Individual Policyholder Research Articles

Urban flooding and ground‐related homes in Canada: an overview

AbstractUrban flooding associated with extreme precipitation is a significant cause of disaster damages for municipalities, homeowners and insurers in Canada. Several approaches have been applied to reduce urban flood risk at the municipal and homeowner scales, including addressing inflow/infiltration in wastewater systems, accommodating extreme stormwater flows in subdivision design and protecting individual homes from flooding. Insurers have also engaged in managing urban flood risk through interactions with individual policyholders and initiatives aimed at better understanding urban flood risk and risk mitigation options. Requiring mitigation measures at the time of the construction of homes, improving insurance data, application of incentives for appropriate private side retrofits, and improved collaboration between insurers and municipalities for identification of urban flood risk areas provide additional opportunities for urban flood risk reduction. Further, senior levels of governments should support inflow/infiltration reduction and application of climate change information to improve the planning and design of municipal infrastructure.

Does Cognitive Ability Impact Life Insurance Policy Lapsation?

Life insurance is an important household risk management and financial tool. Policy lapsation has economic effects on life insurance companies, policyholders, and beneficiaries and the impact may be detrimental when these lapses are unexpected. Prior literature has examined several hypotheses of life insurance lapse focusing mainly on macroeconomic factors using aggregate data and household microeconomic factors using household-level data. We introduce and test individual cognitive ability variables in a model of the life insurance voluntary lapse decision by individual policyholders using household-level data from the Health and Retirement Study. We find that one measure of cognitive ability in particular, numeracy, is related to the voluntary lapse decision. While controlling for numeracy, we find evidence that those individuals with higher levels of net worth are less likely to voluntarily lapse a policy which is consistent with the emergency fund hypothesis. We introduce a new measure of liquidity shock, kids moving home, into the model and find it has a strong positive relationship with the decision to voluntarily lapse a policy. Consistent with life insurance demand theory, we find that those who have recently entered retirement are more likely to lapse their policy.

Research on lapse in life insurance: what has been done and what needs to be done?

PurposeThe purpose of this paper is to review research on lapse in life insurance and to outline potential new areas of research in this field.Design/methodology/approachThe authors consider theoretical lapse rate models as well as empirical research on life insurance lapse and provide a classification of these two streams of research. More than 50 theoretical and empirical papers from this important field of research are reviewed. Challenges for lapse rate modeling, lapse risk mitigation techniques, and possible trends in future lapse behavior are discussed.FindingsLapse rate modeling has been a very active field of research in the last years, as evidenced by the 44 papers on lapse modeling considered in this review. Moreover, a fair amount of empirical work (another 12 papers) has been done, especially on the issue of how environmental variables affect lapse. Research on individual policyholder and contract information is more scarce, since such information is typically treated as confidential.Practical implicationsThe risks arising from lapse are of high economic importance. Lapsation is thus of interest not only to academics, but is highly relevant for the industry, regulators, and policymakers, especially in regard to designing an appropriate regulatory environment. Lapsation also impacts many actuarial tasks, such as product design, pricing, hedging, and risk management. A review of the recent literature might be helpful for these tasks.Originality/valueTo the best of the authors' knowledge, this is the first structured review of the increasingly important literature on life insurance lapsation. Next to the structured review of the existing models and the empirical evidence, the paper also contributes to the literature by discussing challenges for lapse rate modeling and possible trends.

A causal inference approach to measure price elasticity in Automobile Insurance

Understanding the precise nature of price sensitivities at the individual policyholder level is extremely valuable for insurers. A rate increase has a direct impact on the premium customers are paying, but there is also the indirect impact as a result of the “causal” effect of the rate change on the customer’s decision to renew the policy term. A rate increase may impair its intended impact on the overall profitability of the portfolio if it causes a large number of policyholders to lapse their policy and switch to an alternative insurer. The difficulty in measuring price elasticity from most insurance databases is that historical rate changes are reflective of a risk-based pricing exercise. As a result, the specific rate change at which a customer is exposed is a deterministic function of her observed covariates. The nature of the data is thus observational, rather than experimental. In this context, measuring the causal effect of a rate change on the policyholder’s lapse outcome requires special modeling considerations. Conventional modeling approaches aimed to directly fit the lapse outcome as a function of the rate change and background covariates are likely to be inappropriate for the problem at hand. In this paper, we propose a causal inference framework to measure price elasticity in the context of Auto Insurance. One of the strengths of our approach is the transparency about the extent to which the database can support causal effects from rate changes. The model also allows us to more reliably estimate price-elasticity functions at the individual policyholder level. As the causal effect of a rate change varies across individuals, making an accurate rate change choice at the individual subject level is essential. The rate at which each subject is exposed could be optimized on the basis of the individual characteristics, for the purpose of maximizing the overall expected profitability of the portfolio.

