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Atatalab, Fatemeh, Payandeh Najafabadi, Amir. (1400). Prediction of outstanding IBNR liabilities using delay probability. سامانه مدیریت نشریات علمی, 1(2), 37-47. doi: 10.22054/jmmf.2021.13839
Fatemeh Atatalab; Amir Teimour Payandeh Najafabadi. "Prediction of outstanding IBNR liabilities using delay probability". سامانه مدیریت نشریات علمی, 1, 2, 1400, 37-47. doi: 10.22054/jmmf.2021.13839
Atatalab, Fatemeh, Payandeh Najafabadi, Amir. (1400). 'Prediction of outstanding IBNR liabilities using delay probability', سامانه مدیریت نشریات علمی, 1(2), pp. 37-47. doi: 10.22054/jmmf.2021.13839
Atatalab, Fatemeh, Payandeh Najafabadi, Amir. Prediction of outstanding IBNR liabilities using delay probability. سامانه مدیریت نشریات علمی, 1400; 1(2): 37-47. doi: 10.22054/jmmf.2021.13839

Prediction of outstanding IBNR liabilities using delay probability

Journal of Mathematics and Modeling in Finance
دوره 1، شماره 2، اسفند 2021، صفحه 37-47    اصل مقاله (396.69 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22054/jmmf.2021.13839
نویسندگان
Fatemeh Atatalab1؛ Amir Teimour Payandeh Najafabadi* 2
1Department of Actuarial Science, Shahid Beheshti University, Theran, Iran
2Department of Actuarial Science, Shahid Beheshti University, Tehran, Iran
چکیده
‎An important question in non life insurance research is the ‎estimation of number of future payments and corresponding ‎amount of them. A ‎loss reserve is the money set aside by insurance companies to pay ‎policyholders claims on their policies. The policyholder behavior for reporting claims after its ‎occurrence have significant effect on the costs of the insurance ‎company. This article considers the problem of predicting the amount and number ‎of claims that have been incurred but not reported, ‎say IBNR‎. ‎Using the delay probabilities in monthly level, ‎calculated by the Zero Inflated Gamma Mixture distribution, ‎it predicts IBNR's‎ ‎loss reserve. ‎‎The model advantage in the IBNR reserve is insurers can predict ‎the number of future claims for each future date. ‎This enables ‎them to change the claim reporting process. The practical applications of our findings are applied against a third party liability (TPL) insurance loss portfolio. Additional information about claim can be considered in the loss reserving ‎model and making the prediction of amount more accurate.
کلیدواژه‌ها
Insurance؛ ‎ Loss reserve؛ EM algorithm؛ Zero-Inflated Gamma Mixture distribution
مراجع
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