2. Pieces of the PuzzlePieces of the Puzzle
• Compare:Compare:
• Quote Cost FactorsQuote Cost Factors
• Pay-in amountsPay-in amounts
• CollateralCollateral
• Projected cost at expected loss levelProjected cost at expected loss level
• Projected cost at higher confidence levelsProjected cost at higher confidence levels
• Retention comparisonsRetention comparisons
• Financial Risk Retention ToleranceFinancial Risk Retention Tolerance
• Discounted After-Tax CostDiscounted After-Tax Cost
• Policy Forms and Program AgreementsPolicy Forms and Program Agreements
3. Where do we put the puzzle pieces?Where do we put the puzzle pieces?
MetricMetric Why the Metric is not a perfect decisionWhy the Metric is not a perfect decision
discriminatordiscriminator
Quote Cost FactorsQuote Cost Factors Produces costs that vary with exposures, losses, tax andProduces costs that vary with exposures, losses, tax and
assessment rates, claim counts and claim types so mayassessment rates, claim counts and claim types so may
ultimately differ from actual.ultimately differ from actual.
Pay-in amountsPay-in amounts May not bear any relation to ultimate cost.May not bear any relation to ultimate cost.
CollateralCollateral Cost, amount, and form could vary over time with loss payouts,Cost, amount, and form could vary over time with loss payouts,
development, choice of factors and methodology, insured’sdevelopment, choice of factors and methodology, insured’s
financial condition, insured-insurer relationship.financial condition, insured-insurer relationship.
Cost at Expected LossCost at Expected Loss Actual loss will almost certainly differ from projected and actualActual loss will almost certainly differ from projected and actual
loss outcomes may be affected by choice of carrier or TPA orloss outcomes may be affected by choice of carrier or TPA or
degree of investment in loss control and safety.degree of investment in loss control and safety.
Cost at Higher Confidence LevelsCost at Higher Confidence Levels Insured’s risk aversion levels will affect their evaluation. MayInsured’s risk aversion levels will affect their evaluation. May
understate risk if underlying distribution and parameterunderstate risk if underlying distribution and parameter
assumptions don’t match reality as is often the case.assumptions don’t match reality as is often the case.
Retention ComparisonsRetention Comparisons Assumes we know underlying loss distributions and parametersAssumes we know underlying loss distributions and parameters
and that they do not change over time; cost of capital constantand that they do not change over time; cost of capital constant
over time; loss outcomes don’t vary by insurer or TPA.over time; loss outcomes don’t vary by insurer or TPA.
Financial Risk Retention ToleranceFinancial Risk Retention Tolerance Ad hoc rules of thumb that yield a range of possible outcomes.Ad hoc rules of thumb that yield a range of possible outcomes.
Based on a financial snapshot at a point in time which mayBased on a financial snapshot at a point in time which may
change in the near future.change in the near future.
Discounted After-Tax CostDiscounted After-Tax Cost Assumes constant rates of return/tax rates, actual payouts andAssumes constant rates of return/tax rates, actual payouts and
losses will match model assumptions and won’t vary by insurer.losses will match model assumptions and won’t vary by insurer.
Policy Forms & Program AgreementsPolicy Forms & Program Agreements May be advantages and disadvantages for each carrier.May be advantages and disadvantages for each carrier.
Sometimes hard to know a priori which would have been mostSometimes hard to know a priori which would have been most
important to TCOR outcomes. Doesn’t consider carrier financialimportant to TCOR outcomes. Doesn’t consider carrier financial
strength.strength.
4. Putting the pieces together?Putting the pieces together?
• Present Comparisons and DiscussPresent Comparisons and Discuss
• Conclusion on best option not always clear:Conclusion on best option not always clear:
Different quote alternatives better for different criteria.Different quote alternatives better for different criteria.
Analytics can produce mutually contradictory indications.Analytics can produce mutually contradictory indications.
• Which quote is “best” overall?Which quote is “best” overall?
