Micro-level VS macro-level reserving in non-life insurance: why and when?

Olivier Lopez (1) , Xavier Milhaud (2, 3) , Pierre-Emmanuel Thérond (4, 3)

1 SU - Sorbonne Université
2 Laboratoire de Finance et d'Assurance
3 SAF - Laboratoire de Sciences Actuarielle et Financière
4 Galea & Associés

In non-life insurance, business sustainability requires accurate and robust predictions of reserves related to unpaid claims. To this aim, two different approaches have historically been developed: aggregated loss triangles and individual claim reserving. The former has reached operational great success in the past decades, whereas the use of the latter still remains very limited. Through two illustrative examples and introducing a new tree-based algorithm, we show, not surprisingly, that individual claim reserving is really promising in the context of long-term risks.

Mots clés: reserving; long-tail; censoring; regression tree; non-life insurance

Domaines: Statistiques [math.ST]

Olivier Lopez, Xavier Milhaud, Pierre-Emmanuel Thérond. Micro-level VS macro-level reserving in non-life insurance: why and when?. 2018. ⟨hal-01868744v1⟩