Tweedie double GLM loss triangles with dependence within and across business lines
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| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20220008044 | ||
| 003 | MAP | ||
| 005 | 20220310171111.0 | ||
| 008 | 220310e20211206esp|||p |0|||b|spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20220002479$aAraiza Iturria, Carlos Andrés | |
| 245 | 1 | 0 | $aTweedie double GLM loss triangles with dependence within and across business lines$cCarlos Andrés Araiza Iturria, Frédéric Godin, Mélina Mailhot |
| 520 | $aWe propose a stochastic model allowing property and casualty insurers with multiple business lines to measure their liabilities for incurred claims risk and calculate associated capital requirements. Our model includes many desirable features which enable reproducing empirical properties of loss ratio dynamics. For instance, our model integrates a double generalized linear model relying on accident semester and development lag effects to represent both the mean and dispersion of loss ratio distributions, an autocorrelation structure between loss ratios of the various development lags, and a copula-based aggregation of risks model driving the dependence across the various business lines. Our work is the first in the literature to combine all such advantageous features within a loss triangle model. The model allows for a joint simulation of loss triangles and the quantification of the overall portfolio risk through risk measures. Consequently, a diversification benefit associated with the economic capital requirements can be measured, in accordance with IFRS 17 standards which allow for the recognition of such benefit. The allocation of capital across business lines based on the Euler allocation principle is then illustrated. The implementation of our model is performed by estimating its parameters based on a car insurance data obtained from the General Insurance Statistical Agency (GISA), and by conducting numerical simulations whose results are then presented | ||
| 650 | 4 | $0MAPA20080586447$aModelo estocástico | |
| 650 | 4 | $0MAPA20080570651$aSiniestralidad | |
| 700 | 1 | $0MAPA20180010583$aGodin, Fréderic | |
| 700 | 1 | $0MAPA20200006664$aMailhot, Mélina | |
| 773 | 0 | $wMAP20220007085$g06/12/2021 Volúmen 11 - Número 2 - diciembre 2021 , p. 619-653$tEuropean Actuarial Journal$dCham, Switzerland : Springer Nature Switzerland AG, 2021-2022 |