Ad Hoc client dialogue.Ad Hoc client dialogue.
Client has no clear, consistent basis for their decision.Client has no clear, consistent basis for their decision.
““Select Preferred Quote” (SPQ) model provides a metric toSelect Preferred Quote” (SPQ) model provides a metric to
support the decision based on preference weights the clientsupport the decision based on preference weights the client
assigns and performance weights supported by currentassigns and performance weights supported by current
analytics.analytics.
5. SPQ process:SPQ process:
Solve the PuzzleSolve the Puzzle
• Work with client to (Work with client to (can be done pre-quotecan be done pre-quote):):
⇒ Identify Main Criteria that will be used to evaluate quoteIdentify Main Criteria that will be used to evaluate quote
⇒ Identify Sub-criteria for each Main Criteria where appropriateIdentify Sub-criteria for each Main Criteria where appropriate
⇒ Obtain client preference rankings (1-9) for Main Criteria and Sub-criteria through aObtain client preference rankings (1-9) for Main Criteria and Sub-criteria through a
dialogue considering pairwise comparisonsdialogue considering pairwise comparisons
• Obtain QuotesObtain Quotes
• Run standard analytical models and develop usual comparisonsRun standard analytical models and develop usual comparisons
• Assign performance rankings (1-9) to quotes relative to criteria and sub-criteria usingAssign performance rankings (1-9) to quotes relative to criteria and sub-criteria using
standard analyses as data to consider in setting the rankings. (standard analyses as data to consider in setting the rankings. (can be done prior tocan be done prior to
meeting with client and discussed and modified based on client feedback or togethermeeting with client and discussed and modified based on client feedback or together
with the clientwith the client).).
⇒ Input preference and performance rankings to the modelInput preference and performance rankings to the model
⇒ Review output with client and apply sensitivity testing if desired by varying preferenceReview output with client and apply sensitivity testing if desired by varying preference
weights as instructed by client.weights as instructed by client.
⇒ Additional negotiations with markets to improve quotes if needed or select and bindAdditional negotiations with markets to improve quotes if needed or select and bind
optimal quote.optimal quote.
6. Suggested Criteria and Sub-criteriaSuggested Criteria and Sub-criteria
MainMain
CriteriaCriteria
Sub-Sub-
CriteriaCriteria
CostCost
VariabilityVariability
• RetentionRetention
LevelLevel
• Agg StopAgg Stop
ProtectioProtectio
nn
• VariableVariable
ExpenseExpense
• LimitsLimits
AdequacAdequac
yy
CashflowCashflow N/A or TBDN/A or TBD
CollateralCollateral • AmountAmount
• FormForm
Main CriteriaMain Criteria Sub-CriteriaSub-Criteria
InsurerInsurer • FinancialFinancial
StrengthStrength
• ClaimsClaims
PayingPaying
• ServiceService
• U/WU/W
flexibilityflexibility
• CommunicCommunic
ationation
• SystemsSystems
• ResponsivResponsiv
enesseness
ClaimsClaims • UnbundledUnbundled
• ServiceService
Can be customized to add or remoCan be customized to add or remo
Criteria/Sub-criteria.Criteria/Sub-criteria.
