levantesi, Susanna, 2014. "A health insurance pricing model based on prevalence rates: Application to critical illness insurance," Insurance: Mathematics and Economics, Elsevier, vol. 58(C), pages 174-184.
    3. Séverine Arnold (-Gaille) & Michael Sherris, 2013. "Forecasting Mortality Trends Allowing for Cause-of-Death Mortality Dependence," North American Actuarial Journal, Taylor & Francis Journals, vol. 17(4), pages 273-282.
    4. Fellingham, Gilbert W. & Kottas, Athanasios & Hartman, Brian M., 2015. "Bayesian nonparametric predictive modeling of group health claims," Insurance: Mathematics and Economics, Elsevier, vol. 60(C), pages 1-10.
    5. Christoph Hambel & Holger Kraft & Lorenz S. Schendel & Mogens Steffensen, 2017. "Life Insurance Demand Under Health Shock Risk," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1171-1202, December.
    6. Ermanno Pitacco, 2016. "Premiums for Long-Term Care Insurance Packages: Sensitivity with Respect to Biometric Assumptions," Risks, MDPI, vol. 4(1), pages 1-22, February.
    7. Johannes Schoder & Peter Zweifel, 2011. "Flat-of-the-curve medicine: a new perspective on the production of health," Health Economics Review, Springer, vol. 1(1), pages 1-10, December.
    8. Andrés Villegas & Steven Haberman, 2014. "On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 168-193.
    9. Renshaw, A. E. & Haberman, S., 2003. "Lee-Carter mortality forecasting with age-specific enhancement," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 255-272, October.
    10. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Li-Fei Huang, 2018. "Using App Inventor to provide the amortization schedule and the sinking fund schedule," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-9, December.

    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. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Blake, David & El Karoui, Nicole & Loisel, Stéphane & MacMinn, Richard, 2018. "Longevity risk and capital markets: The 2015–16 update," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 157-173.
    3. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    4. Danesi, Ivan Luciano & Haberman, Steven & Millossovich, Pietro, 2015. "Forecasting mortality in subpopulations using Lee–Carter type models: A comparison," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 151-161.
    5. Ling Wang & Mei Choi Chiu & Hoi Ying Wong, 2020. "Volterra mortality model: Actuarial valuation and risk management with long-range dependence," Papers 2009.09572, arXiv.org.
    6. Shang, Han Lin & Haberman, Steven, 2017. "Grouped multivariate and functional time series forecasting:An application to annuity pricing," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 166-179.
    7. Niels Haldrup & Carsten P. T. Rosenskjold, 2019. "A Parametric Factor Model of the Term Structure of Mortality," Econometrics, MDPI, vol. 7(1), pages 1-22, March.
    8. Yang, Sharon S. & Wang, Chou-Wen, 2013. "Pricing and securitization of multi-country longevity risk with mortality dependence," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 157-169.
    9. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485564, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
    10. David Blake & Marco Morales & Enrico Biffis & Yijia Lin & Andreas Milidonis, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 515-532, April.
    11. Heather Booth & Rob Hyndman & Leonie Tickle & Piet de Jong, 2006. "Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(9), pages 289-310.
    12. Wang, Chou-Wen & Huang, Hong-Chih & Hong, De-Chuan, 2013. "A feasible natural hedging strategy for insurance companies," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 532-541.
    13. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    14. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
    15. Lee, Yung-Tsung & Wang, Chou-Wen & Huang, Hong-Chih, 2012. "On the valuation of reverse mortgages with regular tenure payments," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 430-441.
    16. de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2016. "Coherent modeling of male and female mortality using Lee–Carter in a complex number framework," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 130-137.
    17. Annamaria Olivieri & Ermanno Pitacco, 2022. "Time Restrictions on Life Annuity Benefits: Portfolio Risk Profiles," Risks, MDPI, vol. 10(8), pages 1-18, August.
    18. Ayuso, Mercedes & Bravo, Jorge M. & Holzmann, Robert, 2021. "Getting life expectancy estimates right for pension policy: period versus cohort approach," Journal of Pension Economics and Finance, Cambridge University Press, vol. 20(2), pages 212-231, April.
    19. Colin O’hare & Youwei Li, 2017. "Modelling mortality: are we heading in the right direction?," Applied Economics, Taylor & Francis Journals, vol. 49(2), pages 170-187, January.
    20. Wang, Ling & Chiu, Mei Choi & Wong, Hoi Ying, 2021. "Volterra mortality model: Actuarial valuation and risk management with long-range dependence," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 1-14.

    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:jrisks:v:6:y:2018:i:1:p:13-:d:133289. 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.