The merits of pooling claims revisited

PurposeDefinitions of pooling effects in insurance companies may convey the impression that the achieved risk reduction effect will be beneficial for policyholders, since typically lower premiums are paid for the same safety level with an increasing number of insureds, or a higher safety level is achieved for a given premium level for all pool members. However, this view is misleading and the purpose of this paper is to reexamine this apparent merit of pooling from the policyholder's perspective.Design/methodology/approachThis is achieved by comparing several valuation approaches for the policyholders' claims using different assumptions of the individual policyholder's ability to replicate the contract's cash flows and claims.FindingsThe paper shows that the two considered definitions of risk pooling do not offer insight into the question of whether pooling is actually beneficial for policyholders.Originality/valueThe paper contributes to the literature by extending and combining previous work, focusing on the merits of pooling claims (using the two definitions above) from the policyholder's perspective using different valuation approaches.

Longitudinal modeling of insurance claim counts using jitters

Modeling insurance claim counts is a critical component in the ratemaking process for property and casualty insurance. This article explores the usefulness of copulas to model the number of insurance claims for an individual policyholder within a longitudinal context. To address the limitations of copulas commonly attributed to multivariate discrete data, we adopt a ‘jittering’ method to the claim counts which has the effect of continuitizing the data. Elliptical copulas are proposed to accommodate the intertemporal nature of the ‘jittered’ claim counts and the unobservable subject-specific heterogeneity on the frequency of claims. Observable subject-specific effects are accounted in the model by using available covariate information through a regression model. The predictive distribution together with the corresponding credibility of claim frequency can be derived from the model for ratemaking and risk classification purposes. For empirical illustration, we analyze an unbalanced longitudinal dataset of claim counts observed from a portfolio of automobile insurance policies of a general insurer in Singapore. We further establish the validity of the calibrated copula model, and demonstrate that the copula with ‘jittering’ method outperforms standard count regression models.

Longitudinal Modeling of Insurance Claim Counts Using Jitters

Modeling insurance claim counts is a critical component in the ratemaking process for property and casualty insurance. This article explores the usefulness of copulas to model the number of insurance claims for an individual policyholder within a longitudinal context. To address the limitations of copulas commonly attributed to multivariate discrete data, we adopt a jittering method to the claim counts which has the effect of continuitizing the data. Elliptical copulas are proposed to accommodate the intertemporal nature of the jittered claim counts and the unobservable subject-specific heterogeneity on the frequency of claims. Observable subject-specific effects are accounted in the model by using available covariate information through a regression model. The predictive distribution together with the corresponding credibility of claim frequency can be derived from the model for ratemaking and risk classification purposes. For empirical illustration, we analyze an unbalanced longitudinal dataset of claim counts observed from a portfolio of automobile insurance policies of a general insurer in Singapore. We further establish the validity of the calibrated copula model, and demonstrate that the copula with jittering method outperforms standard count regression models.

