I know that I don’t know what you do
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I know that I don’t know what you do Informational asymmetry from the insurer’s point of view Orsolya Rétallér Corvinus University of Budapest
description
I know that I don’t know what you do. Informational asymmetry from the insurer’s point of view Orsolya Rétallér Corvinus University of Budapest. Theoretical background. Informational asymmetry in the insurance market. Competitive market – single period (Rotschild and Stiglitz, 1976) - PowerPoint PPT Presentation
Transcript of I know that I don’t know what you do
I know that I don’t know what you doInformational asymmetry from the insurer’s point of viewOrsolya RétallérCorvinus University of Budapest
Theoretical background
TÁMOP-4.2.2/B-10/1-2010-0023
Informational asymmetry in the insurance market• Competitive market – single period
(Rotschild and Stiglitz, 1976)• Monopol market – single period
(Stiglitz, 1977)• Competitive market – multi period
(Cooper and Hayes, 1987 and Kuntreuther and Pauly, 1985)• Monopol market – multi period
(Dionne, 1983 and Dionne and Lassere, 1985)
My goal:
Making adverse se
lection visib
le
Assumptions
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General Assumptions• No influence on the risk• Insurance is not mandatory• Insurer is in monopol position• Initial number of policyholders• Policyholders are not distinguished• Insured asset worth 1• Maximum number of losses per year: 1• Amount of loss is independent from the number of losses• 10 period of time
Model structure
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Permanent data• Continuous Risk• Type of Risk• Discrete Risk
Period-dependent data• Policyholder Dummy• Presumed Risk• Loss Dummy• Amount of Loss• Actual Risk
A series of simulations
Initial number of policyholders: 1,000
Premium principle: net premium principle
Maximal risk: 100%
Premium tolerance: 5%
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Initial Frequencies Distribution of Amount of Losses
Moral Hazard Policyholder’s Risk Assumption
Adverse Selection Model
A series of simulations
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Initial Frequencies Distribution of Amount of Losses
Moral Hazard Policyholder’s Risk Assumption
Adverse Selection Model
• Not specified1• 80-5-5-5-5%2• 5-5-5-5-80%3
A series of simulations
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Initial Frequencies Distribution of Amount of Losses
Moral Hazard Policyholder’s Risk Assumption
Adverse Selection Model
A series of simulations
• Bernoulli1• Pareto2• Gamma3• Lognormal4
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Initial Frequencies Distribution of Amount of Losses
Moral Hazard Policyholder’s Risk Assumption
Adverse Selection Model
• No moral hazard1• Significant moral hazard2
A series of simulations
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Initial Frequencies Distribution of Amount of Losses
Moral Hazard Policyholder’s Risk Assumption
Adverse Selection Model
• Aware of the risk1• Developing over time2
A series of simulations
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H4H1 H2H3The number of policyholders is decreasing over time.
The premium is increasing over time.The cumulative profit for 10
periods is negative.
The lower the discrete risk is, the faster the group terminates the contract.
Hypotheses
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ResultsInitial Frequencies
1 2 3 4 502468
10
Fall-out by typesNot specified initial
frequencies
Type
Num
ber
of p
erio
ds
1 2 3 4 502468
10
Fall-out by types80-5-5-5-5%
Type
Num
ber
of p
erio
ds
1 2 3 4 502468
10
Fall-out by types5-5-5-5-80%
Type
Num
ber
of p
erio
ds
1 2 3 4 5 6 7 8 9 100
200400600800
1000
Number of PolicyholdersBernoulli Distribution
Number of periodsNum
ber
of P
olic
yhol
ders
1 2 3 4 5 6 7 8 9 100
200400600800
1000
Number of PolicyholdersGamma Distribution
Number of periodsNum
ber
of P
olic
yhol
ders
1 2 3 4 5 6 7 8 9 100
200400600800
1000
Number of PolicyholdersPareto Distribution
Number of periodsNum
ber
of P
olic
yhol
ders
1 2 3 4 5 6 7 8 9 100
200400600800
1000
Number of PolicyholdersLognormal Distribution
Number of periodsNum
ber
of P
olic
yhol
ders
ResultsDistribution of Amount of Losses
2 3 4 5 6 7 8 9 1000.20.40.60.8
1
PremiumNo Moral Hazard
Number of periods
Prem
ium
2 3 4 5 6 7 8 9 1000.20.40.60.8
1
PremiumSignificant Moral Hazard
Number of periods
Prem
ium
ResultsMoral Hazard
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1 2 3 4 5 6 7 8 9 10750800850900950
1000
Number of PolicyholdersAware of the Risk
Number of periodsNum
ber
of P
olic
yhol
ders
1 2 3 4 5 6 7 8 9 10750800850900950
1000
Number of PolicyholdersDeveloping over time
Number of periodsNum
ber
of P
olic
yhol
ders
ResultsPolicyholders’ Risk Assumptions
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H1The number of policyholders is decreasing over time.
Results of Hypotheses
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1 2 3 4 5 6 7 8 9 10750800850900950
1000
Number of PolicyholdersAware of the Risk
Number of periodsNum
ber
of P
olic
yhol
ders
1 2 3 4 5 6 7 8 9 10750800850900950
1000
Number of PolicyholdersDeveloping over time
Number of periodsNum
ber
of P
olic
yhol
ders
ResultsPolicyholders’ Risk Assumptions
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H1The number of policyholders is decreasing over time.
Results of Hypotheses
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H2The premium is increasing over time.
Results of Hypotheses
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2 3 4 5 6 7 8 9 100.470.480.490.5
0.510.520.530.540.550.560.57
Premiumwhen the policyholders’ risk
assumption is developing over time
Number of periods
Prem
ium
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H2The premium is increasing over time.
Results of Hypotheses
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H3The cumulative profit for 10 periods is negative.
Results of Hypotheses
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2 3 4 5 6 7 8 9 10
-2
-1
0
1
2
3
4
Profitwhen the majority of the policyholders
is in the low risk type
Number of periods
Profi
t
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H3The cumulative profit for 10 periods is negative.
Results of Hypotheses
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H4The lower the discrete risk is, the faster the group terminates the contract.
Results of Hypotheses
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ResultsInitial Frequencies
1 2 3 4 502468
10
Fall-out by typesNot specified initial
frequencies
Type
Num
ber
of p
erio
ds
1 2 3 4 502468
10
Fall-out by types80-5-5-5-5%
Type
Num
ber
of p
erio
ds
1 2 3 4 502468
10
Fall-out by types5-5-5-5-80%
Type
Num
ber
of p
erio
ds
H4The lower the discrete risk is, the faster the group terminates the contract.
Results of Hypotheses
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Conclusions
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• Adverse selection might have major influences on the• Number of policyholders• Premium• Loss expenses• Premium income• Profit
• Gender directive – role of adverse selection is enhancing• Simulations as tools for observing adverse selection
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To download my paper and model please visit:
TÁMOP-4.2.2/B-10/1-2010-0023
https://sites.google.com/site/orsiretaller/kutatas-research
