Employee Benefits Program Valuation with Multiple Decrement Model Based on PSAK 24 Post-COVID-19 Pandemic

Wahyuni Ekasasmita, Nur Rahmi, M. Fauzan Iskandar

Abstract


In this article, we evaluate the post-labor compensation program based on PSAK-24 in the new normal era of the COVID-19 pandemic. In order to create a table multiple decrements based on a single table decrement namely, death, withdrawal, total permanent disability, and retirement. In the new normal era of the COVID-19 pandemic, the benefits of death, death caused by COVID-19, withdrawal, total permanent disability, and retirement were then aggregated. The method used in this study is a quantitative method with a case study approach of COVID-19. The data used is secondary data on the number of COVID-19 positive cases in Indonesia from January 2021 to December 2022. In this study, an actuarial model, the Multiple Decrement Model, was applied to calculate the valuation of the post-labor compensation program based on PSAK-24 using five decrements as the cause of claims consisting of death, death cause of COVID-19, withdrawal, total permanent disability and retirement. The calculation results that can be seen that large annual net premiums multiple decrement cases that provide benefits according to the cause of failure getting bigger as that person gets older.

 


Keywords


Employee Benefit Program; Multiple Decrement Model; Post COVID-19.

Full Text:

DOWNLOAD [PDF]

References


Academy of Actuaries, A. (2004). Fundamentals of Current Pension Funding and Accounting For Private Sector Pension Plans.

Angkasa, A. P., Lestari, D., & Devila, S. (2021). Comparison of entry age normal and projected unit credit method for funding of defined benefit pension plan. AIP Conference Proceedings, 2374. https://doi.org/10.1063/5.0059248

Anthropelos, M., & Blontzou, E. (2023). On Valuation and Investments of Pension Plans in Discrete Incomplete Markets. Risks, 11(6), 103. https://doi.org/10.3390/risks11060103

Barigou, K., Loisel, S., & Salhi, Y. (2020). Parsimonious Predictive Mortality Modeling by Regularization and Cross-Validation with and without Covid-Type Effect †. https://doi.org/10.3390/risks901

Bateman, H., Dobrescu, L. I., Liu, J., Newell, B. R., & Thorp, S. (2023). Determinants of early-access to retirement savings: Lessons from the COVID-19 pandemic. Journal of the Economics of Ageing, Vol.24. https://doi.org/10.1016/j.jeoa.2023.100441

Bayar, Y., Gavriletea, M. D., Danuletiu, D. C., Danuletiu, A. E., & Sakar, E. (2022). Pension Funds, Insurance Companies and Stock Market Development: Evidence from Emerging Markets. Mathematics, Vol. 10. Issue 13 https://doi.org/10.3390/math10132335

Boado-Penas, M. C., Brinker, L. V., Eisenberg, J., & Korn, R. (2023). Managing reputational risk in the decumulation phase of a pension fund. Insurance: Mathematics and Economics, Vol.109, pages 52–68. https://doi.org/10.1016/j.insmatheco.2022.12.005

Deshmukh, S. (2012). Multiple decrement models in insurance: An introduction using R. In Multiple Decrement Models in Insurance: An Introduction Using R. Springer India. https://doi.org/10.1007/978-81-322-0659-0

Financial Accounting Standards Board, I. of I. C. A. (2010). Pernyataan Standar Akuntansi keuangan Imbalan Kerja.

Ekasasmita, W. (2015). Model Multi Status Untuk Menentukan Premi Asuransi Critical Illness. Universitas Gadjah Mada. https://etd.repository.ugm.ac.id/penelitian/detail/88567

Ekasasmita, W., Bahri, M., Bachtiar, N., Rahim, A., & Nur, M. (2023). One-Dimensional Quaternion Fourier Transform with Application to Probability Theory. Symmetry, 15(4), 815. https://doi.org/10.3390/sym15040815

Goto, S., & Yanase, N. (2021). Pension return assumptions and shareholder-employee risk-shifting. Journal of Corporate Finance, Vol.70. https://doi.org/10.1016/j.jcorpfin.2021.102047

Idrovo-Aguirre, B. J., & Contreras-Reyes, J. E. (2021). Monetary fiscal contributions to households and pension fund withdrawals during the COVID-19 pandemic: An approximation of their impact on construction labor supply in chile. Social Sciences, Vol.10, Issue 11. https://doi.org/10.3390/socsci10110417