7. Preference Ranking ScalePreference Ranking Scale
1 Equal
2 Weak or Slight
3 Moderate
4 Moderate Plus
5 Strong
6 Strong Plus
7 Very Strong
8 Very, Very Strong
9 Highest Possible
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
0.5
0.3333
0.2500
0.2000
0.1667
0.1429
0.1250
0.1111
0.9091
0.8333
0.7692
0.7143
0.6667
0.6250
0.5882
0.5556
0.5263
Between Equal and Weak
Reciprocals
8. Main Criteria PreferenceMain Criteria Preference
Rankings and WeightsRankings and Weights
Cost Variability Cashflow Collateral Admin Coverage Insurer Claims Loss Control
Cost Variability 1.0000 7.0000 9.0000 9.0000 0.1429 5.0000 0.1667 8.0000
Cashflow 0.1429 1.0000 5.0000 9.0000 3.0000 5.0000 2.0000 5.0000
Collateral 0.1111 0.2000 1.0000 9.0000 0.2500 6.0000 9.0000 9.0000
Admin 0.1111 0.1111 0.1111 1.0000 9.0000 8.0000 8.0000 9.0000
Coverage 7.0000 0.3333 4.0000 0.1111 1.0000 7.0000 7.0000 7.0000
Insurer 0.2000 0.2000 0.1667 0.1250 0.1429 1.0000 7.0000 7.0000
Claims 6.0000 0.5000 0.1111 0.1250 0.1429 0.1429 1.0000 7.0000
Loss Control 0.1250 0.2000 0.1111 0.1111 0.1429 0.1429 0.1429 1.0000
0.2269
0.1679
0.1412
0.1510
0.1753
0.0441
0.0860
0.0076
Weights representsWeights represents
eigenvectoreigenvector
associated withassociated with
dominantdominant
eigenvalue of theeigenvalue of the
Matrix entries belowMatrix entries below
diagonaldiagonal
are reciprocal ofare reciprocal of
those above andthose above and
calculated by thecalculated by the
model.model.
nt assigns preference rankings in the upper triangular part of mant assigns preference rankings in the upper triangular part of ma
9. Sub-criteria Preference Rankings andSub-criteria Preference Rankings and
weights: Cost Volatilityweights: Cost Volatility
Retention Levels Agg Stop
Variable
Expense
Limits
Adequacy
Retention Levels 1 5 5 5
Agg Stop 0.2 1 0.166666667 0.2
Variable Expense 0.2 6 1 0.2
Limits Adequacy 0.2 5 5 1
0.5701
0.0493
0.1225
0.2581
atrix entries below diagonalatrix entries below diagonal
re reciprocal of those above.e reciprocal of those above.
agonal = 1.agonal = 1.
is would be repeated foris would be repeated for
ch set of sub-criteria in thech set of sub-criteria in the
odelodel
Weights representsWeights represents
eigenvector associated witheigenvector associated with
dominant eigenvalue of thedominant eigenvalue of the
matrix.matrix.
10. Rank quote performance relative toRank quote performance relative to
Criteria/Sub-CriteriaCriteria/Sub-Criteria
0.026122
0.026122
0.266908
0.266908
0.127166
0.127166
0.055092
0.055092
0.049425
es are assigned relative performance ranks.es are assigned relative performance ranks.
x above would be constructed for each criteriax above would be constructed for each criteria
ub-criteria.ub-criteria.
T3M T5M OR 3M OR 5M C 3M U C 3M B A 3M U A 3M B L 3M
T3M 1 1.0000 0.1429 0.1429 0.2000 0.2000 0.3333 0.3333 0.5000
T5M 1.0000 1 0.1429 0.1429 0.2000 0.2000 0.3333 0.3333 0.5000
OR 3M 7.0000 7.0000 1 1 3 3 5.0000 5.0000 5.0000
OR 5M 7.0000 7.0000 1.0000 1 3 3 5.0000 5.0000 5.0000
C 3M U 5.0000 5.0000 0.3333 0.3333 1 1.0000 3.0000 3.0000 3.0000
C 3M B 5.0000 5.0000 0.3333 0.3333 1.0000 1 3.0000 3.0000 3.0000
A 3M U 3.0000 3.0000 0.2000 0.2000 0.3333 0.3333 1 1.0000 1.0000
A 3M B 3.0000 3.0000 0.2000 0.2000 0.3333 0.3333 1.0000 1 1.0000
L 3M 2.0000 2.0000 0.2000 0.2000 0.3333 0.3333 1.0000 1.0000 1
Weights represents eigenvectorWeights represents eigenvector
associated with dominantassociated with dominant
eigenvalue of the matrix.eigenvalue of the matrix.
