2015 NA competitive analysis survey report v9 AB AC...Companies find their competitor rate analysis...
Transcript of 2015 NA competitive analysis survey report v9 AB AC...Companies find their competitor rate analysis...
CompetitiveAnalysisPracticesinPersonalLinesInsurance‐NorthAmerica
2015SurveyResultsPublishedby
© Earnix 2015 2
ExecutiveSummary
Asinsurancemarketsbecomemoresaturated,competitiveintelligencehasgrownintoakeyfunctionforeveryinsurer.Atthesametime,howinsurerstrackandanalyzetheircompetitorsis still an evolving practice – with best practices being formed and adapted to meet thechallengesof ever‐changingmarket dynamics and the opportunitiespresentedby emergingdatasourcesandinnovativetechnologies.ThissurveywasconductedbyEarnixwiththegoalofhelpinginsuranceexecutivesandpricingprofessionalsunderstandhowcompaniesacrosstheindustryanalyzecompetitiveinformationand how this information is being used. Survey responses were collected online from 60executivesandpricingprofessionalsrepresentinginsurancecarriersfromtheUnitedStatesandCanada.Thisreportincludesareviewofthesurveyfindings,accompaniedbyanEarnixexpertanalysisoftheresults,basedonourworkwithleadinginsurersinNorthAmerica.Keyfindingsfromthesurveyinclude:
Closetohalfofthecompaniessurveyed(42%)haveadedicatedcompetitiveanalysisteam;thelargerthecompanyis,themorelikelyitistohaveadedicatedteam.
Regardless of company size, the effectiveness of competitive analysis efforts isperceivedtobehigherwhencompanieshaveadedicatedcompetitiveanalysisteam.
Comparativeratingvendorsarenowtheprimarysourceforobtainingcompetitors’premiumdata,usedby87%ofthecompaniessurveyed.
Companiesfindtheircompetitorrateanalysishighlyuseful.Theprimaryusesofcompetitorrateanalysisaregaugingthecompany’scompetitivemarketpositionandguidingfactorselection.
Asignificantnumberofcompanies(43%)saycompetitiveanalysishasbecomemoreimportantasaresultoftheincreaseininsuranceshoppingsites.
Almosthalfoftherespondents(47%)plantoincreasetheinvestmentincompetitiveanalysisoverthenexttwelvemonths.
Ihopeyoufindtheseresultsinformativeandwouldwelcomeanyquestionsorcommentsonthefindings.Sincerely,
MerylGoldenGeneralManagerNorthAmerica,Earnix
© Earnix 2015 3
TableofContents
ExecutiveSummary ................................................................................................................... 2
CompetitiveAnalysisTeam ........................................................................................................ 5
CompetitiveAnalysisTeam ........................................................................................................ 6
WhichCompetitorsAreAnalyzed? ............................................................................................. 7
TypesandUsesofCompetitiveAnalysis ..................................................................................... 8
SourcesofInformationUsedforCompetitiveAnalysis ................................................................ 9
EffectivenessofCompetitiveAnalysisEfforts ........................................................................... 10
InvestmentandImprovementsinCompetitiveAnalysis ........................................................... 11
ObtainingCompetitorPremiums .............................................................................................. 13
AssigningCreditScores ............................................................................................................ 14
ConfidenceinEstimatingCompetitors’CreditScores ................................................................ 15
AssigningTelematicsDiscounts ............................................................................................... 16
UseofCompetitorRateAnalysis,FrequencyofUpdates ............................................................ 17
ImpactofInsuranceShoppingSites .......................................................................................... 18
ConfidenceintheAccuracyofCompetitorRates ....................................................................... 19
HowtoMakeCompetitorRateAnalysisMoreEffective? ........................................................... 20
RespondentDemographics:CompanyLinesandSize ................................................................ 21
RespondentDemographics:RoleintheCompany ..................................................................... 22
TableofFigures ....................................................................................................................... 23
© Earnix 2015 4
CompetitiveAnalysisPractices
ThereisnodoubtthatthecompetitivelandscapeintheNorthAmericanpersonallinesinsurancemarket ischanging.Themarket is themostcompetitive ithaseverbeen,andgrowingmarketshareseemstobeatoppriorityformanycarriers.Thistrendhasresultedinthewillingnessofmanycompaniestopricepoliciesaggressivelytoattractandretainmorebusiness.Analyzingthecompetitioniscriticalinunderstandingtheeverchangingmarket.Withtheproliferationofdigitalchannels, mobile internet and aggressive advertising we are seeing an acceleration of moreaggressiveandcomplexratechanges.
