Micro-level stochastic loss reserving for general insurance

By Katrien Antonio, R. Plat. 2012

154 citations recorded by the source corpus.

Subfields: Demography, Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/6fcc3f21ab7c65ee3ab637ab13ef9801786afc28

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Demography

1. Katrien Antonio
2. Andrei L. Badescu

In Economics and Econometrics

1. Katrien Antonio
2. Andrei L. Badescu

In Management Science and Operations Research

1. Roel Verbelen
2. Sheldon Lin
3. Lan Gong
4. Katrien Antonio
5. Andrei L. Badescu

Citations in the corpus

• FITTING MIXTURES OF ERLANGS TO CENSORED AND TRUNCATED DATA USING THE EM ALGORITHM (2015, methodology): “Censored and truncated data occur in the context of claim reserving as well (Antonio and Plat, 2014). Indeed, the reserving actuary wants to predict the future development of claims when setting aside reserves at the present moment and has to deal with claims being reported but not yet settled (RBNS”