Insurance abstract
A method of evaluating a permanent life insurance policy including
the steps of establishing a benchmark cost of insurance value, obtaining
a policy illustration, resolving an illustrated cost of insurance
value from the policy illustration, and comparing the benchmark
cost of insurance value with the illustrated cost of insurance value.
A matrix of mortality profiles may be established wherein the benchmark
cost of insurance is adjusted in relation to the matrix. The matrix
may include gender-based, lifestyle and pricing method risk values.
Gender-based risk values reflect the differing mortality rates experienced
between males and females over a lifetime. Lifestyle-based risk
values may acknowledge dangerous activities such as tobacco use,
job occupation and the like. Pricing method risk values are based
on the statistical evidence that affluent individuals generally
lead healthier lifestyles while also purchasing substantial policy
values.
Insurance claims
What is claimed is:
1. A method of evaluating a permanent life insurance policy comprising:
obtaining a first policy illustration; resolving an illustrated
premium load value from the policy illustration; resolving an illustrated
fixed expense value from the first policy illustration; resolving
an illustrated cost of insurance value from the first policy illustration;
resolving an illustrated net amount at risk value from the first
policy illustration; establishing a first pricing policy value for
the first policy illustration from the sum of the illustrated cost
of insurance value, the illustrated premium load value, and the
illustrated fixed expense value divided by the illustrated net amount
at risk value; and comparing the first pricing policy value with
a second pricing policy value.
2. The method of claim 1 wherein the first and second pricing policy
values are expressed in units of one dollar.
3. The method of claim 1 wherein the illustrated policy expense
value for the first policy illustration includes an illustrated
premium load value from the first policy illustration.
4. The method of claim 1 wherein the illustrated policy expense
value for the first policy illustration includes an illustrated
fixed expense value from the first policy illustration.
5. The method of claim 1 wherein the illustrated premium load value
for the first policy illustration includes an illustrated cash-value
based expense value from the first policy illustration.
6. The method of claim 1 wherein the illustrated premium load value
for the first policy illustration includes investment management
fees.
7. The method of claim 1 wherein the illustrated premium load value
for the first policy illustration includes M&E risk charges.
8. The method of claim 1 wherein the illustrated fixed expense
value for the first policy illustration includes an illustrated
State Premium Tax value.
9. The method of claim 1 wherein the illustrated fixed expense
value for the first policy illustration includes an illustrated
Deferred Acquisition Cost (DAC) tax value.
10. The method of claim 1 wherein the illustrated premium load
value for the first policy illustration includes an illustrated
sales load value.
11. The method of claim 1 wherein the illustrated fixed expense
value for the first policy illustration includes an illustrated
fixed periodic expense value.
12. The method of claim 1 wherein an average of pricing policy
values are established from a plurality of policy illustrations.
13. The method of claim 1 wherein an average of pricing policy
values are established from a plurality of policy illustrations
to resolve a benchmark pricing policy value.
14. The method of claim 1 further comprising: establishing a matrix
of mortality profiles; and adjusting the illustrated cost of insurance
value according to the matrix.
15. The method of claim 14 wherein the matrix comprises gender-based
risk values.
16. The method of claim 14 wherein the matrix comprises lifestyle-based
risk values.
17. The method of claim 14 wherein the matrix comprises pricing
method risk values.
18. A method of evaluating a permanent life insurance policy comprising:
obtaining a first policy illustration; resolving an illustrated
premium load value from the policy illustration; resolving an illustrated
fixed expense value from the first policy illustration; resolving
an illustrated cost of insurance value from the first policy illustration;
resolving an illustrated fixed expense value from the first policy
illustration; establishing a calculation period; resolving an illustrated
net amount at risk value from the first policy illustration for
each year in the calculation period; dividing the sum of the illustrated
net amount at risk for all the years in the calculation period by
the count of years to establish an average net amount at risk establishing
a first pricing policy value for the first policy illustration from
the sum of the illustrated cost of insurance value, the illustrated
premium load value, and the illustrated fixed expense value divided
by the illustrated net amount at risk value; and comparing the first
pricing policy value with a second pricing policy value.
19. The method of claim 18 wherein the first and second pricing
policy values are expressed in units of one dollar.
20. The method of claim 18 wherein the illustrated policy expense
value for the first policy illustration includes an illustrated
premium load value from the first policy illustration.
21. The method of claim 18 wherein the illustrated policy expense
value for the first policy illustration includes an illustrated
fixed expense value from the first policy illustration.
22. The method of claim 18 wherein the illustrated premium load
value for the first policy illustration includes an illustrated
cash-value based expense value from the first policy illustration.
23. The method of claim 18 wherein the illustrated premium load
value for the first policy illustration includes investment management
fees.
24. The method of claim 18 wherein the illustrated premium load
value for the first policy illustration includes M&E risk charges.
25. The method of claim 18 wherein the illustrated fixed expense
value for the first policy illustration includes an illustrated
State Premium Tax value.
26. The method of claim 18 wherein the illustrated fixed expense
value for the first policy illustration includes an illustrated
Deferred Acquisition Cost (DAC) tax value.
27. The method of claim 18 wherein the illustrated premium load
value for the first policy illustration includes an illustrated
sales load value.
28. The method of claim 18 wherein the illustrated fixed expense
value for the first policy illustration includes an illustrated
fixed periodic expense value.
29. The method of claim 18 wherein an average of pricing policy
values are established from a plurality of policy illustrations.
30. The method of claim 18 wherein an average of pricing policy
values are established from a plurality of policy illustrations
to resolve a benchmark pricing policy value.
31. The method of claim 18 further comprising: establishing a matrix
of mortality profiles; and adjusting the illustrated cost of insurance
value according to the matrix.
32. The method of claim 31 wherein the matrix comprises gender-based
risk values.
33. The method of claim 31 wherein the matrix comprises lifestyle-based
risk values.
34. The method of claim 31 wherein the matrix comprises pricing
method risk values.
Insurance description
FIELD OF INVENTION
This invention relates to a method for evaluating financial information,
and more specifically to evaluating permanent life insurance policies
for cost and performance criteria.
BACKGROUND OF THE INVENTION
The permanent life insurance product is the most complex financial
instrument that is purchased or owned by the general market of consumers,
combining the benefits and costs otherwise found in insurance and
investments into a single financial instrument. For instance, like
term insurance, all permanent life insurance policies pay a death
benefit. All permanent life insurance products include some form
of a term-insurance-like "risk" premium, usually referred
to as the Cost of Insurance Charges (herein "COIs"). In
addition to this death benefit, all permanent life insurance products
include a living benefit in some form of account value, commonly
referred to as the cash surrender value. This account value is the
surplus or excess premium paid into the policy above and beyond
the various policy charges, and is invested into either the insurance
company's general account of predominantly bonds and mortgages in
the case of universal life products, or a variety of mutual-fund-like
separate accounts in the case of variable life products. All permanent
life insurance products include policy charges for investment management
fees, investment advisory fees, and fund operating expenses, like
Certificates of Deposits and mutual fund investments. Also like
some mutual funds, permanent life insurance products can include
a charge that is deducted from contributions to the policy, commonly
referred to as a premium load. Lastly, permanent life insurance
products can assess or include additional policy charges unique
to the permanent life insurance products itself, like state premium
taxes, federal deferred acquisition costs (herein "DAC")
taxes, fixed or flat administration charges, and Mortality and Risk
Expense (herein "M&E") charges.
While owners of whole life insurance, and other similar permanent
life insurance products have always paid either some or all of the
above charges, these charges had been "bundled" into an
overall "fixed" policy premium calculated based on these
underlying pricing factors, but were known only to insurance company
actuaries, and were hidden from view of the policy owner. However,
with the introduction of universal life in 1986, these policy charges
were "unbundled", disclosing for the first time the individual
policy pricing components as to COIs, premium loads, fixed policy
expenses, and account-value-based charges. At the time, this information
was only available through the duly licensed agent of the life insurance
company underwriting and distributing the given product, or from
the insurance company itself. While policy expenses were "unbundled",
this information was not widely available, was almost never separately
evaluated, considered or included in the decision to purchase a
particular product, and was customarily only disclosed or communicated
by virtue of an annual statement for the policy produced on the
policy anniversary (i.e. more than 1-year after the purchase of
the given policy). With the advent of variable life insurance products,
the level of disclosure has increased to further disclose and publish
for general public consumption all guaranteed pricing factors determining
the maximum policy charges, and most of the current pricing factors
reflecting the policy expenses currently applicable. Of the 4 basic
types of charges: (1) COIs, (2) Premium Loads, (3) Fixed Policy
Fees, and (4) Account-Value-Based charges, all are disclosed and
published on both a current and guaranteed basis, except COIs. Because
these COIs are typically the most influential determinant of policy
pricing, contributing as much as 75% of the total premium of a given
policy, any comparison of policy pricing that does not include COIs
is at least inconclusive, and potentially misleading.
Cost of Insurance Charges (COIs)
COIs are deductions from permanent life insurance policies to cover
anticipated payments for claims. As with most types of insurance,
claims are, and arguably should be, the largest single cost factor
of any insurance policy (if claims are not the largest single cost
factor, then is the product really insurance against the risk of
some claim, or something else?). With life insurance, COIs typically
account for about 75% of the total premium, and, as expected, the
higher the claims, the higher the premiums. COI charges are calculated
year-by-year as the result of the policy death benefit (see net
amount at risk below) multiplied times a COI rate provided by the
insurance company for each age corresponding to each policy year
for each product. These deductions are much like term life insurance
premiums in that they are predominantly for claims paid during a
given period (typically 1 year). For this reason, COIs are frequently
referred to as the pure "risk" portion of the premium,
reimbursing the insurance company for the risk associated with paying
the death benefit. Because the risk of death increases with age,
so do the COIs.
For example, assume an insurance company provides permanent life
insurance for a group of 1,000 policyholders whom all are insured
for $100,000 and three (3) insureds out of the group of 1,000 die
in a given year. The insurance company pays $300,000 to the beneficiaries
of those three insureds. The insurance company must collect $300
from each policy owner over the course of the period in order to
pay this $300,000 in claims (i.e. 1,000 policyholders.times.$300=$300,000
in death claims paid). In this case, the COI Rate would equal $3.00
per $1,000 of death benefit (i.e. each insured paid $3.00 multiplied
times 100 for each $1,000 of death benefit).
Of course, as the average age of the population of 1,000 in the
group ages, then the risk of more deaths increases. For example,
the next year, all insureds are a year older, and because the probability
of death increases with age, we assume that four (4) insureds out
of population of 1,000 die in this next year (for simplicity sake,
we will assume that the insurance company sold three (3) new $100,000
policies to replace the three $100,000 policies removed from our
pool by the three deaths in the prior year). The insurance company
will pay $400,000 to the beneficiaries of those four insureds. The
insurance company must collect $400 from each policy owner over
the course of the period in order to pay this $400,000 in claims
(i.e. 1,000 policyholders.times.$400=$400,000 in death claims pad/to
be paid). In this case, the COI Rate would equal $4.00 per $1,000
of death benefit (i.e. each insured paid $4.00 multiplied times
100 for each $1,000 of death benefit).
This example also assumes the insurance company collects only the
exact amount necessary to pay these claims. However, in reality,
the insurance company must also collect a profit to remain in business.
Actual COIs in this example would, therefore, be slightly higher
to cover anticipated claims, but then also to provide a profit to
the insurance company providing the insurance and bearing the risk.
In addition, some insurers "load" the COIs to cover other
policy expenses that are not disclosed elsewhere. For instance,
some policies are marketed as "no-load" or "low-load"
policies, and as such do not disclose certain policy expenses or
loads. The expenses or loads that are typically "hidden"
are sales loads, and other premium based loads. However, because
certain premium based loads must be paid (e.g. state premium taxes,
federal deferred acquisition costs (DAC) taxes, and the cost to
distribute the policies), some insurers "hide" these costs
inside "loaded" COIs.
As mentioned above, in all cases, these COIs are calculated each
policy year as the result of the policy "net at risk"
death benefit multiplied times a COI Rate provided by the insurance
company for each age corresponding to each policy year for each
product. This "net at risk" death benefit is that portion
of the total death benefit in excess of any policy cash value. For
example, one of the defining characteristics of permanent life insurance
policies is that they have a cash value in addition to the death
benefit. This cash value typically increases over time. Death benefits
can either remain level, in which case this "net at risk"
death benefit changes from year to year. Depending upon the design
of the policy, death benefits can also, at the policy owner's election,
increase along with the cash value over time, in which case this
"net at risk" death benefit remains the same from year
to year. While different policies can calculate the "net at
risk" death benefit differently, this Net Amount at Risk can
be generally represented as follows:
Where: NAR.sub.Year =Net amount at risk during a policy year. DB.sub.Year
=Total death benefit during a policy year. CV.sub.Year =Policy cash
account value during a policy year.
It should be noted that the above-illustrated analysis is not necessarily
tied to an annual period. Semi-annual, monthly or other time frames
may be incorporated to resolve the net amount at risk during a time
frame.
It is common for permanent life insurance policies with a level
death benefit to be priced such that policy cash values and policy
death benefits become equal by design at the maturity or endowment
age of the policy (defined by statute between age 95 and 100 depending
on the policy). As such, as cash values increase and the death benefit
remains level, the "net at risk" death benefit (or net
amount at risk) declines.
On the other hand, permanent life insurance policies with an increasing
death benefit are typically priced such that policy cash values
become equal to the originally issued face amount, while the total
death benefit is either equal to, or approximates this originally
issued face amount, plus the accumulated cash account value at any
given point in time. As such, as cash values increase and in so
doing push up the death benefit, the "net at risk" death
benefit remains level.
As a result, the actual COIs for a given policy will be a function
of the COI rate provided by the insurance company for each year
of a given policy, the net amount at risk in each of those years
of the given policy, and the design of the policy death benefit
(i.e. level death benefit or increasing death benefit) for the given
policy.
Insurance Expenses and Charges
While different insurance companies use different naming conventions
for what can appear to be many different types of expenses and charges
associated with a given policy, these various policy expenses are
customarily disclosed as State Premium Taxes, DAC taxes, Sales Loads/Expenses,
Underwriting Charges/Expenses, Policy Issue Charges/Expenses, Policy
Administration Charges/Expenses, Administration Expense Charges/Fees,
Policy/Contract Maintenance Charges/Expenses, Policy Service Fees/Expenses,
Mortality and Expense Risk Charges (variable products only), Investment
Management Fees, Investment Advisory Fees, Fund Operating Expenses,
and Other Carrier Loads/Charges/Fees. However, despite this confusing
variety of terms, all policy expenses can be grouped/categorized
by the nature of the expense into 3 basic types: 1) Premium-Based
Charges, 2) Cash-Value-Based Charges, and 3) Fixed-Type Charges.
1. Premium-Based Charges:
Premium-Based Charges are charged to policyholders as a percent
of the premium paid in a given year and typically ranges between
0% and 35%. Premium-based charges customarily cover state premium
taxes that average 2.50%, DAC taxes averaging 1.5%, and Sales Loads/Expenses
ranging between 0% and 30%. Carriers may also impose a premium-based
charge. In addition, while state premium taxes and DAC taxes are
generally calculated by the respective government agencies as a
percent of premium, and while insurance companies must certainly
pay these taxes, insurance companies are not required to assess
the charge as a percent of premium. As such, some insurance companies
charge no (i.e. 0%) premium charges, and collect state and federal
taxes from other charges within the policy (usually COIs).
Premium-based charges can also vary depending on either the policy
year in which a premium is paid and the level of the premium paid
into a given policy. For instance, a higher premium load may be
assessed in the early policy years to recover up-front expenses
related to underwriting, issue and distribution of a given policy.
After these up-front expenses have been amortized (frequently over
a period of ten policy years), premium loads are then often reduced
to cover the relatively lower policy owner service and policy administration
expenses. In addition, a higher premium load may be charged on actual
premiums paid up to a "Base Policy Premium" or "Target
Premium" level, while a lower premium load may be charged on
actual premiums paid in excess of this "Base Policy Premium"
or "Target Premium" amount. This "Base Policy Premium"
or "Target Premium" is generally the premium which, if
paid every policy year, would endow or mature the policy for its
originally issued face amount based on guaranteed policy pricing
assumptions as to COIs, expenses and earnings. In other words, "Base
Policy Premium" or "Target Premium" is calculated
by actuaries of the insurance company such that if the insurance
company charged the maximum allowable under the terms of the policy
contract, and if the policy owner paid the "Base Policy Premium"
or "Target Premium" every year, then the policy would
guarantee to pay a death benefit regardless of the age of death
of the insured.
This "Base Policy Premium" or "Target Premium"
is, therefore, analogous to the "insurance premium" (i.e.
that premium typically paid to maintain the insurance). Premium
amounts paid into the policy in excess of this "Base Policy
Premium" or "Target Premium" can, therefore, be viewed
as "excess premium" above and beyond that which required
supporting a given insurance death benefit. The reason a policy
owner would decide to pay this "excess premium" could
be to either create a cash value reserve which can be used to pay
future premiums, COIs and policy expenses from within the policy
effectively pre-paying future premium otherwise due from the policy
owner, and to accumulate wealth in the form of policy cash values
that benefit from preferred federal income tax treatment and special
protection from the claims of creditors under state law. As such,
premiums paid up to the "insurance premium" are subjected
to "insurance loads" to cover policy expenses unique to
the insurance component of the policy, while premiums paid in excess
of the "insurance premium" are subjected to a lower level
of loads on those monies contributed toward policy cash values.
While different policies can calculate premium loads differently,
these charges can be generally represented as follows:
Where: PL.sub.Year =Calculated Premium Loads PREM.sub.Target =Target
Premium PREM.sub.Excess =Total Premium Paid in Excess of Target
Premium PL.sub.Target =Premium Load Percentage Up to Target Premium
PL.sub.Excesse =Premium Load Percentage After Target Premium is
Paid
2. Cash-Value-Based Charges:
Cash-value-based charges are charged to policyholders as a percent
of either the policy cash account values (i.e. the total cash value
of a given policy) or the policy cash surrender value (i.e. the
cash value of the policy less any surrender charges or cancellation
fees that would apply on the surrender or cancellation of the policy).
All permanent life insurance products include a living benefit,
in addition to the death benefit, in the form of this cash account
value or cash surrender value. This surrender value is the surplus
or excess premium paid into the policy above and beyond the various
policy charges. These surrender values are invested into either
the insurance company's general account of predominantly bonds and
mortgages in the case of whole life and universal life products,
or a variety of mutual-fund-like separate accounts selected by the
policy owner in the case of variable life products.
Cash-value-based charges are most commonly calculated as a percent
policy cash account values, typically range between 0.00% and 4.00%
in total, but are divided by their nature into two (2) different
types of cash-value-based charges; 1) fund-level or fund-specific
charges, and policy-level or policy-specific charges. Fund-level
or fund-specific charges relate specifically to the investment portfolio
or separate accounts funds upon which the cash value is based. Examples
of fund-level or fund-specific charges include, but are not limited
to charges at the investment fund or portfolio level for investment
management fees, investment advisory fees, and fund operating expenses,
but these charges may or may not be disclosed depending upon the
type of the policy (e.g. whole life and universal life policies
do not customarily disclose fund-level or fund-specific charges
while variable products do publish these expenses.)
In addition, because fund-level or fund-specific charges are a
function of the underlying investment portfolio or separate account
funds, which may or may not be disclosed, and which can be, and
usually is different for different policies of the same product
line, then these fund-level or fund-specific charges are more of
a investment expense than a policy expense, and therefore should
only be considered when comparing investment or separate account
fund selections, and not when comparing policy level costs. On the
other hand, policy-level or policy-specific charges relate specifically
to the policy itself, without regard to underlying portfolio investments
or separate account fund selections. The most common policy-level
or policy-specific cash-value-based charge is the M&E charge
intended to cover the risks assumed by the insurance company that
actual cost of insurance charges will be greater than expected (i.e.
insureds live less time than anticipated resulting in increased
claims) and that actual expense charges will be greater than expected.
Some products also include policy-level or policy-specific cash-value-based
charge in addition to the M&E charge, both of which can vary
depending on the year of the policy (e.g. 1.00% of cash values during
the first 10 policy years, and 0.5% of cash values thereafter).
Because these policy-level or policy-specific cash-value-based charges
are specific to the policy, without regard to the underlying investment
portfolio or separate account fund selections, they are truly a
policy cost to be considered when comparing one policy to another.
As such, while different policies can calculate policy-level or
policy-specific cash-value-based charges differently, these charges
can be generally represented as follows:
Wherein: CVC.sub.Year =Cash-value-based charges for a selected
year; CSV.sub.Year =Cash surrender value for the selected year;
and CVCP.sub.Year =Cash value based charge percentage for the selected
year.
3. Fixed-Type Charges:
Fixed-Type Charges are charged to policyholders as some fixed amount
calculated at the time the policy is issued either as a flat monthly
charge (e.g. $10.00 a month), or in relation to the originally issued
policy face amount (e.g. $1.00 per $1,000 of policy face amount).
While this charge is fixed in amount at the time the policy is issued,
it can vary by predetermined schedule depending on the year of the
policy (e.g. $10.00 a month and $1.00 per $1,000 of policy face
amount during the first 10 policy years, and $5.00 a month and $0.00
per $1,000 of policy face amount thereafter). While different policies
can calculate Fixed-Type Charges differently, these charges can
be generally represented as follows: ##EQU1##
Where: FTC.sub.Year =Fixed Type Charges for each policy year. FTC.sub.Flat
=Monthly Fixed Type Charges FTC.sub.Amt =Fixed Type Charges Per
$1,000 DB=Death benefit
In addition, fixed-type charges can also include contingent or
back-end policy surrender charges that are deducted from the policy
cash account value upon surrender or cancellation/termination of
the policy. These surrender charges are calculated in relation to
the initially issued policy face amount and can be as much as 100%
of the target premium (defined above) for policies available to
the general public at large (i.e. policies commonly referred to
as "Retail Policies"), but can be less or even 0% for
policies purchased in larger volumes (i.e. frequently referred to
as "Institutionally-Priced" policies). In either case,
this surrender charge typically remains level for an initial period
of years (e.g. 5 years), then reduces to $0 over a following period
of years (e.g. policy years 6-10 or 6 through 15). ##EQU2##
Where: SC.sub.Year =Surrender Charges for each policy year. SC.sub.Rate
=Surrender Charges Per $1,000 DB=Death benefit
It is for this reason that the current practice of shopping for
permanent life insurance does not involve consideration and comparison
of these individual cost components. Instead, shopping for a suitable
permanent life insurance product involves the comparison of an illustration
of hypothetical policy values for a given group of products based
on a variety of variables, some of which are unique to the prospective
insured, (e.g. such as age, income, health profile, lifestyle, etc.),
and others that are unique to the given product. However, because
of these variables that are unique to a given product, comparing
illustrations as a means of determining suitability is frequently
an inaccurate and erroneous process that can lead to inaccurate
and erroneous conclusions. In addition to policy pricing variables
that may be unique to a given product, different products also employ
different methods of computing policy expenses and benefits. While
individual pricing components may be disclosed, these computational
methods are not, again leading to the potential for evaluating different
products on a basis that is thought to be comparable, but which
is actually different. Due to this complex nature of permanent life
insurance products, consumers and advisors are frequently ill-equipped
and unprepared to identify differences in the multifarious computations
underlying the illustration of hypothetical policy values, again
leading to the possibility that this method of policy evaluation
can lead to an incorrect conclusion.
Simply defined, insurance is the payment of a premium today in
return for the payment of a claim as some future point. The factors
considered in the selection and purchase of all life insurance policies
can be reduced to the following three factors: (1) the financial
strength and claims paying ability of the insurance company underwriting
and issuing the insurance product, (2) the brand value of the insurance
company underwriting and issuing the insurance product, and (3)
the premium, price, or cost for the insurance product.
While information is readily available from a variety of Ratings
Services (e.g. AM Best, Standard & Poors, Moody's, etc.) who
evaluate the financial strength and claims paying ability of virtually
every insurance company, there is no independent source of pricing
information for the majority of life insurance products purchased.
Presently, the only sources for information as to how much an insurance
policy should cost is limited to: 1) Premium Search Engines for
fixed-premium and fixed-benefit products like Term Life Insurance;
2) Morningstar PrincipiaPro for certain elements of variable life
insurance products; and 3) agents and brokers who represent a one
or more life insurance companies.
However, each of these information sources answer only part of
the question as to how much an insurance policy should cost, and
therefore are limited for a number of reasons.
There are a variety of "Term Insurance Search Engine"
services available to the general public from a variety of providers
such as Quotesmith.RTM., InsWeb.RTM., Compulife.RTM., LifeLink,
and the like. While some of these "Search Engines" provide
consumers with the information necessary to determine how much they
should be paying for term life insurance, these search engines have
limited application simply due to the fact that term life insurance
represents only a fraction of the life insurance products purchased,
accounting for approximately ten percent of the total premiums paid
for life insurance. In addition, because term insurance premiums
for an individual policy are a fraction of the premium otherwise
payable for some form of permanent insurance, the premium savings
available to consumers who are now able to comparison shop by virtue
of access to this information are also only a fraction of the savings
available from a similar service for permanent life insurance products.
On the other hand, a strong demand for life insurance pricing information
in general is clearly demonstrated by the shear number of term insurance
search engine service providers and the widespread popularity of
these services.
Morningstar, Inc. publishes a collection of pricing information
for some, but not all of the pricing variables used to calculate
premiums for a variety of variable life and variable universal life
insurance products. For instance, Morningstar includes in its publication
information relating to the premium-based loads, the fixed policy
charges, and the asset-based expenses. However, Morningstar does
not include in its database any information relating to the COIs.
Because these COIs contribute as much as 75% of the total cost of
a given policy, the Morningstar service cannot be used to answer
the question as to how much the variable life and variable universal
life policies should cost.
The most complete source of life insurance pricing information
is the community of life insurance agents and brokers at large.
Only they are provided with reliable policy pricing data by the
authors of this information--the life insurance companies that "manufacture"
the various life insurance products. However, while the agent and
broker are the most reliable source of pricing information for a
particular product, they typically represent a small fraction of
the insurance companies (frequently only a single insurance company)
offering products in the general market. They are not a reliable
source of enough product pricing data to be able to reliably answer
the question as to how much life insurance should cost and which
is the most suitable product for a given consumer. In addition,
the current practice employed by agents, brokers and advisors to
compare policy information is inherently flawed.
As a result, while consumers have access to pricing information
for the limited market of term insurance products, and limited information
about the market of permanent life insurance products, or complete
information about a limited number of products (frequently a very
limited number of products), the consumer is not privy to the assumptions
behind the calculations that make up policy illustrations.
Permanent insurance products are still going to incur life insurance
operating and mortality costs that have to be covered before passing
on the surplus to policy owners in the form of cash value accumulations.
Currently, the consumer is not privy to the assumptions behind the
calculations that make up policy illustrations. In the absence of
this critical information, consumers and their advisors are vulnerable
to financial exploitation and misunderstanding during the policy
selection process. A policy illustration shows how a life insurance
policy is structured and is used in an attempt to compare one policy
with another. The illustration typically shows patterns of charges
in premium outlays, cash-value accumulation and death benefits.
Variations between two policies may result from differences in company
operational efficiency, investment performance, underwriting policy,
profit objects, the costs associated with marketing, and a host
of other variables. Consumers often erroneously associate a policy's
premium with its cost. Cost includes, not just premiums, but additional
elements of a policy such as death benefits, cash values and dividends.
Retail Pricing
Insurance carriers pool policies to make risks more predictable.
(See Law of Large Numbers.) In fact, the larger the pool, the more
predictable the risk. Pooling, which combines large and small policies
and low and high risk segments of the pool, averages the variables
that contribute to premium prices.
In effect, this averaging cross-subsidizes smaller transactions
and higher-risk segments with excess "profits" from the
larger transactions and lower-risk segments in the pool. (See Problems
with Pooled Products.) Consequently, for larger transactions and
lower-risk buyers, Retail Pricing may not represent the best value.
However, most insurance buyers have access only to Retail Pricing.
While most products will continue to be priced to serve this largest
segment of the market, a growing number of select buyers are gaining
access to Institutional and Experience-Rated
Institutional Pricing
Large public companies purchase insurance differently than the
average "retail" buyer. Because these large transactions
and large groups of policies cost less to sell and administer, carriers
typically reduce institutional premiums to reflect volume discounts
and economies of scale.
While institutional products are becoming more widely available,
threshold financial requirements still limit access to Institutional
Pricing that offers lower premiums to only a small percent of insurance
buyers.
Experience-Rated Pricing
In addition to the same advantage of lower expenses offered by
institutional pricing, experience-rated pricing also offers the
benefit of lower COI charges.
Experience-rated products are generally either proprietary products
to a given block of businesses or available on a private placement
basis to qualified buyers.
Experience-rated products are based on the superior claims experience
of professionals, business executives and owners, and high net worth
individuals. Because this group enjoys healthier lifestyles and
better health care, they live longer. As a result, this group experiences
lower mortality rates, and products priced for this market generally
have lower COI charges than products sold to retail and institutional
markets.
There is presently no technology for the comparison of permanent
life insurance products. The only existing technology involves the
comparison of "fixed premium and fixed benefit" products,
like term life insurance, where a predetermined premium is stipulated
for a given amount of coverage. In this application, this current
technology involves the creation of a database of published information
and then simply searching this database for this fixed rate based
on the amount of coverage and a number of other factors like age,
gender, risk profile, etc. However, due to the lack of published
information about the pricing of permanent life insurance products,
and due to the number of combinations and permutations of the number
of variables involved in the pricing of an individual life insurance
product, the current database-search-engine-like technology does
not lend itself to the comparison of permanent life insurance products.
For this reason, the consumer is currently relegated to, for lack
of a superior method, seeking out this information on their own,
but limited to the extent that they have a personal relationship
with a sufficiently large number of life insurance agents or brokers
who are properly licensed to sell a given life insurance product
or products as to be able to obtain the information on a wide enough
variety of products to make an informed decision as to the most
suitable product for the given need.
Life insurance policies that are promoted on the basis of a permanent
insurance product are still going to incur life insurance operating
and mortality costs that have to be covered before passing on the
surplus to policy owners in the form of cash value accumulations.
Currently, the consumer is not privy to the assumptions behind the
calculations that make up policy illustrations. In the absence of
this critical information, consumers and their advisors are vulnerable
to financial exploitation and misunderstanding during the policy
selection process.
The premium charge alone depends on several factors including (1)
the exposure of the policyholder and the insured goods or services
to the various insured perils; (2) the degree of risk associated
with the policyholder; (3) the expenses of acquiring and administering
the business; and (4) the profit required by the insurer. Modern
Actuarial Theory and Practice. Booth et al., Chapman (1999) at page
307.
The objective of any method used to compare two policies is to
resolve the best value for the consumer. At least eight (8) distinct
methods of comparing life insurance policy costs have been suggested
in Life & Health Insurance: 13.sup.th Edition. Black, Kenneth,
Jr., Skipper, Harold D., Jr. Prentice Hall (2000), at page 283:
traditional net cost, interest-adjusted net cost, equal outlay,
cash accumulation, comparative interest rate, internal rate of return,
yearly rate of return, and yearly price. However, none of the methods
seamlessly provide a true cost comparison between two permanent
life insurance policies. Nor do the methods suggest resolving a
benchmark value for comparing a plurality of products against an
industry baseline.
As a result, in the current environment, the consumer is confronted
with the challenge of selecting a suitable permanent life insurance
product, that is complex in nature with pricing based on many different
pricing factors, but with limited disclosure of those pricing factors,
and therefore a limited ability to compare pricing information.
In addition, what pricing information that is available is generally
evaluated and compared using an inaccurate and erroneous means,
by default, and the only source for reliable pricing information
is limited a subset of the full universe of products that could
otherwise be suitable. These circumstances have resulted in a process
for selecting and purchasing a suitable permanent life insurance
product in which 1) the consumer frequently seeks the advise of
an independent advisors (e.g. certified public accountants, attorneys,
bankers, certified financial planners, stockbrokers, consultants,
etc.), 2) these independent advisors request pricing information
(i.e. an illustration of hypothetical policy values) from those
agents and brokers with whom they have relationships, 3) these agents
and brokers produce the requested illustration of hypothetical policy
values from data and systems provided them by the insurance companies
whom they represent, and then 4) for lack of an alternative, the
consumer compares these illustrations, often with the help of one
of the advisors, to attempt to identify the most suitable product.
However, each of these illustrations of hypothetical policy values
is comprised of between 6 and 20 pages, consisting of as many as
200+ distinct and unique policy values for each policy under consideration,
involving the many abovementioned variables which may or may not
be disclosed, and that are the result of the computational methodology
with is not disclosed. The consumer is presented with formidable
task of evaluating and comparing hundreds or thousands of data items
in an effort to identify the most suitable product for their needs.
To complicate matters further, different products perform and illustrate
differently, under different planned premium payment scenarios.
In other words, one product may perform competitively as compared
to other products when illustrated assuming one planned premium
payment scenario, but under a different planned premium payment
scenario, that same product may perform and illustrate inferior
to the other products in its peer group. This is due to the construction
of the various loads. For instance, a product with low fixed-type
charges that do not vary with the level of funding (like COIs),
and high premium-based charges (like sales and service loads), will
perform optimally under a minimum premium scenario, but will be
less competitively-priced relative to other peer products under
maximum premium scenarios. Conversely, a product with high fixed-type
charges, and low premium or account-value-based charges (M&E
charges), will perform optimally under a maximum premium scenario,
but will be less competitively-priced relative to peer products
under minimum premium scenarios. The suitability of a given product
is not only dependent upon the pricing of the individual pricing
components and computational methodologies, which may or may not
be disclosed, but is also dependent upon the construction of those
pricing variables under different policy designs.
One drawback of the current evaluation methods is that many policies
are purchased on the basis a single policy-pricing component rather
than overall cost. For instance, some policies are marketed and
sold as "no-load or low-load" policies, implying lower
policy costs and expenses than "load" policies. However,
while these policies do not assess a premium-based expense, these
same products can charge increased COIs, increased fixed policy
fees, and increased account-value-based charges to more than make
up for the foregone premium load. While consumers certainly find
appeal in and are attracted to these products, they may actually
present an inferior value to that of a product that may include
a premium load, but then also offer lower COIs or other policy expenses.
Absent some means of uniformly evaluating and comparing policy costs,
consumers can unwittingly purchase a less suitable product at a
higher cost.
Another drawback of current methods is that "comparison shopping"
for a suitable life insurance policy is severely handicapped, if
not impossible, due to the fact that, while individual policy pricing
components are disclosed, there is no means to compare the cost-competitiveness
nor the pricing-adequacy of these individual cost components. For
instance, when a consumer "goes shopping" for most other
products, be it a tangible product or an intangible product, the
consumer generally has access to the various features associated
with a given product, as well as the cost of either the product,
or the individual product features, or both. For example, when preparing
to buy a tangible product, like a washing machine, consumers can
refer to a variety of product information resources (e.g. Consumer
Reports) to compare products, product features and price before
actually buying the product. Likewise, when preparing to buy an
intangible product, like a mutual fund, consumers can similarly
refer to a variety of product information resources (e.g. Morningstar,
Lipper, etc.) to compare products, product features (e.g. investment
performance and the level of service) and price before actually
buying the product. On the other hand, in the case of life insurance,
there is no such means of comparison-shopping.
Comparison-shopping for permanent life insurance is also severely
handicapped by "relationship barriers," limiting the number
of products that can be considered to some subset of the total universe
of products that could otherwise prove to be suitable. For instance,
agents and brokers are the only reliable source of policy pricing
information for a given product. However, agents and brokers are
limited in the number of products for which they can be a source
of reliable pricing information. This is because they are limited
in the number of insurance companies they can represent for the
following reasons: the insurance company prohibits them from representing
other insurance companies; insurance company pays higher commissions
and offer incentive trips for sales and marketing concentrated with
that carrier; the current distribution system is so fragmented with
so many agents and brokers representing so many different insurance
companies, they are unable to concentrate these sales and marketing
efforts beyond just a limited number of carriers; and without some
means of compiling, organizing and reporting policy pricing information
for the full universe of permanent life insurance products, they
are simply limited in their ability to compile, organize and present
this information themselves.
Because agents and brokers are limited in their ability to gain
access to reliable policy pricing information, the consumer is limited
in the number of products that may be considered by the relationships
they may have with various licensed agents and brokers, and the
relationships that their advisors may have with various licensed
agents and brokers (referred to herein as "relationship barriers").
Present methods of "comparison shopping" for life insurance
involve comparing projected policy pricing based on many unknown
variables that are subject to change, and as such, often result
in "apples-to-oranges" comparisons, and frequently lead
to the selection of a less suitable product than that which is otherwise
available. For instance, absent some uniform means of comparison
shopping, shopping for a permanent life insurance product instead
involves comparing illustrations of hypothetical policy values based
on a variety of variables, some of which are unique to the prospective
insured, (e.g. such as age, income, health profile, lifestyle, etc.),
and others that are unique to the given product. However, because
of these variables that are unique to a given product, comparing
illustrations as a means of determining suitability is frequently
an inaccurate and erroneous process that can lead to inaccurate
and therefore erroneous conclusions. In addition to policy pricing
variables that may be unique to a given product, different products
also employ different methods of computing policy expenses and benefits.
While individual pricing components may be disclosed, these computational
methods are not, again leading to the potential for evaluating different
products on a basis that is thought to be comparable, but which
is actually different. Due to this complex nature of permanent life
insurance products, consumers and advisors are frequently ill-equipped
identify differences in the multifarious computations underlying
the illustration of hypothetical policy values, again leading to
the possibility that this method of policy comparison can lead to
an incorrect conclusion.
The most influential policy cost determinants are the COIs. COIs
are typically hidden from the consumer, and even when they are disclosed,
there is still no uniform means of comparison. This is why term
insurance is so appealing and why there has been resurgence in the
purchase of term insurance.
Policies are purchased based on a projected premium calculated
in an illustration of hypothetical policy values rather than selecting
a policy based on an ascertainable and reasonably sustainable overall
cost. For instance, because the current and only means of comparison
shopping involves comparing illustrations of hypothetical policy
values, which are based on many different variables, which may or
may not be disclosed, there is no way to empirically measure them
on an objective basis.
Policies are purchased on the basis a single policy pricing component
rather than overall cost. For instance, some policies are marketed
and sold as no-load policies, implying lower policy costs and expenses
than "load" policies. However, while no-load policies
do not assess a premium-based expense, these same products can charge
increased COIs, increased fixed policy fees, and increased account-value-based
charges to more than make up for the foregone premium load. While
consumers certainly find appeal in and are attracted to no-load
products, these products can actually present an inferior value
to that of a product that may include a premium load, but then also
offer lower COIs or other policy expenses. Absent some means of
uniformly evaluating and comparing policy costs, consumers can unwittingly
purchase a less suitable product at a higher cost.
Policies are purchased based on hypothetical illustrated performance
rather than actual individual pricing components. For instance,
without some means to identify all individual pricing variables,
it is impossible to compare these variables to actual historical
experience, and in so doing, consider whether or not a given policy
is adequately priced to deliver the illustrated benefits. While
past performance is no guarantee of future results, illustrated
pricing that is consistent with actual mortality and expense experience
would certainly offer the promise of greater reliability than a
product priced on anticipated, but not actual experience. For instance,
the illustration of hypothetical policy values for a given product
may calculate a comparatively low and competitive premium. However,
if that premium is based on inadequate or unrealistic mortality
assumptions (e.g. the COIs illustrated for an actual product required
25% of all insureds in the risk pool to be alive at age 100), then
the actual premium required will be higher than that illustrated.
Absent some means of uniformly evaluating and comparing policy costs,
consumers can unwittingly purchase a less suitable product that
may appear to offer a lower cost, but which actually requires a
higher cost.
Advisors have no independent, objective, information-based resource
to reference in order to provide answers to these client questions,
even though they are asked insurance related questions by their
clients more often than any other party in life insurance value
network. For instance, studies routinely show that advisors work
more closely with their clients and have a more customer-intimate
relationship than any other party to the life insurance value network.
This is validated by another survey finding that advisors are asked
insurance-related questions almost once a week, and is in contrast
to the average life insurance agent who is infrequently asked insurance-related
questions for fear the agent is only compensated directly for answers
that lead to a new sale.
Consumers get caught in the middle between advisors and agents
providing conflicting advise causing confusion, higher costs, less
than optimal advice and a less than suitable product. For instance,
consumers frequently seek the help of advisors in the areas of tax
planning, retirement planning, estate planning, business succession
and continuity planning, overall financial planning, and general
insurance and benefit planning. The nature of this work is typically
focused on the needs of the consumer independent of any given product,
is usually based on planning principals generally available in the
advisory community, and is customarily compensated on a fee-for-service
basis for the time involved in this work. While an insurance product
specialist who could advise the consumer as to the most suitable
product from the complete universe of products available in the
market would be a natural and valuable member of such a planning
team, agents lack the ability to gather, analyze and compare policy
pricing information for a meaningful representation of that full
universe of products, for the reasons discussed above. Absent the
ability to add value by contributing market knowledge and suitability
recommendations from a broad universe of products, agents routinely
"earn their keep" by offering advise in the same areas
as the other members of the planning team. In addition, because
agents are compensated by virtue of a commission on the sale of
a life insurance product, the advice rendered by agents is frequently
related to the sale of a life insurance product. On the other hand,
Advisors frequently render advice with a bias against the purchase
of life insurance, even when empirical data indicates otherwise.
This bias against life insurance seems to be both in response to
the agent bias toward life insurance, and due to the fact that the
agents are the only reliable source of life insurance pricing information.
In other words, advisors and agents are competitors rendering similar
planning advice, but only the agents have access reliable life insurance
pricing information. Advisors must either become willingly dependent
on their competition (i.e. agents and brokers) for information affecting
their recommendations, or must make recommendations that do not
involve life insurance. Of course, this puts consumers in the awkward
position of discerning between the advice and recommendations of
two professionals--one with a bias towards life insurance and one
with a bias against life insurance--which certainly does not serve
the best interest and outcome for the consumer.
Still another drawback of the current system is that detailed policy
information is guarded as proprietary to the insurance carriers.
Accordingly without some means or method to aggregate competitive
product information with the detail necessary for true comparisons,
consumers are left to blindly make purchasing decisions that in
no way correlate to the best product for their needs.
Accordingly, what is needed in the art is method for accurately
comparing the value and performance of a permanent life insurance
policy.
It is, therefore, to the effective resolution of the aforementioned
problems and shortcomings of the prior art that the present invention
is directed.
However, in view of the prior art in at the time the present invention
was made, it was not obvious to those of ordinary skill in the pertinent
art how the identified needs could be fulfilled.
SUMMARY OF THE INVENTION
The present invention comprises a method of evaluating a permanent
life insurance policy comprising the steps of establishing a benchmark
cost of insurance value, obtaining a policy illustration, resolving
an illustrated cost of insurance value from the policy illustration,
and comparing the benchmark cost of insurance value with the illustrated
cost of insurance value.
A matrix of mortality profiles may be established wherein the benchmark
cost of insurance is adjusted in relation to the matrix. The matrix
may include gender-based, lifestyle and pricing method risk values.
Gender-based risk values reflect the differing mortality rates experienced
between males and females over a lifetime. Lifestyle-based risk
values may acknowledge dangerous activities such as tobacco use,
job occupation and the like. Pricing method risk values are based
on the statistical evidence that affluent individuals generally
lead healthier lifestyles while also purchasing substantial policy
values.
In addition to comparing the illustrated cost of insurance value
with the benchmark cost of insurance value, a number of other comparisons
are preferable to gain a fair understanding of the performance and
value of a permanent life insurance policy. Additional steps may
include establishing a benchmark premium load value, resolving an
illustrated premium load value from the policy illustration, and
comparing the benchmark premium load value with the illustrated
premium load value.
Fixed expenses may also be factored by establishing a benchmark
fixed expense value, resolving an illustrated fixed expense value
from the policy illustration, and comparing the benchmark fixed
expense value with the illustrated fixed expense value. Policy earning
values may also be analyzed by establishing a benchmark policy earning
value, resolving an illustrated policy earning value from the policy
illustration, and comparing the benchmark policy earning value with
the illustrated policy earning value.
Policy earning values may be correctly adjusted and analyzed to
account for carrier imposed fees by establishing an array carrier
expenses deducted from the illustrated policy earning value, calculating
a net illustrated policy earning value from the difference between
the illustrated policy earning value and the array of carrier expenses,
and comparing the benchmark policy earning value with the net illustrated
policy earning value.
Resolving a benchmark unit-of-measure against which a given policy
may be compared includes identifying a gender-based risk class for
a given policy to be evaluated (e.g. male, female, unisex [used
in corporate multi-life cases]), establishing an industry-standard
gender-based COI constant, identifying a health profile-based risk
class for a given policy to be evaluated (i.e. preferred plus, preferred,
standard, smoker/tobacco user, substandard), establishing an health
profile-adjusted COI constant, establishing a policy pricing method
(i.e. "Retail", "Institutional", or "Experience-Rated")
appropriate for the individual profile, establishing a pricing-method-adjusted
benchmark COI constant (e.g. 74% of the lifestyle-adjusted COI constant
for "Retail Pricing", 63% for "Institutional Pricing",
and 55% for "Experience-Rated Pricing").
In the next step, a pricing-method-specific benchmark premium load
value is established by calculating a average for all known products
for which data is available, of all premium based policy expenses
to include, but not limited to, State Premium Taxes, Federal Deferred
Acquisition Cost (DAC) Taxes, Sales and Servicing Loads, Other Carrier
Loads, and any other policy expense that is calculated in a fashion
in which the policy premium is a variable that determines the expense,
establishing a pricing-method-specific benchmark policy fixed-expense
value by calculating a average for all known products for which
data is available, of all policy fixed-expenses to include, but
not limited to, Issue Charges, Underwriting Charges, Administration
Charges, and any other policy expense that is calculated in a fashion
in which the expense is expressed as stated, fixed or flat dollar
amount, that can vary by age and policy year, but which is multiplied
by some other variable, like the policy face amount, the number
of months in the year.
An illustrated net average policy earning value (net of deductions
for investment management fees, fund advisory fees, fund operating
expenses and other expenses deducted at the fund account level)
is provided and a pricing-method-specific benchmark policy-value-based
expense value is established by calculating a average for all known
products for which data is available, of all premium based policy
expenses to include, but not limited to, M&E, other carrier
charges, and any other policy expense that is calculated in a fashion
in which the policy account value or policy cash value is a variable
that determines the expense, establishing a pricing-method-specific
"net-net" policy earning value by subtracting the policy-value-based
expense value from the illustrated net average policy earning value,
establishing a present value discount rate equal to the "net-net"
policy earning value (i.e. that rate at which policy values would
otherwise grow but for the deduction policy expenses, establishing
a average Net Amount at Risk (NAR) by calculating the average of
the difference between the death benefit of the hypothetical benchmark
policy at the beginning of the calculation period for the benchmark
policy, minus the sum of: the benchmark policy cash value at the
beginning of the calculation period for the benchmark policy, plus
the benchmark policy premium paid during the calculation period
for the benchmark policy, less the benchmark policy premium loads
deducted during the calculation period for the benchmark policy,
less the benchmark policy fixed policy expenses deducted during
the calculation period for the benchmark policy, plus the benchmark
policy earnings credited to policy cash values during the calculation
period for the benchmark policy, establishing a pricing-method-specific
policy benchmark cost per $1 of insurance by calculating the quotient
of a denominator equal to the average net amount at risk used to
divide a numerator equal to the sum of: the present value of lifestyle-adjusted/pricing-method-adjusted
benchmark COI constants for all policy years, the present value
of pricing-method-specific benchmark premium load values for all
policy years, the present value of pricing-method-specific benchmark
policy fixed-expense values for all policy years.
In an alternative embodiment of the invention, a method of evaluating
the cost competitiveness and the pricing adequacy of an insurance
policy is provided by comparing the cost per $1 of insurance for
a specific policy to the cost per $1 of insurance for the appropriate
benchmark calculated above including the steps of, identifying the
gender for an individual profile (as derived from the proposed illustration
of hypothetical policy values), identifying the health profile for
an individual profile (as derived from the proposed illustration
of hypothetical policy values), identifying the pricing method for
an individual profile (as derived from the proposed illustration
of hypothetical policy values), identifying the COIs for a given
policy (as derived from the proposed illustration of hypothetical
policy values), identifying the premium load values for a given
policy to include, but not limited to, State Premium Taxes, Federal
Deferred Acquisition Cost (DAC) Taxes, Sales and Servicing Loads,
Other Carrier Loads, and any other policy expense that is calculated
in a fashion in which the policy premium is a variable that determines
the expense (as derived from the proposed illustration of hypothetical
policy values), identifying the policy fixed-expense values for
a given policy to include, but not limited to, Issue Charges, Underwriting
Charges, Administration Charges, and any other policy expense that
is calculated in a fashion in which the expense is expressed as
a stated, fixed or flat dollar amount, that can vary by age and
policy year, but which is multiplied by some other variable, like
the policy face amount, the number of months in the year, etc. (as
derived from the proposed illustration of hypothetical policy values),
identifying the illustrated (provided by the user, advisor, or prospective
insurance applicant/policy owner from the illustration of hypothetical
policy values) net average policy earning value (net of deductions
for investment management fees, fund advisory fees, fund operating
expenses and other expenses deducted at the fund account level)
(as derived from the proposed illustration of hypothetical policy
values), identifying the policy-value-based expense values for a
given policy to include, but not limited to, M&E, Other Carrier
Charges, and any other policy expense that is calculated in a fashion
in which the policy account value or policy cash value is a variable
that determines the expense (as derived from the proposed illustration
of hypothetical policy values), establishing a policy-value-based
expense percentage value by calculating the average over the duration
of the policy of the quotient of a numerator equal to policy-value-based
expense values for a given policy divided by a denominator equal
to the sum of: the illustrated cash value at the beginning of the
calculation period for the given policy, plus the illustrated premium
paid during the calculation period for the given policy, less the
illustrated premium loads deducted during the calculation period
for the given policy, less the illustrated fixed policy expenses
deducted during the calculation period for the given policy, plus
the illustrated earnings credited to policy cash values during the
calculation period for the given policy, establishing the "net-net"
policy earning value for a given policy by subtracting the policy-value-based
expense percentage value from the illustrated net average policy
earning value (as derived from the proposed illustration of hypothetical
policy values), establishing a present value discount rate equal
to the "net-net" policy earning value (i.e. that rate
at which policy values would grow but for the deduction of COIs,
premium loads and policy fixed expenses;, establishing an average
net amount at risk by calculating the average of the difference
between the illustrated death benefit at the beginning of the calculation
period for the given policy, minus the sum of: the illustrated cash
value at the beginning of the calculation period for the given policy,
plus the illustrated premium paid during the calculation period
for the given policy, less the illustrated premium loads deducted
during the calculation period for the given policy, less the illustrated
fixed policy expenses deducted during the calculation period for
the given policy, plus the illustrated earnings credited to policy
cash values during the calculation period for the given policy,
establishing a cost per $1 of insurance for a given policy by calculating
the quotient (i.e. the result of dividing) of a denominator equal
to the average net amount at risk for the given policy used to divide
a numerator equal to the sum of: the present value of COI charges
for all policy years for a given policy, the present value of premium
load values for all policy years for a given policy, the present
value of policy fixed-expense values for all policy years for a
given policy, comparing the cost per $1 of insurance for a given
policy to the appropriate benchmark calculated above, establishing
the creditability of illustrated pricing factors by identifying
the illustrated basis for underlying cost of insurance charges,
expenses and earnings assumptions (e.g. pricing based on actual
insurance company mortality, expense or investment experience, or
pricing based on some assumed improvements in their current experience)
under the premise that past performance is no guarantee of future
results, but is certainly an indication of the credibility of future
illustrated policy performance, and establishing the reliability
of illustrated pricing factors by identifying the circumstances
in which an insurance company may change the actual pricing of a
given product to be different than that illustrated (e.g. Can policy
pricing be changed for just the product under evaluation, or must
the carrier change pricing for all products in a given pool? Can
policy pricing be changed for in force policies without including
the same change in newly sold policies? Are there any outside influences
effecting the change in policy pricing?).
Another alternative embodiment of the invention includes a method
of estimating pricing for a given policy by collecting varying amounts
of policy pricing data related to cost of insurance rates, premium
loads, fixed policy expenses, cash-value-based expenses, and illustrated
earnings rates that is independent of the insurance company underwriting
the given product comprising the steps of establishing two methods
of collecting policy pricing data: (1) an Estimated Method giving
the Advisor/user the ability to quickly, easily and anonymously
enter a sampling of policy pricing data in varying amounts from
a given illustration of hypothetical policy values that is then
used to estimate policy pricing at various levels of precision,
and (2) an Actual Method giving the user the ability to supply all
policy pricing data elements from a given illustration of hypothetical
policy values for all policy years which is then used to calculate
actual policy pricing with maximum precision, collecting a gender-based
risk class for a given policy to be evaluated (e.g. male, female,
unisex [used in corporate multi-life cases]), establishing an industry-standard
gender-based COI constant, collecting a health profile-based risk
class for a given policy to be evaluated (i.e. preferred plus, preferred,
standard, smoker/tobacco user, substandard), establishing an health
profile-adjusted COI constant, establishing a policy pricing method,
establishing a pricing-method-adjusted COI constant, establishing
a method of determining the Net Amount at Risk (NAR) for a given
policy year for a given policy by calculating the difference between
the death benefit at the beginning of the calculation period for
a given year of a given policy less the sum of: the illustrated
cash value at the beginning of the calculation period for the given
policy, plus the illustrated premium paid during the calculation
period for the given policy, less the illustrated premium loads
deducted during the calculation period for the given policy, less
the illustrated fixed policy expenses deducted during the calculation
period for the given policy, plus the illustrated earnings credited
to policy cash values during the calculation period for the given
policy, identifying the Cost of Insurance Charge/Deduction (COI
Expense) for a sampling of policy years for a given policy (as derived
from the proposed illustration of hypothetical policy values), establishing
a method of determining Cost of Insurance Rates per $1 of policy
death benefits (COI Rate) for a given policy year for a given policy
by calculating the quotient (i.e. the result of dividing) of a numerator
equal to the illustrated Cost of Insurance Charge/Deduction (COI
Expense) for the given policy years for a given policy divided by
a denominator equal to the Net Amount at Risk for the same policy
years of the same policy, establishing a method of estimating Cost
of Insurance COI charges for a given policy by determining the ratio
of COI Rates from the sampling of policy years for a given policy
divided by the Benchmark COI Rate, which is then multiplied by the
Benchmark COI Rate for all policy years, establishing a method of
varying the ease of supplying COI data inversely with calculating
the precision of the COI estimate by providing the user with the
ability to complete a minimum of 3 random iterations for disparate
policy years to achieve maximum ease/minimum precision, 1 iteration
for each 10 policy years for medium ease and precision, and 1 iteration
for each 5 policy years for minimum ease/high precision, collecting
the premium load values for sampling of policy years (1 sample for
each year in which the premium load is different/unique) for a given
policy (as derived from the proposed illustration of hypothetical
policy values), collecting the policy fixed-expense values for a
sampling of policy years (1 sample for each year in which the fixed-expense
value is different/unique) for a given policy (as derived from the
proposed illustration of hypothetical policy values), collecting
the illustrated net average policy earning rate (net of deductions
for investment management fees, fund advisory fees, fund operating
expenses and other expenses deducted at the fund account level)
for a sampling of policy years (1 sample for each year in which
the net average policy earning rate is different/unique) (as derived
from the proposed illustration of hypothetical policy values), collecting
the policy-value-based expense values for a sampling of policy years
(1 sample for each year in which the net average policy earning
rate is different/unique) for a given policy (as derived from the
proposed illustration of hypothetical policy values), establishing
a policy-value-based expense percentage value by calculating the
average over the duration of the policy of the quotient (i.e. the
result of dividing) of a numerator equal to (i) policy-value-based
expense values for a given policy divided by a denominator equal
to the sum of: the illustrated cash value at the beginning of the
calculation period for the given policy, plus the illustrated premium
paid during the calculation period for the given policy, less the
illustrated premium lo ads deducted during the calculation period
for the given policy, less the illustrated fixed policy expenses
deducted during the calculation period for the given policy, plus
the illustrated earnings credited to policy cash values during the
calculation period for the given policy, establishing the "net-net"
policy earning value for a given policy by subtracting the policy-value-based
expense percentage value from the illustrated net average policy
earning value (as derived from the proposed illustration of hypothetical
policy values), establishing a present value discount rate equal
to the "net-net" policy earning value (i.e. that rate
at which policy values would grow but for the deduction of COIs,
premium loads and policy fixed expenses, establishing a method for
estimating premium load values for all policy years from premium
load values collected for the sampling of policy years by calculating
the present value of each unique premium load value for each policy
year, establishing a method for estimating policy fixed-expense
values for all policy years from premium load values collected for
the sampling of policy years by calculating the present value of
each unique policy fixed-expense value for each policy year, establishing
a method for estimating policy-value-based expense values for all
policy years from policy-value-based expense values for a sampling
of policy years by calculating the present value of each unique
policy-value-based expense value for each policy year, establishing
a method of estimating the cost per $1 of insurance for a given
policy by calculating the quotient (i.e. the result of dividing)
of a denominator equal to the average estimated net amount at risk
calculated for the sampling of year for which data was provided
for the given policy which is then used to divide a numerator equal
to the sum of: the present value of estimated COIs for all policy
years for a given policy, the present value of estimated premium
load values for all policy years for a given policy, and the present
value of policy fixed-expense values for all policy years for a
given policy.
Another embodiment of the invention includes a method of dynamically
increasing the precision of the benchmark cost per $1 of insurance
computation over time by continually compiling policy pricing information
in a database comprising the steps of establishing a database for
compiling: policy pricing data related to cost of insurance rates,
premium loads, fixed policy expenses, cash-value-based expenses,
and historical earnings rates, whether pricing factors are based
on actual or projected insurance company experience as to mortality,
expense or investment experience, and changes to pricing factors
over time, and the circumstances surrounding the changes. Establishing
an initial benchmark unit-of-measure for evaluating the cost competitiveness
and the pricing adequacy of an insurance policy using the benchmark
for a given pricing method created above, populating the database
with the initial unit-of-measure/benchmark for evaluating the cost
competitiveness and the pricing adequacy of an insurance policy
for each pricing method, populating/updating the database with actual
policy pricing data collected from public domain information sources
(e.g. the product prospectus or private offering memorandum for
a given policy, State Department of Insurance filings for a given
product from a given carrier, etc.) as that data becomes available
(i.e. as new products are filed with the SEC and approved by the
State Department of Insurance), populating/updating the database
with actual policy pricing data collected directly from insurance
companies (e.g. from illustrations of hypothetical policy values
for a given product generated by computer software provided by the
respective insurance company, and written product guides published
by the respective insurance company), populating/updating the database
with estimated pricing data calculated above., establishing over
time an average of actual and estimated policy pricing data collected
and compiled in the database in order to compute an additional/new
replacement benchmark that represents the average policy pricing
for each pricing component as they relate to cost of insurance rates,
premium loads, fixed policy expenses, cash-value-based expenses,
and illustrated earnings rates.
A method of distributing insurance policies in which the selection
and ultimate purchase of the product is determined by both qualitative
factors (the perceived level of service associated with the insurance
company and the distributor/servicing organization, the perceived
financial strength and claims paying ability of an insurance company,
etc.), and quantitative factors (like policy costs, the credibility
of illustrated policy pricing assumptions, and the reliability of
those pricing assumptions as it relates to actual policy performance
over time) comprising the steps of: establishing an objective and
uniform means of identifying, calculating, benchmarking and comparing
both the cost-effectiveness and the pricing adequacy of an insurance
policy, establishing an objective and uniform means of identifying
and quantifying the credibility of illustrated policy pricing factors,
establishing an objective and uniform means of identifying and quantifying
the reliability of illustrated policy pricing factors, establish
a means of collecting policy pricing data on any/every product available
in the marketplace, categorizing all policy pricing data into the
following 4 pricing elements: Cost of Insurance charges, premium
load values including, but not limited to, State Premium Taxes,
Federal Deferred Acquisition Cost (DAC) Taxes, Sales and Servicing
Loads, Other Carrier Loads, and any other policy expense that is
calculated in a fashion in which the policy premium is a variable
that determines the expense, policy fixed-expense values including,
but not limited to, Issue Charges, Underwriting Charges, Administration
Charges, and any other policy expense that is calculated in a fashion
in which the expense is expressed as stated, fixed or flat dollar
amount, that can vary by age and policy year, but which is multiplied
by some other variable, like the policy face amount, the number
of months in the year, etc., policy-value-based expense values including,
but not limited to, M&E, Other Carrier Charges, and any other
policy expense that is calculated in a fashion in which the policy
account value or policy cash value is a variable that determines
the expense, normalizing each of the 4 types of policy expenses
to adjust for timing differences in the assessment of the charges,
compiling normalized policy pricing data all policies available
in the marketplace in this standardized format that lends itself
to easy retrieval and comparison, establish a means of dynamically
improving the precision of the pricing data as more and more policy
pricing data is collected over time, making the data available to
Advisors such that they can use the data to determine the most suitable
product for their client from the full universe of products available
in the marketplace (not just those products which a particular agent
or broker may be licensed to sell, which is by marketplace definition
only those products for which he/she has dependable pricing information).
In a preferred embodiment of the invention, the following economic
incentives are provided to motivate Advisors of prospective insurance
buyers and prospective insurance buyers themselves to use the service:
(1) prospective buyers will be motivated by promise of premium savings
associated with identifying most cost-effective policy, and the
peace of mind associated with identifying a responsibly-priced policy
with credible and reliable pricing assumptions, (2) advisors will
be motivated by the ability to provide a new service that is consistent
with their existing servicing offerings (i.e. an informational reference
service that can be used to research and based recommendations to
their clients), that meets their rules for independence, and that
fits within their existing fee-for-service compensation model; (3)
advisors will also be motivated to use the data by the ability to
be transitionally compensated; (4) motivating Advisors to introduce
other Advisors to the service by providing an economic incentive
to virally market the service (e.g. waive subscription fees for
any Advisor who causes another Advisor to become registered with
the service); (5) motivating Advisors to encourage their clients
to enter into insurance policy transactions through the service
by providing an economic incentive to purchase the policy through
a fulfillment center affiliated with the service (e.g. waive subscription
fees for any Advisor who causes a transaction to be closed through
an affiliated fulfillment center); and (6) establishing co-marketing
and fulfillment agreements with affiliated fulfillment centers who
are properly licensed with all insurance companies in all 50 States
such that an advisor can research, recommend and facilitate the
purchase of the most cost-effective, yet responsibly priced policy
available in the entire marketplace.