Adecadeago,mostcompaniesfollowedapredictablepatternfortheirratechanges.Traditionally,companieswouldupdatesomeoftheirfactorsannually(driverclass,deductibles,etc.);everyfewyears,theymightintroduceanewratingelementsuchasanewdiscount.Nowadays,companiesarecontinuouslyrollingoutnewprograms,withvastlyincreasedcomplexity.Overthepastfewyears,wehaveseen the roleof thecompetitiveanalyst change fromclericalwork tocomplexstrategic analysis. Today, almost half of insurance carriers have dedicated competitiveintelligenceteams.
Theprimaryresponsibilityforthesededicatedcompetitiveintelunitsistocollect,analyze,andcommunicatecompetitoractivity.Justlikeinthepast,themainsourceofcompetitiveinformation(79%ofcompanies)iscompetitorratefilings.However,thecomplexityofmanycompanies’ratingstructureshasincreasedinrecentyears,makingdecipheringtheratesextremelychallenging;itisnotuncommonforfilingstobethousandsofpageslong.
Thislevelofcomplexityissignificantlyslowingdowntheanalyticsprocess.Forexample,yearsagowhenananalystwasasked“whatarethemulti‐policydiscountsforourtopfivecompetitors?”findingtheanswerwasamatterofscrollingthroughafewratemanualsandfindingthepublisheddiscountinthemulti‐policydiscounttable.Now,whatusedtobeasinglenumberisinmanycasesa multivariate table that requires a significant effort to analyze. Work that previously tookminutesisnowtakinghours.
Tokeepupwiththeincreaseinratingsophistication,overhalfofcompaniesforeseeinvestingmoreincompetitiveintelligenceoverthenextyears.Thisisaprofoundstatementconsideringthehighpressurethatmanycompaniesare feelingwithregardtotheirexpenseratio.Whilemostcompanies are trying to reduce expenses, many still see the need to stay current with theconstantlychangingmarket.Surveyrespondentshaveidentifiedaneedforbetteranalysistoolsandbetterdatacollectionasthetoptwoimprovementsformoreeffectivecompetitiveanalysis.Presumablythisiswherecompanieswillbeinvesting.
Overthenext fewyears,wecanexpectthecomplexityofratingplanstocontinuetheupwardtrend,thusfurtherincreasingtheneedtostaycurrentonmarketprices.Competitiveintelligencewillcontinuetobeanecessaryinvestmentfortheforeseeablefuture.
DrewLawyerSr.ProfessionalServicesConsultant,Earnix
© Earnix 2015 5
CompetitiveAnalysisTeamClosetohalfofthecompaniessurveyed(42%)haveadedicatedcompetitiveanalysisteam.
Figure1:Haveadedicatedcompetitiveanalysisteam
Whetheracompanyhasadedicatedteamforcompetitiveanalysiscorrelatestothecompanysize.67%ofthecompanieswithover$5BinGrossWrittenPremium(GWP)haveadedicatedteam,comparedtojust13%ofthecompanieswithlessthan$250MinGWP.
Figure2:Percentofcompaniesthathaveadedicatedcompetitiveanalysisteam
Yes42%
No58%
13%
37% 39%
67%
88%
63% 61%
33%
< $250M $250M‐$1B $1B‐$5B > $5B
Gross Written Premium for personal lines insurance (2014)
Have a dedicated team
No
Yes
© Earnix 2015 6
CompetitiveAnalysisTeamWhiletheaveragesizeofcompetitiveanalysisteamsisrightaroundfourpeople,43%ofthecompaniesthathaveadedicatedteamhavefiveormoremembersworkingintheseteams.
Figure3:NumberofpeopleincompetitiveanalysisteamProductmanagement has the primary responsibility for competitive analysis in 42%of thecompaniesthatdon’thaveadedicatedteam.Inaquarter(25%)ofthecompanies,severaldepartmentsdotheanalysisrelatedtotheirareaof expertise. The actuarial group is responsible for competitive analysis in 13% of thecompanies.
Figure4:Primaryresponsibilityforcompetitiveanalysis
16%
42%
32%
11%
1‐2 3‐4 5‐10 10+
Average: 4.1
4%
4%
8%
13%
25%
42%
No person or group is responsible for competitiveanalysis
Finance
Sales Management
Actuarial Group
Several departments do the analysis related to theirarea of expertise
Product Management
© Earnix 2015 7
WhichCompetitorsAreAnalyzed?Whenselectingwhichcompetitorstoanalyze,mostcompanieschoosetheirlargestcompetitors.Asmany as 42% of the respondents target the largestwriters of each line of business in theprimarydistributionchannelofthecompany,andanother21%targetthelargestwritersineachstate/provinceregardlessofdistributionchannel.
Figure5:Topcriteriausedtodeterminewhichcompetitorstoanalyze
Whiletheaveragenumberofcompetitorstrackedineachstate/provinceisrightaroundfive,28%ofthecompaniesaretrackingsevenormorecompetitors.
Figure6:Activelytrackingcompetitorsperstate/province
9%
7%
9%
12%
21%
42%
Other
The companies with the best operating results
The largest writers of each line of business in the country
The companies deemed to be most innovative
The largest writers in each state/province
The largest writers of each line of business in the primarydistribution channel of the company
23%
49%
12%
16%
3 or less 4‐6 7‐9 10+
Average: 5.1
© Earnix 2015 8
TypesandUsesofCompetitiveAnalysisAlmosteverycompanysurveyed(93%)performsratestructureandratecompetitiveanalysis.Othercommontypesof competitiveanalysis includeproduct features (79%),coveragesandcontracts(70%),financialmetrics(58%),andunderwritingguidelines(56%).
Figure7:Typesofcompetitiveanalysisperformed(Respondentscouldselectmorethanoneoption)
Themajorityof thecompaniessurveyed (72%)usecompetitiveanalysis information togaugeoverallcompetitiveness,guidefactorselectionand/ordetermineoverallratelevel.Othercommonusesofcompetitiveinformationincludeavoidingadverseselection(47%),addingcredibilitytobusinesssegmentsinareaswithlowdatavolumeandsupportforcompanyfilings(37%each).
Figure8:Top3usesofcompetitiveanalysisinformation(Respondentscouldselectmorethanoneoption)
21%
44%
56%
58%
70%
79%
93%
Marketing spend and tactics
Overall business strategy
Underwriting guidelines
Financial metrics
Coverages and contracts
Product features
Rate structures and rates
7%
14%
19%
26%
37%
37%
47%
72%
Anticipating future competitor actions and preempt them
Adopting strategies and tactics used by leading carriers
Help build our research agenda
Implementing similar tactics over time when proven
Support our filings
Credibility complement due to low data volume in certaingeographies or sublines
Making sure we are not adversely selected against
Gauge overall competitiveness, guide our factor selectionsand/or determine overall rate level
© Earnix 2015 9
SourcesofInformationUsedforCompetitiveAnalysisThe majority of survey respondents (79%) use company filings as their leading source ofinformationforconductingcompetitiveanalysis.
Vendor reports that aggregate competitor data (70%), company annual / quarterly reports(65%),companywebsite(63%),andinformationcollectedfromagentsandsalesreps(58%)areadditionalsourcescommonlyusedbycompanies.
Figure9:Sourcesofinformationusedforcompetitiveanalysis(Respondentscouldselectmorethanoneoption)
16%
37%
40%
47%
49%
58%
63%
65%
70%
79%
Marketing spend reports
Analyst reports
Investor conference calls
Industry conferences and meetings
Trade publications and newsletters
Information collected from agents and sales reps
Company website
Company annual/quarterly reports
Vendor reports that aggregate competitor data
Company filings
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EffectivenessofCompetitiveAnalysisEffortsMostcompaniesviewtheircompetitiveanalysiseffortsaseffective,withanaveragescoreof3.4onascaleof1‐5.Almosthalfoftherespondents(44%)rateditasa4orabove.
Figure10:Effectivenessofcompetitiveanalysisefforts
Regardlessofcompanysize, theeffectivenessofcompetitiveanalysisefforts isperceivedtobehigherwhencompanieshaveadedicatedcompetitiveanalysisteam.
Figure11:Effectivenessofcompetitiveanalysiseffortsbycompanysize
0%
9%
47%
35%
9%
1 ‐ Not EffectiveAt All
2 3 4 5 ‐ HighlyEffective
Average: 3.4
4.00 4.00
3.092.85
<$1B >$1BGross Written Premium for personal lines insurance (2014)
Have a dedicated team
Yes
No
© Earnix 2015 11
InvestmentandImprovementsinCompetitiveAnalysisClosetohalfoftherespondents(47%)plantoinvestmoreincompetitiveanalysisinthenext12months.51%planonkeepingthecurrentlevelofinvestment,whileonly2%intendtoinvestless.
Figure12:Investmentincompetitiveanalysisinthenext12months
Accordingtosurveyrespondents,betteranalysistools(58%)andbetterdatacollection(51%)wouldbethetopchoicesforimprovingtheeffectivenessofcompetitiveanalysis.
Otherimprovementsmentionedinclude:
Moreactionablerecommendations Morestructuredprocesses Moretimelyanalysis
Figure13:Topimprovementsforamoreeffectivecompetitiveanalysis(Respondentscouldselectmorethanoneoption)
We anticipate investing more
47%
No change51%
We anticipate investing less
2%
21%
30%
33%
37%
40%
51%
58%
Broader dissemination of analysis
A dedicated Competitive Analysis team
More timely analysis
More structured processes
More actionable recommendations
Better data collection
Better analysis tools
© Earnix 2015 12
CompetitorRateAnalysisPracticesWith the increased complexity of competitors’ rating plans, companies are adapting theirtoolsetforcomparingpremiums.Adecadeago,acompanycouldmaintainitscompetitors’ratesinabasicExcelworkbook.Eachtimeacompanychangedrates,theworkbookwouldbeupdatedwiththenewfactors.Thesedaysaregone(oratleastquicklydisappearing).Insurersarenowrelyingmoreheavilyoncompetitive rating tools.87%of the companiessurveyedciteusingvendorstoacquire/calculatepremiumsfortheircompetition.
Unfortunately,thesetoolsarenotwithouttheirowncomplexity.Inmanycases,companiesdonothavetherelevantpolicyinformationtopopulatethesetoolsandbroadassumptionsmustbemade(e.g.credit,underwriting,telematics).Somecompaniesinvestsignificantlytoperfecttheseassumptionsandproducethemostaccuratecompetitiveanalysispossible,whileotherssavetimeandenergybyjustmakingmoregeneralizedassumptions.
Onethingabouttheseassumptionsisthattheycanevolveovertime.Creditestimationisoneexample:21%ofcompaniesareusingavarietyofmethodstoimputetheircompetitors’creditscores.Overtime,companieshavebeenabletorefinetheircreditscoreestimation,resultinginmultiplemethodsusedthroughouttheindustry.However,fornewerprogramsliketelematics,most companies (71%) are just assuming no discount applies. As adoption becomes morewidespread and the focus shifts to finding a competitive niche within telematics, theseassumptionswillsurelybecomemorerefined.
Evenwithall theseassumptionsbuilt intotheprocess,companiesarestillmostlyconfidentintheresultingpremiums.Halfofthecompaniessurveyedarehighlyconfidentintheaccuracyoftheircalculatedcompetitors’rates.
Theprimaryuseofcompetitiverateanalysiscitedinthissurveyisgaugingcompetitivemarketposition(92%).Whiletherearemultiplewaystogaugeyourcompany’scompetitiveposition,somemethodsarelesspronethanotherstobiasesintroducedbytheinherentimperfectionsoftheassumptions.Forexample,maintainingthesamerateassumptionsovertimeandmeasuringthe changes in competitive position can provide a good indication of how companies arechangingratesbysegment,eveniftheaggregateleveleffectmightbeoff.Companiesthatareregularlychangingtheirunderlyingassumptionsfinditmoredifficulttounderstandhowtheircompetitivepositionischangingovertime.
Althoughcompetitiverateanalysisisanimperfectscience,companiesarestillfindingvalueinthe results and use the information to guild many aspects of the pricing process such ascredibilitycomplementsanddefiningterritoryboundaries.Withpricecompetitionconsistentlyincreasing,companieswillcontinuetofindinnovativewaystoleveragecompetitivepricingdataforyearstocome.
DrewLawyerSr.ProfessionalServicesConsultant,Earnix
“Ifyouknowtheothersandknowyourself,youwillnotbeimperiledinahundredbattles.”‐‐SūnZǐ,6thcenturyBCEChinesegeneralwhowroteTheArtofWar
© Earnix 2015 13
ObtainingCompetitorPremiumsClose to two‐thirds of the respondent (62%) use their own quotes to assemble themarketbasketofriskstheycomparetotheircompetitors.Simulatingdataforahypotheticalmarketbasketandusingtheirownin‐forcepolicieswerementionedby46%oftherespondents,while41%oftherespondentpurchasequotesfromanoutsidevendorinordertoassemblethemarketbasketofrisks.
Figure14:Waystoassemblemarketbasketofrisksforwhichratesarecompared(Respondentscouldselectmorethanoneoption)
Thevastmajorityofthecompanies(87%)obtaincompetitorpremiumsfromcomparativeratingvendors. 35% mentioned that their agents provide competitor premiums, 34% calculatecompetitorspremiumsbycollectionfilings,and30%purchasepremiumsfromanoutsidevendor.
Figure15:Waystoobtaincompetitorspremiums(Respondentscouldselectmorethanoneoption)
32%
41%
46%
46%
62%
We obtain quotes from our agents/brokers
We purchase quotes from an outside vendor
We use our in‐force policies
We simulate risk data for a hypothetical marketbasket
We use our own quotes
30%
34%
35%
87%
We purchase premiums from an outsidevendor
We calculate competitor premiums bycollecting filings
Our agents provide competitor premiums
We obtain premiums from comparative ratingvendors
© Earnix 2015 14
AssigningCreditScoresCompanies use a variety ofways to handle credit scoringwhen programming competitors’rates.Moreover,21%ofthecompaniesusedifferentmethodsfordifferentcompetitors.Popularmethodsusedbythesecompaniesinclude:
Reverseengineeringofcompetitors’creditscoringsystems Usinganexternalvendortoassigncreditscores Assumingsimilarcreditscoregrouptowhattheircompanyassigned
Only12%ofthecompaniesignorecreditscorevarianceandusejustasinglecredittier.
Figure16:Waystohandlecreditscoringwhenprogramingcompetitors'ratesinternally
6%
12%
18%
18%
21%
21%
We make assumptions about the credit score groupbased on risk characteristics
We only consider a single credit tier
We calculate competitors' rates assuming a similar creditscore group to what our company assigned to the risk
We rely on an external vendor for assigning the competitors’ credit scores
We have (reverse) engineered our competitors creditscoring system
We use different methods for different competitors
© Earnix 2015 15
ConfidenceinEstimatingCompetitors’CreditScoresConfidenceinestimatingcompetitors’creditscoresisnotveryhigh,withanaveragescoreof2.8onascaleof1‐5.Overathirdofthecompanies(36%)ratestheirconfidence2orless.
Figure17:Confidenceinestimatingcompetitors’creditscoresThe confidence in estimating competitors’ credit scores is higher when companies have adedicatedcompetitiveanalysisteam,regardlessofcompanysize.
Figure18:Confidenceinestimatingcompetitors’creditscoresbycompanysize
15%
21%
36%
21%
6%
1 ‐ Not TooConfident
2 3 4 5 ‐ HighlyConfident
3.80
3.38
2.60
2.00
<$1B >$1B
Gross Written Premium for personal lines insurance (2014)
Have a dedicated team
Yes
No
Average: 2.8
© Earnix 2015 16
AssigningTelematicsDiscountsMostrespondents(71%)assumenotelematicsdiscountwhenprogramingcompetitors’ratesinternally.9%oftherespondentsmakedistributionalassumptionsaboutwhoreceivesadiscountandhowlargeitis,andanother9%onlyapplytheinitialofferdiscount.
Figure19:Waystohandletelematicsscoreswhenprogramingcompetitors'ratesinternally
9%
3%
9%
9%
71%
Other
We use internal data to score competitors’ telematics models
We only apply the initial offer discount
We make distributional assumptions about whoreceives a discount and how large
We assume no telematics discount
© Earnix 2015 17
UseofCompetitorRateAnalysis,FrequencyofUpdatesAlmostallsurveyrespondents(92%)usetheresultsoftheircompetitorrateanalysistogaugetheircompetitivemarketposition.Additionalcommonusesinclude:
Guidefactorselections Getideasforhowtorefinetheirownratestructure Defineterritorialboundaries
Figure20:Useofcompetitors’rateanalysis(Respondentscouldselectmorethanoneoption)
Closetohalf(49%)ofthecompaniessurveyedupdatecompetitorrateseverytimetheyworkonaratechange.Another37%oftherespondentsupdatecompetitors’ratesonaregularbasis,while11%updatethematarandomfrequency.
Figure21:Frequencyofupdatingcompetitors’rates
44%
50%
56%
58%
69%
92%
Consider competitor premiums when setting ouroverall rate level
Estimate the impact on new business growth andother metrics for any rate change
Define our own territorial boundaries
Get ideas for how to refine our own rate structure
Guide our factor selections
Gauge our competitive market and market positions
Every time we are working on a rate
change49%
Whenever an important
competitor changes rates3%
On a regular basis 37%
On a random basis11%
© Earnix 2015 18
ImpactofInsuranceShoppingSitesTheemergenceofinsuranceshoppingsitesismakingcompetitorrateanalysismoreimportantintheeyesofmanyoftherespondents(43%),while54%oftherespondentsexpressednochange.Only3%saiditbecamelessimportant.
Figure22:Competitorrateanalysisinlightofautoinsuranceshoppingsites
Smallercompaniesaremoreaffectedbytheriseofshoppingsites.Asmanyas50%ofthesmallercompaniessaytheircompetitorrateanalysishasbecomemoreimportantcomparedtojust39%ofthelargercompanies.
Figure23:Competitorrateanalysisinlightofshoppingsitesbycompanysize
More important
43%
Less important
3%
Has not changed in importance
54%
50%39%
50%61%
<$1B >$1B
Gross Written Premium for personal lines insurance (2014)
No change orless important
More important
© Earnix 2015 19
ConfidenceintheAccuracyofCompetitors’RatesMostcompaniesarequiteconfident in theaccuracyof their calculatedcompetitors’ rates.Theaveragescoreis3.3onascaleof1‐5,and50%oftherespondentsratetheirconfidenceasa4orhigher.
Figure24:Confidenceintheaccuracyofthecalculated/derivedcompetitors’rates
Accordingtosurveyresults,itseemsthathavingadedicatedcompetitiveanalysisteamhasonlyaminorimpactontheconfidenceintheaccuracyofcalculatedcompetitors’rates.
Figure25:Confidenceintheaccuracyofthecalculated/derivedcompetitors’ratesbycompanysize
6%
14%
31%
44%
6%
1 ‐ Not TooConfident
2 3 4 5 ‐ HighlyConfident
3.403.75
3.27 3.22
<$1B >$1B
Gross Written Premium for personal lines insurance (2014)
Have a dedicated team
Yes
No
Average: 3.3
© Earnix 2015 20
HowtoMakeCompetitorRateAnalysisMoreEffective?Close to two‐thirds (65%) of the respondents acknowledge the usefulness of competitor rateanalysisbyratingthema4orhigheronascaleof1‐5.Theaveragescoreacrossallrespondentsis3.8.
Figure26:Usefulnessofcompetitorrateanalysis
Thetopimprovementsthatwouldmakeforamoreeffectivecompetitiverateanalysisaccordingtotherespondentsareimprovedaccuracyofcompetitors’rates(70%)andbetterunderstandingofcompetitors’creditscoringalgorithms(68%).
