IDEAS home Printed from https://ideas.repec.org/a/ora/journl/v1y2015i2p370-379.html
   My bibliography  Save this article

Inflation Adjusted Chain Ladder Method

Author

Listed:
  • Bente Corneliu Cristian

    (Universitatea din Oradea,)

  • Gavriletea Marius Dan

    (Facultatea de Business,)

Abstract

Claims reserving is one of the basic actuarial tasks in the insurance industry. Based on observed claims development figures (complete or incomplete development triangles or trapezoids) actuaries have to predict the ultimate claim amount for different lines of business as well as for the whole insurance portfolio. In order to fulfil the commitments at any time arising from contracts insurance, insurance companies are required to establish and maintain certain technical reserve. As a result, these technical reserves have a major role in ensuring stability, the financial insurance companies being completely necessary to estimate as correctly. Also the technical background operation is an essential part of insurance companies as related funds are invested and earnings are an important source of income.Calculation of technical provisions is achieved by actuarial methods and their overvaluation or underestimation distorts business of insurers. The overvaluation reserves leads to reduced solvency margin and the company may be unable to make to commitments at a time, and undervaluation influence and profit taxes paid may be higher.The inflation-adjusted Chain-Ladder methodology incorporates an explicit allowance for past and future inflation. This method requires a triangle of paid claims and credible estimates of past and future inflation assumptions. Incremental payments in each calendar period are adjusted by past inflation to the same money terms. This way it assumes that the inflation-adjusted development is stable – so that the Chain-Ladder assumption can hold. Then the incremental values are restated again as a cumulative development triangle and the Chain-Ladder method is applied. Finally, as the payments will actually be paid in the future, incremental cash flows will be adjusted by the future inflation assumption to allow for this.All the economic actors active in a market consider and analyse permanently the evolution of the business cycle by using available data in order to make rational choices in their business decision. In other words, the decision making relies in all its phases and in all circumstances on data, here including statistical data.It is important for an insurance company that, through its programming for how they will achieve security, aware of the risks that may arise for them commensurable, ie probabilistic estimate them, so things will market the normally.In this way, for damage or for those that are outstanding or unreported or random propose a methodology based on which one who engages in this way to know what to do.

Suggested Citation

  • Bente Corneliu Cristian & Gavriletea Marius Dan, 2015. "Inflation Adjusted Chain Ladder Method," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 370-379, December.
    • Handle: RePEc:ora:journl:v:1:y:2015:i:2:p:370-379
    as

    Download full text from publisher

    File URL: http://anale.steconomiceuoradea.ro/volume/2015/n2/044.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Enrique de Alba, 2002. "Bayesian Estimation of Outstanding Claim Reserves," North American Actuarial Journal, Taylor & Francis Journals, vol. 6(4), pages 1-20.
    2. England, P.D. & Verrall, R.J., 2002. "Stochastic Claims Reserving in General Insurance," British Actuarial Journal, Cambridge University Press, vol. 8(3), pages 443-518, August.
    3. David Scollnik, 2001. "Actuarial Modeling with MCMC and BUGs," North American Actuarial Journal, Taylor & Francis Journals, vol. 5(2), pages 96-124.
    4. Marjorie Rosenberg & Virginia Young, 1999. "A Bayesian Approach to Understanding Time Series Data," North American Actuarial Journal, Taylor & Francis Journals, vol. 3(2), pages 130-143.
    5. Verrall, R.J., 1990. "Bayes and Empirical Bayes Estimation for the Chain Ladder Model," ASTIN Bulletin, Cambridge University Press, vol. 20(2), pages 217-243, November.
    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. Corneliu Cristian Bente, 2017. "Actuarial Estimation Of Technical Reserves In Insurance Companies. Basic Chain Ladder Method," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 227-234, July.
    2. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2016. "Stochastic loss reserving with dependence: A flexible multivariate Tweedie approach," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 63-78.
    3. Corneliu Cristian Bente, 2017. "Inflation Adjusted Chain Ladder Method As A Challenge To Actuaries," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 157-165, December.
    4. Verrall, R.J. & England, P.D., 2005. "Incorporating expert opinion into a stochastic model for the chain-ladder technique," Insurance: Mathematics and Economics, Elsevier, vol. 37(2), pages 355-370, October.
    5. Boratyńska, Agata, 2017. "Robust Bayesian estimation and prediction of reserves in exponential model with quadratic variance function," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 135-140.
    6. Gigante, Patrizia & Picech, Liviana & Sigalotti, Luciano, 2013. "Claims reserving in the hierarchical generalized linear model framework," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 381-390.
    7. Alessandro Ricotta & Edoardo Luini, 2019. "Bayesian Estimation of Structure Variables in the Collective Risk Model for Reserve Risk," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(2), pages 1-2.
    8. Han, Zhongxian & Gau, Wu-Chyuan, 2008. "Estimation of loss reserves with lognormal development factors," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 389-395, February.
    9. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
    10. de Andres-Sanchez, Jorge, 2007. "Claim reserving with fuzzy regression and Taylor's geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 40(1), pages 145-163, January.
    11. COSTA, JUAN IGNACIO BACCINO & DE ARMAS, GONZALO & Álvarez-Vaz, Ramón Dr., 2022. "Estudio De Algunos Métodos De Reservas Técnicas En Condiciones De Incertidumbre Para Seguros De No Vida (Study Of Some Methods Of Technical Reserves Under Conditions Of Uncertainty For Non-Life Insura," OSF Preprints 3pjr9, Center for Open Science.
    12. Gian Paolo Clemente & Nino Savelli & Diego Zappa, 2019. "Modelling Outstanding Claims with Mixed Compound Processes in Insurance," International Business Research, Canadian Center of Science and Education, vol. 12(3), pages 123-138, March.
    13. Crevecoeur, Jonas & Antonio, Katrien & Verbelen, Roel, 2019. "Modeling the number of hidden events subject to observation delay," European Journal of Operational Research, Elsevier, vol. 277(3), pages 930-944.
    14. D. Kuang & B. Nielsen & J. P. Nielsen, 2008. "Identification of the age-period-cohort model and the extended chain-ladder model," Biometrika, Biometrika Trust, vol. 95(4), pages 979-986.
    15. Koissi, Marie-Claire & Shapiro, Arnold F., 2006. "Fuzzy formulation of the Lee-Carter model for mortality forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 39(3), pages 287-309, December.
    16. Ihsan Chaoubi & Camille Besse & H'el`ene Cossette & Marie-Pier C^ot'e, 2022. "Micro-level Reserving for General Insurance Claims using a Long Short-Term Memory Network," Papers 2201.13267, arXiv.org.
    17. D. Kuang & B. Nielsen, 2018. "Generalized Log-Normal Chain-Ladder," Papers 1806.05939, arXiv.org.
    18. Bischofberger, Stephan M. & Hiabu, Munir & Mammen, Enno & Nielsen, Jens Perch, 2019. "A comparison of in-sample forecasting methods," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 133-154.
    19. Himchan Jeong & Dipak Dey, 2020. "Application of a Vine Copula for Multi-Line Insurance Reserving," Risks, MDPI, vol. 8(4), pages 1-23, October.
    20. Michal Gerthofer & Michal Pešta, 2017. "Stochastic Claims Reserving in Insurance Using Random Effects," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(5), pages 542-560.

    More about this item

    Keywords

    claims reserving; chain-ladder method; damages; premium rates.;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    Statistics

    Access and download statistics

    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:ora:journl:v:1:y:2015:i:2:p:370-379. 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: Catalin ZMOLE (email available below). General contact details of provider: https://edirc.repec.org/data/feoraro.html .

    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.