Jaiswal, K. M., Dudhgaonkar, S., Gharade, P., & Sharma, N. (2022). Post-valuation quality check of multiple-choice questions. International Journal of Basic & Clinical Pharmacology, 12(1), 43. https://doi.org/10.18203/2319-2003.ijbcp20223353

Josa-Fombellida, R., & Navas, J. (2020a). Time consistent pension funding in a defined benefit pension plan with non-constant discounting. Insurance: Mathematics and Economics, Vol. 94, pages 142–153. https://doi.org/10.1016/j.insmatheco.2020.07.007

Lee, H., Ahn, J. Y., & Ko, B. (2019). Construction of multiple decrement tables under generalized fractional age assumptions. Computational Statistics and Data Analysis, Vol. 133, pages 104–119. https://doi.org/10.1016/j.csda.2018.09.004

Ma, & Zhien. (2009). Dynamical Modeling and Analysis of Epidemics. https://books.google.co.id/books?hl=id&lr=&id=LT5kDQAAQBAJ&oi=fnd&pg=PR5&dq=Ma,+%26+Zhien.+(2009).+Dynamical+Modeling+and+Analysis+of+Epidemics.&ots=57gMbzVGUG&sig=1SaQunpkgwtt1ZiGOiptJCyr8fc&redir_esc=y#v=onepage&q=Ma%2C%20%26%20Zhien.%20(2009).%20Dynamical%20Modeling%20and%20Analysis%20of%20Epidemics.&f=false

Marska-Dzioba, N., & Barczak, A. (2022). Impact of COVID-19 on the Disability Fund in Poland. Sustainability (Switzerland), Vol. 14, Issue 19. https://doi.org/10.3390/su141912914

Nur, S., Daulay, R., Apriva Hidayana, R., & Halim, N. A. (2022). Pension Fund Calculation Using Traditional and Projected Unit Credit Methods for Total Actuarial Liability and Normal Cost Cases. 3(4), 132–135. http://iorajournal.org/indx.php/orics/index

Petraki, A., & Zalewska, A. (2015). Jumping over a low hurdle: Personal pension fund performance. http://ssrn.com/abstract=2250847Electroniccopyavailableat:http://ssrn.com/abstract=2250847

Shang, Y., Qi, P., Chen, H., Yang, Q., & Chen, Y. (2022). COVID-19 and its impact on tourism sectors: implications for green economic recovery. Economic Change and Restructuring. https://doi.org/10.1007/s10644-022-09456-7

Strumskis, M., & Balkevičius, A. (2016). Pension fund participants and fund managing company shareholder relations in Lithuania second pillar pension funds. Intellectual Economics, 10(1), 1–12. https://doi.org/10.1016/j.intele.2016.06.004

Walk, D., Haviv, N., Hasisi, B., & Weisburd, D. (2021). The role of employment as a mediator in correctional education’s impact on recidivism: A quasi-experimental study of multiple programs. Journal of Criminal Justice, Vol. 74. https://doi.org/10.1016/j.jcrimjus.2021.101815

Wang, P., Zheng, X., Li, J., & Zhu, B. (2020). Prediction of epidemic trends in COVID-19 with logistic model and machine learning technics. Chaos, Solitons and Fractals, 139. https://doi.org/10.1016/j.chaos.2020.110058

Williams, H., Guh, S., Barrack, A., Boss, K., & Nigam, S. (2018). Long-Term Benefits of Employee Wellness Programs: A Blue Cross Blue Shield of Louisiana (BCBSLA) Case Study. Value in Health, 21, S140. https://doi.org/10.1016/j.jval.2018.04.946

Zhang, L., Zhang, H., & Yao, H. (2018). Optimal investment management for a defined contribution pension fund under imperfect information. Insurance: Mathematics and Economics, Vol.79, pages 210–224. https://doi.org/10.1016/j.insmatheco.2018.01.007




DOI: https://doi.org/10.31764/jtam.v8i1.17417

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Wahyuni Ekasasmita, Nur Rahmi, M. Fauzan Iskandar

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

_______________________________________________

JTAM already indexing:

                     


_______________________________________________

 

Creative Commons License

JTAM (Jurnal Teori dan Aplikasi Matematika) 
is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

______________________________________________

_______________________________________________

_______________________________________________ 

JTAM (Jurnal Teori dan Aplikasi Matematika) Editorial Office: