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Exposure
basic unit of risk underlying insurance premium, measures how much risk the insurer is subject to before losses
Exposure base
unit used to measure risk, price, and compare risk across policies
Criteria for Exposure Bases
Proportional—> scales directly with expected losses
Practical—> objective, easy and inexpensive to obtain and verify
Precedence—> considerate of historical precedence as it is costly for industry to change an existing exposure base
reported losses
incremental paid losses + change in case reserves during time period
Main Considerations for aggregating to appropriate time grouping
1.) Match premium and exposure to losses, need to be on like for like basis
2.) Use most recent data available
3.) Minimize cost of data collection retrieval
Time Grouping Analysis: Calendar Year Pros and Cons
Pros: results are final immediately after year is over
Cons: Poor matching in time between premiums/exposures and losses
Time Grouping Analysis: Calendar/Accident Year Pros and Cons
Pros: better match in timing between premium and losses. Best for short tailed business
Cons: future development must be estimated since AY losses develop over time
Time Grouping Analysis: Accident Year Pros and Cons
Pros: slightly better than calendar/accident year
Cons: premium and exposure data subject to development
Time Grouping Analysis: Policy Year Pros and Cons
Pros: true match between premium and exposures. best for long tailed business
Cons: longest of any grouping to develop
Time Grouping Analysis: Report Year Pros and Cons
Pros: # of claims at YE known, helpful in estimating IBNER
Cons: not useful for estimating IBNYR
Types of External Data
Statistical plans: aggregate data cross companies and produce analyses or rates that companies can use
Other aggregated industry data
Competitor rate filings+ manuals
Other 3rd party data: economic or geo-demographic data
Principles of P&C Insurance Ratemaking
1.) Rate is estimate of expected value of future costs
2.) Rate must be sufficient to pay claims, cover expenses, and provide return for taking on the risk
3.) Rate must be adequate at individual level
4.) Rate is appropriate if it is not excessive, not inadequate and not unfairly discriminatory
External Influences of Rates
traffic density, urbanization/population density, legal environment, medical costs, repair costs, weather/cat exposure, crime/fraud, economic conditions, infrastructure
Types of Adjustments to Historical Data (8)
Large events and anomalies
One time changes
Trends
Development
Load for UW expenses and ULAE
Set UW profit goal
Reinsurance costs
Credibility
Adjustments to Historical Data: large events and anomalies
replace large claims and cat events in historical data with long term average or modeled estimate
Adjustments to Historical Data: one time changes
adjust for known difference from future period due to rate changes, law changes, coverage changes and benefit changes
Adjustments to Historical Data: trends
forecast for changes in cost and mix of business
Basic limits
limits assumed in insurer’s basic rate when calculating premium. Losses above may be handled separately with ILFs or excess loss loadings
Rating Factors
used to bring premiums to basic limits when wanting losses to basic limits
basic limit premium = actual premium/ rating factor
Excess loss loading
need to decide on loading which accounts for portion of losses above the cap
Non pricing measures to deal with risks from cat losses
restrict writings in high risk areas
require higher deductibles in high risk areas
purchasing reinsurance
Rate changes
adjusting for price when cost or risk changes
changes indicate a change in price charged per unit of exposure
Direct Effect
obvious impacts on premium, losses, or expenses resulting from a change
Indirect Effect
impact to premium, losses, or expenses from changes in human behavior that are consequences of one time changes
difficult to quantify but is incorporated into trend adjustments
On-Leveling Premium
restates historical premium at current rate levels
want to charge same amount each time period regardless of ups and downs so premium is table and consistent
Methods to On Level Premium
Extension of Exposures
Parallelogram Method
Use Actual writing distributions and group data by rate level
Extension of Exposures
take old policies and pretend today’s rates were in effect back then. Then recalculate what the premium would have been
Pros: most accurate method
Cons: getting detailed data, computing power needed, hard to make assumptions for new rating variables with no historical data
Parallelogram Method
used to group policy data and adjust historical premium by average factor for each historical period
pretty much weighted avg of rate per each period on on exposure period graph then divide it from most recent rate
Pros: quick to calculate
Cons: assumes policies are written evenly throughout historical period and can be inappropriate for class ratemaking if effects vary by class
Trends
adjusting historical losses to future cost levels due to changes in underlying costs of claims
Overlap Fallacy
no overlap between development and trending
trending: reflects difference in ultimate from one historical period to the next (goes down triangle rows)
Development: brings data from each historical period to ultimate level ( goes across columns in triangle)
Development
changes overtime to costs or premiums within an exposure period
Reasons for Changes in Loss Triangles
Changes in case reserve adequacy
Changes in settlement rates
Changes in mix of business
Growing or shrinking book of business
Tort Reform
Chain Ladder/ Development Method: definition
uses past development patterns and applies to latest data forecast to estimate ultimates
do not apply trends to this method!!!!!!
Chain Ladder/ Development Method: assumptions
-future claim development is similar to prior development
-claims observed for immature period tell you something about claims yet to be observed
-consistent claims processing
-stable mix of claims types, policy limits and deductibles, reinsurance limits
Ways to determine a tail factor
specialty study
Industry benchmarks
fitting curve to LDFs and extrapolating tail
using best judgement
Methods for Pricing UW Expenses
All Variable Expenses
Premium Based Projection Method
Exposure/Policy based Projection
All Variable Expense
treat all UW expenses as variable to premium
find ratios(variable and fixed) of all expenses and to get variable expense ratio. By doing this you’re assuming all expenses are variable
Pros: easy to apply and works best when expenses vary with premium
Cons: inaccurate results if some expenses are truly fixed
Premium Based Projection Method
separately calculates fixed and variable expense ratios
pros: more accurate then all variable expense, simple and recognizes fixed costs exist
cons: historical expenses may not reflect future expectations, changes in premium expenses can distort ratios, allocating countrywide fixed expense by prem can unfairly charge states with increased avg premium more
Permissible Loss Ratio
maximum LR an insurer can have while still achieving its target profit
Rate Indication Methods
Pure Premium Method
Loss Ratio Method
Overall Rate Indication Purpose
determine whether current rates are adequate, excessive or inadequate and to calculate the needed rate change
Indicated rate
rate level that covers expected losses+ expenses + target profits
Types of Coverage Triggers
Occurrence
Claims Made
Occurrence
coverage depends on when accident occurs regardless of reported date (subject to statute of limitations)
Claims Made
coverage depends on whether claim is reported during the policy period, does not care about when the claim actually happened as long as event happens after specified retroactive date
reduces report lag from pricing risk compared to occurrence
Tail coverage
policy covering accident occurring during the claims made term but reported later
usually used when switch from claims made to occurrence policy
Report Year Diagram
used to understand which ultimate loss costs are covered by which policies
Report Year—> signifies when claim was reported
Report Lag—> Report Year - Accident Year
Claims Made Ratemaking Principles
Claims made will cost less than occurrence as long as cost increases
Claims made adjust to trend changes faster so pricing errors from sudden trend shifts are usually smaller
Shift in reporting patterns are less likely to affect cost of a mature claims made vs occurrence
Claims made reduce risk of reserve inadequacy
Investment income is less under claims made vs occurrence policies
Risk Classification
group risks with similar risk characteristics for purpose of setting price, helps mitigate adverse selection
Adverse Selection
insurer underprices high risk insured relative to competition causing risker individuals to concentrate in that insurers poll and lead to losses
Favorable selection
insurer attracts lower risk insured than average
Skimming the cream
identifying a lower cost group of insured that has not been identified by competition, and recognizing identifying difference in underwriting or marketing instead of rates
Criteria for evaluating rating variables
Statistical Criteria
Operational Criteria
Social Criteria
Legal Criteria
Statistical Criteria
difference in loss costs between classes is real, different groups have truly different risk levels
risks within same class should have similar expected loss levels
need enough stable data to produce reliable estimates
Operational Criteria
classes clearly defined, practical to administer, and easy to verify without excessive cost or manipulation
Social Criteria
classification should be fair, socially acceptable, affordable, behaviorally relevant and respectful of privacy
Legal Criteria
in compliance with laws and regulations
Univariate Classification
covers how to determine indicates rates for a single variable at a time
how much more or less different risk groups should pay relative to each other
studying one risk factor at a time
Relativity
measure how much more or less a risk group is expected to cost compared to a baseline group
Univariate Pricing Approaches
goal: find indicated relativity to a base class
methods- performed with and without credibility
pure premium approach
loss ratio approach
adjusted pure premium approach
Pros and Cons of Univariate Analysis
pros: simple to calculate and intuitive
cons: does not properly account for impact of correlated variables
Multivariate Classification
analysis incorporates impact of multiple variables at a time
most common method is Generalized Linear Models (GLMs)
Generalized Linear Model
create formulaic relationship between multiple predictor variables and a response variable
GLM Diagnostics
standard errors
deviance tests
time consistency
validation test
GLM Diagnostics: Standard Errors
measures how much that estimate would vary from sample to sample
smaller error—> more precise
GLM Diagnostics: Deviance Tests
compares models, commonly used in deciding whether to fit GLM with or without the variable in question
GLM Diagnostics: Time Consistency
estimated parameters consistent overtime
GLM Diagnostics: Validation test
measure model performance on unseen data
Data Mining Techniques: definition
help identify, evaluate, and quantify relationships between risk characteristics and loss experience
Data Mining Techniques: methods
Factor Analysis
Cluster Analysis
CART( Classification and Regression Trees)
MARS( Multivariate Adaptive Regression)
Neural Networks
Factor Analysis
reduce number of variables needed in classification
most common types is principle components
Cluster Analysis
combine similar risks into groups
MARS( Multivariate Adaptive Regression)
turn continuous variables into categorical variable
Neural Networks
can help identify unknown interactions between variables
Challenges of Territorial Ratemaking
highly correlated with other rating variables
Set territories to small areas which have limited credibility
Increased Limit Factors (ILF) Purpose
used to determine how much premium should increase as policy limit increases
Increased Limit Factors (ILF) Assumptions
-all UW expenses and profits are variable and don’t vary by limit
-frequency and severity independent
-frequency is the same for all limits
Limited Average Severity at limit H
severity assuming every loss regardless of actual policy limit is capped at H
Reasons for Deductibles
lower premium for insured because less coverage
eliminates claims below deductible
incentive for insured to mitigate losses since they pay amount below deductible
reduces cat exposure
Loss Elimination Ratio (LER) definition
measure percentage of expected losses that are eliminated by applying a deductible
Loss Constant
flat charges applied to WC premium to cover expected small losses that are not fully reflected in experience rating. This equalizes loss ratios between small and large risk
Insurance to Value (IVT)
ensures a property is insured for an amount close to its replacement value
coverage amount/ replacement cost
Issues when properties are insured less than full replacement cost amount
1.) Insured will not be covered in the event of a total or near total loss
2.) If insurer assumes every home is insured to full replacement value but some home are underinsured
- insured value used in rating is too low
-actual potential loss is based on full replacement cost
-insurer charges too little premium relative to risk
Coinsurance
used to deal with underinsurance
insurer requires property to be insured a minimum percentage of its value, if not there will be a penalty which will be the insurer only paying a fractions of the loss (pays ITV%)
Complements of Credibility Criteria
Accurate: has low variance
Unbiased: on average, equal to what you are estimating
Statistically independent from own data to prevent compounding errors
Easy to compute: otherwise hard to explain
Logical relationship to base statistic: easy to justify to others
Complements in First Dollar Ratemaking Methods
1.) use loss costs from larger group that includes group being rated
2.) Use loss costs from larger group that is related to (but does not include) the subject
3.) rate change from larger group applied to present rates
4.) Harwaynes Method
5.) Trended Present Rates
6.) Competitor rates
Experience Rating
adjust premium based on insureds past claim history on prior policy terms
Experience modification factor
multiplier that adjusts policy’s premium based on insured past loss experience
Experience Rating Plans
ISO CGL
NCCI
Complements in Excess Ratemaking Methods
Increased Limits Analysis
Lower Limits Analysis
Limits Analysis
Schedule Rating
adjust premium for individual risk that are not in premium calculations
premium calculations only capture quantifiable systemwide factors
captures hard to measure, not in data, or unique to individual risk
Large Deductible Policies Considerations
Who will handle claims?
Application of deductible
Deductible processing; who will pay for losses and how
Risk margin
Insured handles claims implications
may hire TPAs
insurer should be cautious insured has less incentive to keep losses below deductible
Insurer paying for all losses implications
will seek reimbursement from insured for loss below the deductible
as a result of paying all losses first:
insurer will get extra cost for billing and processing
credit risk in case insured is unable to pay
-both of these are included in expenses in premium calculations
Insurer risk margin implications
insurer is taking on more risk uncertainty, will charge higher margin for this
Retrospective Rating
use insured’s loss experience during the current policy period to determine the current policy period
Premium flow chart
Manual premium —> Standard premium —> Basic Premium —> Retrospective Premium
Manual Premium
premium based on manual rates and exposures before any individual risk adjustments
Standard premium
premium after applying all rating modifications, before retrospective adjustments
Basic Premium
portion of premium that covers fixed costs (not losses)