skip to main content

ESTIMATION OF IBNR AND RBNS RESERVES USING RDC METHOD AND GAMMA GENERALIZED LINEAR MODEL

*Tiara Yulita  -  Actuary Study Program, Sumatera Institute of Technology, Indonesia
Adhitya Ronnie Effendie  -  Mathematics Study Program, Gadjah Mada University, Indonesia
Open Access Copyright (c) 2022 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract

Estimation of claims reserves is a very important role for insurance companies because the information will be used to assess the insurance company’s ability to meet future claim payment obligations. In practice, claims reserves are divided into two Incurred but Not Reported (IBNR) and Reported but Not Settled (RBNS). Reserving by Detailed Conditioning (RDC) is one of the individual methods that can estimate claims reserves of both the IBNR and RBNS, which involves detailed condition so-called claim characteristics, and some information else so-called background variable. The result of estimating claims reserves using RDC with background variable is not stable because many combinate of calculation from each background variable. The purpose of this study is to overcome these problems, which we can combine RDC and Gamma Generalized Linear Model (GLM) as an effective method for estimating claims reserves. By using Bootstrapping Individual Claims Histories (BICH) method, the results show that estimation of claims reserves using RDC and Gamma GLM gives the fewest value of Mean Square Error of Prediction (MSEP) rather than RDC with Poisson GLM, RDC, and Chain Ladder. Where the smaller the value of the resulting MSEP estimate, the closer to the actual claim reserve value.

Fulltext View|Download
Keywords: IBNR; RBNS; RDC; Gamma Generalized Linear Models; Reserves
Funding: INSTITUT TEKNOLOGI SUMATERA

Article Metrics:

  1. Brostrom, G. (2020). glmmML: Generalized Linear Models With Clustering. Http://Cran. r-Project. Org/Web/Packages/GlmmML/Index. Html
  2. De Jong, P., & Heller, G. Z. (2008). Generalized Linear Models for Insurance Data. Cambridge Books
  3. Drieskens, D., Henry, M., Walhin, J. F., & Wielandts, J. (2012). Stochastic Projection for Large Individual Losses. In Scandinavian Actuarial Journal (Issue 1). https://doi.org/10.1080/03461231003759708
  4. Effendie, A., & Pebriawan, R. (2017). Estimation of IBNR and RBNS Reserve by Detailed Conditioning Method. Far East Journal of Mathematical Sciences (FJMS), 101, 2785–2801. https://doi.org/10.17654/MS101122785
  5. Godecharle, E., & Antonio, K. (2015). Reserving by Conditioning on Markers of Individual Claims: A Case Study Using Historical Simulation. North American Actuarial Journal, 19(4), 273–288. https://doi.org/10.1080/10920277.2015.1046607
  6. Kartikasari, M. D., Effendie, A. R., & Wilandari, Y. (2017). Reserving by Detailed Conditioning on Individual Claim. AIP Conference Proceedings, 1827(March 2017). https://doi.org/10.1063/1.4979428
  7. Kroon, R. (2014). Individual Reserving by Detailed Conditioning - A Parametric Approach
  8. McCulloch, C. E., & Searle, S. R. (2004). Generalized, Linear, and Mixed Models. John Wiley & Sons
  9. Mutaqin, A. K., Tampubolon, D. R., & Darwis, S. (2008). Run-off Triangle Data dan Permasalahannya. Statistika, 8(1), 55–59
  10. Ohlsson, E., & Johansson, B. (2010). Non-Life Insurance Pricing with Generalized Linear Models
  11. Pigeon, M., Antonio, K., & Denuit, M. (2014). Individual Loss Reserving using Paid-Incurred Data. Insurance: Mathematics and Economics, 58(1), 121–131. https://doi.org/10.1016/j.insmatheco.2014.06.012
  12. Rosenlund, S. (2012). Bootstrapping Individual Claim Histories. ASTIN Bulletin: The Journal of the IAA, 42(1), 291–324. https://doi.org/10.2143/AST.42.1.2160744
  13. Rosenlund, S. (2021). Rapp: The Free Actuarial Language. Https://Www.Stigrosenlund.Se/Rapp.Htm
  14. Sunandi, E., Notodiputro, K. A., & Sartono, B. (2022). a Study of Generalized Linear Mixed Model for Count Data Using Hierarchical Bayes Method. Media Statistika, 14(2), 194–205. https://doi.org/10.14710/medstat.14.2.194-205
  15. Verrall, R., Nielsen, J. P., & Jessen, A. H. (2010). Prediction of RBNS and IBNR Claims Using Claim Amounts and Claim Counts. ASTIN Bulletin, 40(02), 871–887. https://doi.org/10.2143/AST.40.2.2061139
  16. Wilandari, Y., Gunardi, & Effendie, A. R. (2021). Estimasi Cadangan Klaim Menggunakan Metode Deterministik dan Stokastik. Jurnal Statistika, 9(1)
  17. Wüthrich, M. V, & Merz, M. (2008). Stochastic Claims Reserving Methods in Insurance (Vol. 435). John Wiley & Sons

Last update:

No citation recorded.

Last update: 2024-12-11 01:26:01

No citation recorded.