6 citations · 12 across the 11 of their papers we have counts for
10 papers · 1 filter
Can a small additional claim lower the premium? Credibility orders for collective risk models
Jihyun Park, Jieun Kim, Taehan Bae +1
The collective risk model is a fundamental framework in insurance ratemaking for modeling aggregate losses by combining claim frequency and claim severity components. A key structu…
A simple Bayesian state-space model for the collective risk model
Jae Youn Ahn, Himchan Jeong, Yang Lu
The collective risk model (CRM) for frequency and severity is an important tool for retail insurance ratemaking, macro-level catastrophic risk forecasting, as well as operational r…
On the ordering of credibility factors
Jae Youn Ahn, Himchan Jeong, Yang Lu
Traditional credibility analysis of risks in insurance is based on the random effects model, where the heterogeneity across the policyholders is assumed to be time-invariant. One p…
Optimal relativities in a modified Bonus-Malus system with long memory transition rules and frequency-severity dependence
Jae Youn Ahn, Eric C. K. Cheung, Rosy Oh +1
In the classical Bonus-Malus System (BMS) in automobile insurance, the premium for the next year is adjusted according to the policyholder's claim history (particularly frequency)…
On a Multi-Year Microlevel Collective Risk Model
Rosy Oh, Himchan Jeong, Jae Youn Ahn +1
For a typical insurance portfolio, the claims process for a short period, typically one year, is characterized by observing frequency of claims together with the associated claims…
Designing a Bonus-Malus system reflecting the claim size under the dependent frequency-severity model
Rosy Oh, Joseph H. T. Kim, Jae Youn Ahn
In auto insurance, a Bonus-Malus System (BMS) is commonly used as a posteriori risk classification mechanism to set the premium for the next contract period based on a policyholder…
Predictive Risk Analysis in Collective Risk Model: Choices between Historical Frequency and Aggregate Severity
Rosy Oh, Youngju Lee, Dan Zhu +1
Typical risk classification procedure in insurance is consists of a priori risk classification determined by observable risk characteristics, and a posteriori risk classification w…
Double-Counting Problem of the Bonus-Malus System
Rosy Oh, Kyung Suk Lee, Sojung C. Park +1
The bonus-malus system (BMS) is a widely used premium adjustment mechanism based on policyholder's claim history. Most auto insurance BMSs assume that policyholders in the same bon…
On Copula-based Collective Risk Models
Rosy Oh, Jae Youn Ahn, Woojoo Lee
Several collective risk models have recently been proposed by relaxing the widely used but controversial assumption of independence between claim frequency and severity. Approaches…
Implementation of Frequency-Severity Association in BMS Ratemaking
Rosy Oh, Peng Shi, Jae Youn Ahn
A Bonus-Malus System (BMS) in insurance is a premium adjustment mechanism widely used in a posteriori ratemaking process to set the premium for the next contract period based on a…