Empirical Investigation of Life Settlements: The Secondary Market for Life Insurance Policies

2013 ◽  
Author(s):  
Afonso V. Januario ◽  
Narayan Y. Naik
Keyword(s):  
Life Insurance ◽  
Empirical Investigation ◽  
Secondary Market ◽  
Insurance Policies ◽  
Life Settlements

Assessing the Impact of Suicide Exclusion Periods on Life Insurance

Crisis ◽  
2010 ◽  
Vol 31 (4) ◽  
pp. 217-223 ◽  
Author(s):  
Paul Yip ◽  
David Pitt ◽  
Yan Wang ◽  
Xueyuan Wu ◽  
Ray Watson ◽  
...  
Keyword(s):  
Life Insurance ◽  
Accidental Death ◽  
Insurance Policy ◽  
Death Rates ◽  
Insurance Policies ◽  
Suicidal Death ◽  
Insured Individual ◽  
The Impact ◽  
Insurance Data ◽  
The Relationship

Background: We study the impact of suicide-exclusion periods, common in life insurance policies in Australia, on suicide and accidental death rates for life-insured individuals. If a life-insured individual dies by suicide during the period of suicide exclusion, commonly 13 months, the sum insured is not paid. Aims: We examine whether a suicide-exclusion period affects the timing of suicides. We also analyze whether accidental deaths are more prevalent during the suicide-exclusion period as life-insured individuals disguise their death by suicide. We assess the relationship between the insured sum and suicidal death rates. Methods: Crude and age-standardized rates of suicide, accidental death, and overall death, split by duration since the insured first bought their insurance policy, were computed. Results: There were significantly fewer suicides and no significant spike in the number of accidental deaths in the exclusion period for Australian life insurance data. More suicides, however, were detected for the first 2 years after the exclusion period. Higher insured sums are associated with higher rates of suicide. Conclusions: Adverse selection in Australian life insurance is exacerbated by including a suicide-exclusion period. Extension of the suicide-exclusion period to 3 years may prevent some “insurance-induced” suicides – a rationale for this conclusion is given.

Computing Risk Measures of Life Insurance Policies through the Cox–Ross–Rubinstein Model

2018 ◽  
Keyword(s):  
Monte Carlo ◽  
Life Insurance ◽  
Risk Measures ◽  
Probability Measures ◽  
Time Interval ◽  
Change Of Measure ◽  
Insurance Policies ◽  
Straightforward Application ◽  
The Monte Carlo Method ◽  
Remaining Time

The problem of computing risk measures of life insurance policies is complicated by the fact that two different probability measures, the real-world probability measure along the risk horizon and the risk-neutral one along the remaining time interval, have to be used. This implies that a straightforward application of the Monte Carlo method is not available and the need arises to resort to time consuming nested simulations or to the least squares Monte Carlo approach. We propose to compute common risk measures by using the celebrated binomial model of Cox, Ross, and Rubinstein (1979) (CRR). The main advantage of this approach is that the usual construction of the CRR model is not influenced by the change of measure and a unique lattice can be used along the whole policy duration. Numerical results highlight that the proposed algorithm computes highly accurate values.

A Study on Risk-Return Characteristics of Life Insurance Policies

2007 ◽  
Author(s):  
Mihir Dash ◽  
Lalremtluangi C. ◽  
Snimer Atwal ◽  
Supriya Thapar
Keyword(s):  
Life Insurance ◽  
Risk Return ◽  
Insurance Policies
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