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CAS E-Forum, Summer 2020
Featuring Five Reserves Call Papers and Four Independent Research Papers
This paper discusses an alternative approach to utilizing and credibility weighting the excess loss information for large account pricing. The typical approach is to analyze the burn costs in each excess layer directly (see Clark 2011, for example). Burn costs are extremely volatile in addition to being highly right skewed, which does not perform well with linear credibility methods, such as Buhlmann-Straub or similar methods (Venter 2003).
The standard method for calculating reserves for permanently injured worker benefits (indemnity and medical) is a combination of adjuster-estimated case reserves and reserves for incurred but not reported claims (IBNR) using a triangle method. There has been some interest in other reserving methodologies based on a calculation of future payments for the expected lifetime of the injured worker using a table of mortality rates.
This paper demonstrates a Bayesian approach for estimating loss costs associated with excess of loss reinsurance programs.
This paper proposes a method to derive paid tail factors using incurred tail factors and historical payout patterns. Traditionally, a ratio of paid-to-incurred losses—and its reciprocal, the conversion factor—may be used to convert payments at a specific maturity to incurred losses, prior to attaching an incurred tail factor. The implied paid tail factor would be the product of the incurred tail factor and the selected conversion factor.
This paper proposes efficient statistical tools to detect which risk factors influence insurance losses before fitting a regres-sion model. The statistical procedures are nonparametric and designed according to the format of the variables commonly encountered in P&C ratemaking: continuous, integer-valued (or discrete) or categorical.
Rating areas are commonly used to capture unexplained geographical variability of claims in insurance pricing. A new method for defining rating areas is proposed using a two-part generalized geoadditive model that models spatial effects smoothly using Gaussian Markov random fields. The first part handles zero/nonzero expenses in a logistic model; the second handles nonzero expenses (on log-scale) in a linear model.
An actuarial approach for calculating a relativity based on geographic diversification is presented. The method models correlation as a function of distance between two exposures, and uses that to calculate a risk margin for each policy. It assumes that any premium provision for a company risk margin is currently allocated in proportion to policy risk-free premium, which results in a uniform risk-loading uprate for all policies.
The world is going through an extraordinary event. Since it first appeared in Wuhan, China, in late 2019 (“First Covid-19 Case Happened in November, China Government Records Show - Report” 2020), the coronavirus has spread rapidly to most of the world’s population. Indeed, one of the difficulties of writing an article like this is to keep up with the pace of change.
Hierarchical compartmental reserving models give a parametric framework to describe aggregate insurance claims processes using differential equations.
Although available since the 1990s, cyber insurance is still a relatively new product that is ever-changing. The report uses a conceptual approach to identify and evaluate potential exposure measures for cyber insurance. In particular, the report studies the losses that can arise with each cyber insurance coverage and identifies potential exposure measures related to these losses.
This paper introduces an individual claims forecasting framework utilizing Bayesian mixture density networks that can be used for claims analytics tasks such as case reserving and claims triaging. This approach produces multi-period, cash-flow forecasts. The modeling framework uses a publicly available data simulation tool.
CAS E-Forum, Winter 2020 Featuring four Essays on Communications to Senior Management and four Independent Research Papers
Motivatio This paper was written in response to a ‘Call for Papers’ on Communication of Technical Results to Senior Management
Method This essay relies on personal experience which has worked for me.
Conclusions Structured and brief communications are key to communicate with senior leadership as time may be limited.
Keywords Communication, Structured Thinking
Motivation: Provide guidance with respect to the creation, testing, documentation, and evaluation of predictive models, in particular Generalized Linear Models.
Approach: Compact summary of data organization & preparation, variable usage & selection, model evaluation, and algorithm building.
Motivation Distributions of unpaid claims are gaining importance within the actuarial community as management, regulators, and others look to the actuarial profession for a quantitative approach to evaluating risk. Actuaries have historically applied their judgment to determine if a best estimate is reasonable, but how do we know if the models used to produce distributions are reasonable?
Split credibility has been used in practice for several decades, though its foundational theory has been investigated only recently. This paper studies the properties of the primary loss and the excess loss in the split experience plan of the National Council on Compensation Insurance (NCCI). We first revisit the claim that the excess loss is more volatile than the total loss.
Very similar modeling is done for actuarial models in loss reserving and mortality projection. Both start with incomplete data rectangles, traditionally called triangles, and model the data by year of origin, year of observation, and lag from origin to observation.
In volume 8, no. 2 of Variance, a technique using actuarial present value was applied to infrastructure service contracts (ISCs) as a way to manage obsolescence in portfolios of fixed, physical capital assets. The theory put forth in that paper was purely deductive and used basic financial mathematics to posit some untested hypotheses.
This paper presents closed-form formulas in order to estimate, based on the historical triangle of ultimate estimates, both the one-year and the total run-off reserve risk.
