scholarly journals Adverse Selection Spirals

2006 ◽  
Vol 36 (2) ◽  
pp. 589-628
Author(s):  
Piet De Jong ◽  
Shauna Ferris

This article discusses risk classification and develops and discusses a framework for estimating the effects of restrictions on risk classification. It is shown that expected losses due to adverse selection depend only on means, variances and covariances of insurance factors and rates of uptake of insurance. Percentage loadings required to avoid losses are displayed. Correlated information, such as family history, is also incorporated and it is seen how such information limits losses and decreases required loadings. Although the evidence suggests that adverse selection is not, at present, a severe problem for insurers, this might change if the authorities impose restrictions on risk classification and/or customers gain an informational advantage (such as better knowledge of their own risk levels). Application is made to unisex annuity pricing in the UK insurance market.

2006 ◽  
Vol 36 (02) ◽  
pp. 589-628 ◽  
Author(s):  
Piet De Jong ◽  
Shauna Ferris

This article discusses risk classification and develops and discusses a framework for estimating the effects of restrictions on risk classification. It is shown that expected losses due to adverse selection depend only on means, variances and covariances of insurance factors and rates of uptake of insurance. Percentage loadings required to avoid losses are displayed. Correlated information, such as family history, is also incorporated and it is seen how such information limits losses and decreases required loadings. Although the evidence suggests that adverse selection is not, at present, a severe problem for insurers, this might change if the authorities impose restrictions on risk classification and/or customers gain an informational advantage (such as better knowledge of their own risk levels). Application is made to unisex annuity pricing in the UK insurance market.


2016 ◽  
Vol 46 (2) ◽  
pp. 265-291 ◽  
Author(s):  
MingJie Hao ◽  
Angus S. Macdonald ◽  
Pradip Tapadar ◽  
R. Guy Thomas

AbstractThis paper investigates equilibrium in an insurance market where risk classification is restricted. Insurance demand is characterised by an iso-elastic function with a single elasticity parameter. We characterise the equilibrium by three quantities: equilibrium premium; level of adverse selection (in the economist's sense); and “loss coverage”, defined as the expected population losses compensated by insurance. We consider both equal elasticities for high and low risk-groups, and then different elasticities. In the equal elasticities case, adverse selection is always higher under pooling than under risk-differentiated premiums, while loss coverage first increases and then decreases with demand elasticity. We argue that loss coverage represents the efficacy of insurance for the whole population; and therefore that if demand elasticity is sufficiently low, adverse selection is not always a bad thing.


2004 ◽  
Author(s):  
Mattias K. Polborn ◽  
Michael Hoy ◽  
Asha Sadanand

2015 ◽  
Vol 20 (2) ◽  
pp. 348-365

This abstract relates to the following paper: AdamsC.Adverse selection in a start-up long-term care insurance market. British Actuarial Journal. doi:10.1017/S1357321714000270


2020 ◽  
pp. 097215092093228
Author(s):  
Zahra Shams Esfandabadi ◽  
Meisam Ranjbari ◽  
Simone Domenico Scagnelli

An efficient risk-level prediction for newly proposed insurance policies plays a significant role in the survival of companies in the highly competitive insurance market. In Iran, risk assessment in comprehensive automobile insurance, which is a part of motor insurance, is only based on the vehicle attributes without proper consideration of personal and behavioural characteristics of driver(s). As a result, pricing is unfair in most of the cases and this can put insurance companies in an unfavourable financial position due to attracting high-risk drivers instead of low-risk ones. In this scenario, to identify and prioritize important factors affecting risk levels and to move towards a fair ratemaking, a two-phase process based on fuzzy Delphi method (FDM) and fuzzy analytic hierarchy process (FAHP) is proposed in this research. Additionally, similarity aggregation method (SAM) is applied to combine the individual fuzzy opinions of the surveyed experts into a group fuzzy consensus opinion. The results of this empirical study contribute to the insurance market of Iran by proposing appropriate weighting of the relevant risk factors to support stakeholders and policymakers for assessing risks more accurately, as well as designing more effective databases and insurance proposal forms.


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