It is therefore an object of the present invention to provide a
method to quantify the value of a permanent life insurance product
against an industry benchmark.
It is another object of the present invention to provide a means
to compare two competing permanent life insurance products.
It is to be understood that both the foregoing general description
and the following detailed description are explanatory and are not
restrictive of the invention as claimed. The accompanying drawings,
which are incorporated in and constitute part of the specification,
illustrate embodiments of the present invention and together with
the general description, serve to explain principles of the present
invention.
These and other important objects, advantages, and features of
the invention will become clear as this description proceeds.
The invention accordingly comprises the features of construction,
combination of elements, and arrangement of parts that will be exemplified
in the description set forth hereinafter and the scope of the invention
will be indicated in the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
For a fuller understanding of the nature and objects of the invention,
reference should be made to the following detailed description,
taken in connection with the accompanying drawings, in which:
FIG. 1 is a functional block diagram illustrating the comparison
of an illustrated insurance policy and a database of benchmark values
embodied in a client-server architecture.
FIG. 2 is a functional block diagram illustrating the process of
resolving a cost of insurance constant.
FIG. 3 is a functional block diagram of the process of resolving
a benchmark premium load value.
FIG. 4 is a functional block diagram of the process of resolving
a benchmark fixed expense value.
FIG. 5 is a functional block diagram of the process of resolving
an illustrated net average policy earning value.
FIG. 6 is a functional block diagram of the process of a benchmark
policy-value-based expense value.
FIG. 7 is a functional block diagram of the process of resolving
a Net.sub.Net policy earning value from the illustrated net average
policy earning value and the illustrated policy-value based expense
value.
FIG. 8 is a functional block diagram of the process an average
net amount at risk.
FIG. 9 is a functional block diagram of the process of resolving
a pricing policy benchmark.
FIG. 10 is a functional block diagram illustrating the resolution
of a true "net-net" average policy earning value compared
between two insurance policies.
FIG. 11 is a partially exploded pie chart showing an exemplary
breakdown in premiums.
FIG. 12 is a functional block diagram illustrating the data path
of insurance policy illustrations according to the current invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
Referring initially to FIG. 1, it will there be seen that an illustrative
embodiment of the present invention is denoted by the reference
number 10 as a whole wherein the invention comprises establishing
a benchmark cost of insurance value 20 from an aggregate of benchmark
values including cost of insurance benchmark 21, premium load benchmark
22, fixed expense benchmark 23 and policy earning benchmark 24.
In a preferred embodiment of the invention, a client data server
30 is in data communication with the database 20 by a first network
connection 31. Data relating to an illustrated policy 40 is entered
into the client data server 30 via a second network connection 32.
This data may originate from agents, brokers, carriers and even
public record sources. An advisor client station 50 is in data communication
with the client data server 30 via a third network connection 33.
The illustrated policy 40 is analyzed by the client data server
30 to resolve an illustrated cost of insurance value. The illustrated
cost of insurance value is then compared to the benchmark cost of
insurance value 20. The results are then transmitted via the third
network connection 33 from the client data server 30 to the advisor
client station 50. The results may be displayed on the advisor client
station 50 by a proprietary network application or, preferably,
by a web browser means.
For illustrative purposes, the logistics of the method may include
implementing a Microsoft SQL 2000 or Oracle database server to act
as a repository for the benchmark data. The client data server 30
may be a Microsoft Windows 2000 Advanced Server or Datacenter and
the first network connection 31 may be an Ethernet-type LAN connection
between the database server and client data server 30. As will be
discussed below, the illustrated policy 40 may be initially received
by fax, email, postal mail or in a database structure such as Microsoft
Excel, Paradox, DB2, or XML. Alternatively, the illustrated policy
40 may be received from the advisor client station 50 through the
third network connection 33.
FIG. 2 illustrates the method of establishing a benchmark of mortality
profiles. A gender-based risk class is identified for a given policy
to be evaluated 60. This is typically split in male, female and
unisex categories. The industry-based COI is then applied to the
gender-based risk class 70. In this illustrative example, a male
risk class is selected. Next, a health profile is identified 80.
Typical categories include preferred plus, preferred, standard,
smoker and substandard, each categories representing a higher mortality
risk respectively. The COI is then adjusted according to the health
profile 90. In this example, we continue to use the male profile
in conjunction with the "preferred"health category. Finally,
a pricing method co-efficient is established 100. The pricing method
coefficient factors affluence into the solution based on empirical
data that, all other variables being equal, wealthier individuals
tend to have better access to health care and thus, require less
claims be paid to their beneficiaries. For example, pricing methods
may be categorized as retail, institutional and experience-rated.
In our example, individuals categorized as "retail" tend
to experience only 74% of the average mortality. Institutional individuals
only experience 63% of the average mortality for their personal
profile. Finally, experience-rated individually only suffer 55%
of the average mortality for their personal characteristics. Accordingly,
it can be understood that experience-rated individuals are more
profitable to insure for carriers, as those individuals are statistically
healthier. By the same token, individuals within the experience-rated
category are reasonably entitled to pay less for life insurance
since they are a superior risk for the carriers to assume.
As evident by the above, a large number of industry standard, or
benchmark, COIs may exist for so many distinct profiles. Expanded
further, these benchmarks must be available for an individual's
maximum lifespan, typically up to 100 years. Therefore, a large
matrix must be populated with benchmarks to provide a meaningful
analysis of illustrated policies under consideration.
FIG. 3 illustrates the resolution of a benchmark premium load value
120 taken from the average of industry loads 110 including state
premium taxes 111, DAC taxes 112, sales and service fees 113 and
other carrier loads 114. FIG. 4 illustrates the resolution of a
benchmark fixed expense value 140 taken from the average of industry
expenses 130 including issue charges 131, underwriting charges 132,
administration charges 133 and other expenses 134. Carriers often
publish average policy earning values regarding the performance
of their products. In FIG. 5, a net average policy earning value
is resolved by subtracting management fees from the illustrated
policy earning value to achieve the illustrated net average policy
earning value 150. In FIG. 7, M&E charges 161 are deducted from
the illustrated net average policy earning value 150 to resolve
the net-net illustrated policy earning value 180. Once this illustrated
net-net value is resolved for the illustrated policy, it may be
compared to the benchmark net-net value 170 resolved in FIG. 6 by
averaging industry expenses 160 such as M&E charges 161 and
other related expenses 162. FIG. 10, illustrates how two illustrated
policies having the same policy earning values vary substantially
in the present invention. Both policies A and B have illustrated
rates of 10.6%. However, Policy A charges a management fee of 0.6%
while Policy B only charges 0.4%. At this point Policy A has a net
rate of 10.0% while Policy B has a net rate of 10.2%. When M&E
risk charges are imposed, Policy A's rate is reduced to 9.8% while
Policy B's rate is maintained at 10.2%. Therefore, assuming all
other factors are equivalent, Policy B is more efficient.
FIG. 8 illustrates the variables 190 and equation 200 for the average
net amount at risk. Net amount of risk is generally defined as the
actual amount of pure life insurance protection, calculated as the
difference between the policy reserve at that point and the face
amount. For instance, it is common for permanent life insurance
policies with a level death benefit to be priced such that policy
cash values and policy death benefits become equal by design at
the maturity or endowment age of the policy (defined by statute
between age 95 and 100 depending on the policy). As such, as cash
values increase and the death benefit remains level/the same, the
"net at risk" death benefit (or net amount at risk) declines.
FIG. 9 illustrates the variables 210 and equation 220 for resolving
a pricing policy benchmark.
FIG. 11 illustrates the overall breakdown of costs that are attributable
to insurance premiums. For illustrative purposes, carriers and taxes
account for 13% of the premiums, sales and service account for another
13%, and claims account for the remaining 74% of premium payments.
As discussed previously, if the carrier's policy insures only healthy,
affluent individuals, then the claims percentage might reasonably
be expected to drop from 74% to 55%. With less claims to pay, the
carrier and agents may earn a greater portion of the premiums paid
or lower the premiums on the policy to make the policy more attractive
to the buyer. FIG. 11 also illustrates the misconception of purchasing
a policy simply on the basis of the "loads." Even if the
sales, service and carrier expenses are high, if the claims (COIs)
are low, the policy might be equivalent or even superior to a "no-load"
policy.
FIG. 12 shows the proprietary boundary 230 currently held by insurance
carriers and their respective agents. Although some public record
disclosures are mandated depending on the jurisdiction, freely obtaining
COIs from carriers on a wholesale basis is not yet available. However,
the present invention provides for the aggregation of transmitted
policies 240 into an illustration database 250. As illustrated policy
information is collected, benchmark values may be resolved from
empirical data rather than theoretical and direct comparisons between
two or more individual policies may be achieved.
It will be seen that the objects set forth above, and those made
apparent from the foregoing description, are efficiently attained
and since certain changes may be made in the above construction
without departing from the scope of the invention, it is intended
that all matters contained in the foregoing description or shown
in the accompanying drawings shall be interpreted as illustrative
and not in a limiting sense.
It is also to be understood that the following claims are intended
to cover all of the generic and specific features of the invention
herein described, and all statements of the scope of the invention
which, as a matter of language, might be said to fall therebetween.
Now that the invention has been described, |