Figure27:Topthreeimprovementsforamoreeffectivecompetitorrateanalysis(Respondentscouldselectmorethanoneoption)
0%
5%
30%
43%
22%
1 ‐ Not Useful AtAll
2 3 4 5 ‐ Very Useful
11%
19%
19%
32%
49%
68%
70%
More actionable recommendations
A more representative sample of risks
Being informed of competitor rate changes ona more timely basis
Better understanding of competitorunderwriting rules
Better analysis tools
Better understanding of competitor creditscoring algorithms
Improved accuracy of competitor rates
Average: 3.8
© Earnix 2015 21
RespondentDemographics:CompanyLinesandSizeThevastmajorityoftherespondents(79%)offerbothautoandhomeinsurance,while13%offeronlyautoinsuranceand8%onlyhomeinsurance.
Figure28:Productoffered
Survey respondents represent a mix of small and large companies, with over half of therespondents (55%) representing companies with more than $1B in Gross Written Premium(GWP).
Figure29:PersonallineinsuranceGrossWrittenPremium(2014)
Auto13%
Home8%
Both79%
13%12%
20%
45%
10%
< $250M $250‐$500M $500M‐$1B $1B‐$5B > $5B
© Earnix 2015 22
RespondentDemographics:RoleintheCompanyThethreerolescomprisingthemajorityofsurveyrespondentsincludeR&Danalystsormanagers(34%),companyexecutives(26%),andpricinganalystsormanagers(23%).
Figure30:Respondentrole
34%
26%
23%
9%
3%6%
R&D Analyst or Manager
Executive Management
Pricing Analyst or Manager
Product/State Manager
Finance
Other
© Earnix 2015 23
TableofFigures
Figure1:Haveadedicatedcompetitiveanalysisteam .................................................................. 5 Figure2:Percentofcompaniesthathaveadedicatedcompetitiveanalysisteam ........................... 5 Figure3:Numberofpeopleincompetitiveanalysisteam .............................................................. 6 Figure4:Primaryresponsibilityforcompetitiveanalysis .............................................................. 6 Figure5:Topcriteriausedtodeterminewhichcompetitortoanalyze ........................................... 7 Figure6:Activelytrackingcompetitorsperstale/province ........................................................... 7 Figure7:Typesofcompetitiveanalysisperformed ........................................................................ 8 Figure8:Top3usesofcompetitiveanalysisinformation ............................................................... 8 Figure9:Sourcesofinformationusedforcompetitiveanalysis ...................................................... 9 Figure10:Effectivenessofcompetitiveanalysisefforts ............................................................... 10 Figure11:Effectivenessofcompetitiveanalysiseffortsbycompanysize ...................................... 10 Figure12:Investmentincompetitiveanalysisinthenext12months ........................................... 11 Figure13:Topimprovementsforamoreeffectivecompetitiveanalysis ....................................... 11 Figure14:Waystoassemblemarketbasketofrisksforwhichratesarecompared ....................... 13 Figure15:Waystoobtaincompetitorspremiums ....................................................................... 13 Figure16:Waystohandlecreditscoringwhenprogramingcompetitors'ratesinternally ............ 14 Figure17:Confidenceinestimatingcompetitors’creditscores .................................................... 15 Figure18:Confidenceinestimatingcompetitors’creditscoresbycompanysize ........................... 15 Figure19:Waystohandletelematicsscoreswhenprogramingcompetitors'ratesinternally ....... 16 Figure20:Useofcompetitors’rateanalysis ............................................................................... 17 Figure21:Frequencyofupdatingcompetitors’rates .................................................................. 17 Figure22:Competitorrateanalysisinlightofautoinsuranceshoppingsites ............................... 18 Figure23:Competitorrateanalysisinlightofshoppingsitesbycompanysize ............................. 18 Figure24:Confidenceintheaccuracyofthecalculated/derivedcompetitorrates ........................ 19 Figure25:Confidenceintheaccuracyofthecalculated/derivedcompetitorratesbycompanysize ................................................................................................................................................ 19 Figure26:Usefulnessofcompetitorrateanalysis ....................................................................... 20 Figure27:Topthreeimprovementsforamoreeffectivecompetitorrateanalysis ........................ 20 Figure28:ProductOffered ........................................................................................................ 21 Figure29:PersonallineinsuranceGrossWrittenPremium(2014) .............................................. 21 Figure30:ResponddtnsRole ..................................................................................................... 22
© Earnix 2015 24
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