Chapter 6: Insurance industry

Chapter 6: Insurance industry

Personal Premium Saving under Basic Protection

This paper outlines a method for distributing to individual policyholders the average New York statewide premium savings of 39 percent which could result from adoption of the Protection Plan. It shows the range of saving is very extensive; dollar savings for a low income insured may be double the average, while savings may be very small for some high income policyholders. Also, as the amount of increased limits coverage is added, the relative dollar amount saved increases; for $25,000/ $50,000 limits with $5,000 medical payments coverage, savings may range up to 67 percent from present costs. Savings will be largest for low income insureds in communities with low rates and will increase as available benefits from collateral sources increase. Almost everybody could receive some saving in insurance premium cost under a Protection Plan. The total possible reductions are substantial to the point of being shocking . Previous studies 1 have estimated the average statewide effect on automobile insurance premium costs if the ProFrank Harwayne, F.C.A.S. has been Chief Actuary for the New York Insurance Department since 1952. He was a founding director of the American Academy of Actuaries and has been consulting actuary to federal, state and Canadian governments as well as Harvard University. Mr. Harwayne has taught mathematics and insurance at C.C.N.Y., Pace College and the College of Insurance. This article was submitted for publication in July, 1968. It was prepared for the Study of Automobile Claims Systems of Harvard Law School. 1 Harwayne, Insurance Costs of Automobile Protection Plan in Relation to Automobile Bodily Injury Liability Costs, LIII Proceedings of the Casualty Actuarial Society, 122 (1966). Concerning this same study, which related to New York state, see also Keeton & O'Connell, Protection and the Costs of Traffic Accidents, 38 N.Y.S.B.J. 255 (1966). For a Michigan study, see Harwayne, Insurance Costs of Protection Plan in Michigan, 1967 U. Ill. L. F. 479; also printed in Crisis in Car Insurance 119 (R. Keeton, J. O'Connell & J. McCord, eds., 1968). For a further New York state study, see The Relative Cost of Protection Insurance in New York State-An Objective Determination, (copyright 1968, Frank Harwayne). tection Plan2 were adopted. This study 2 The Protection Automobile Insurance Plan is set forth most fully, along with an attempt to document its pressing need and a draft statute, in R. Keeton & J. O'Connell, Protection for the Traffic Victim: A Blueprint for Reforming Automobile Insurance (1965) [hereinafter cited as Protection]. For a slightly revised and updated version of Chapter 6 of this book, see Keeton & O'Connell, Basic Protection Automobile Insurance, 1967 U. Ill. L. F. 400, 408-39; also printed in Crisis in Car Insurance 40, 48-79. See also R. Keeton & J. O'Connell, After Cars Crash-The Need for Legal and Insurance Reform (1967), a version written for the general reader. The Protection plan has two principal elements: (1) a new form of compulsory automobile insurance (called Protection coverage) will pay all those injured in traffic accidents without regard to anyone's fault or lack of it. Protection Insurance will compensate for losses up to limits of $10,000 per victim for any victim's out-of-pocket losses-which consist mainly of medical expenses and wage losses. Payment would not be made under B.P. for pain and suffering. Whenever a motorist carrying B.P. insurance is involved in an accident, and he, or a guest, or a pedestrian, is hurt, the motorist's own basic protection insurance company will compensate him or his guest or the pedestrian. (2) The second element is a law that partially exempts from liability for negaligent driving all

Taxation Problems of Life Insurance

The basic principle on which life insurance is founded is that of mutual co-operation. Many persons co-operate to assume and to share risks which the individual could not afford to bear alone. This cooperation takes the form of contributions to a common fund, from which claims are paid as they occur. In the modern form of life insurance the contributions are “level” and dependent chiefly on the age of the contributor at entry to the fund. Since the life insurance risk increases with increasing age it will be obvious that level contributions sufficient to meet all risks will more than suffice to meet the lighter risks of the early years and will be insufficient to meet the heavier risks of the later years. Accordingly, the early excess contributions must be accumulated in the fund to make good the later deficiencies. It is these excess contributions accumulated to meet the future risks that are invested and form the assets of the life companies. These assets are not the property of the companies in the commonly accepted sense of the word, but instead represent the accumulated savings of the individual policy-holders, to whom they are ultimately to be returned. The companies are simply acting as trustees or custodians of these savings, and, in common with other trustees, the assets in which these savings may be invested are prescribed and limited by law. There exists, of course, in most of our Canadian companies a shareholders' interest which, however, is small and of little account, while in the large American companies the shareholders' interest is entirely negligible or non-existent. Since the life insurance business is of a quasi-public nature there has developed a close government supervision over its affairs, with the result that the companies are subjected to regular extensive examinations and also are required to prepare and file periodically complete detailed reports of their business.

On the construction of Models of Policy-values, and on a new method of comparing the Reserves for Policies, according to different Tables of Mortality and Rates of Interest

There is no subject of greater importance in the conduct of the business of Life Assurance than that of the valuation of policies. It is a matter which comes before the actuary from day to day and from year to year, whether in the form of fixing the amount to be returned to an individual policyholder on the cancelment of his contract, or in that of estimating what reserve should be made in the aggregate for a mass of policies existing at the close of a valuation period. Both of these questions have been discussed before the Institute on many previous occasions, and it is not necessary to enter into them now. The task I have set before myself is the humbler one of dealing with results already arrived at. I do not propose to enquire what are the reasons for preferring one mortality table or rate of interest to another, or on what principle of calculation the surrender-value of a policy should be based. I accept the results brought out by the use of any mortality table or rate of interest agreed on, and I propose to consider how these results may be represented by means of diagrams and models, and whether by this means we can arrive at any clearer understanding of the relation to one another of the reserves brought out by different standards of valuation.