life insurance in the transformation · pdf fileconsumer engagement with life insurance by...

01 Executivesummary02 Introduction04 Keytechnology

developmentsimpactinglifeinsurers

13 Impactsonlifeinsuranceindustry

26 Strategicimplications31 Newchallenges39 Conclusion

Life insurance in the digital age: fundamental transformation ahead

No6/2015

Swiss ResigmaNo6/2015 1

Executivesummary

Technologicaladvanceshavethepotentialtoradicallychangethewaylifeinsurersinteractwithconsumersandalsohelpthembetterassessandpricerisks.Therapidspreadofinternet-enabledwearabledevicesandubiquitousconnectivityareenablingnewwaysofcommunicationandinformationsharing.Theamountofdigitaldatageneratedautomatically,inexpensivelyandnon-intrusivelyisgrowingexponentially.Thenumberoftoolstoanalysethedataandextractusefulinsightsonconsumersisalsogrowingrapidly.Developmentsinartificialintelligenceandcognitivesystemsalsocreateopportunitiesforinnovation.Andadvancesinmedicaltechnologyhavethepotentialtoimprovehealthoutcomesandextendlives,thuschangingriskpools.

Inunderwriting,newdatasourcesandinnovativeplatformstostoreandminedataorsimplyautomateexistingprocessescanreducethelengthandinvasivenessofriskassessment,improveriskselectionandrefinepolicypricing.Automationofunderwriting–agrowingtrend–willbepushedtonewfrontiersbydevelopmentsincognitivecomputing,whileBigDataandnewanalyticaltoolswillprogressthestill-nascentstageuseofpredictiveunderwritinginlifeinsurance.Datasharingplatformsforendconsumerswillreducethecostofcollectinghealthinformationandprovideamorecompleteviewofcustomersformoreaccurateriskassessmentandpricing.

Indistribution,theimportanceofnewchannelsfacilitatedbytheinternet,smartphonesandsocialmediaisincreasing.Newtechnologiescanenhanceconsumerengagementwithlifeinsurancebymakingtheapplicationprocesseasierandbyusingrewardsprogrammesandtechniquessuchasgamification.Newsourcesofdataandpredictivemodellingtoolsofferopportunitiesformoregranularclientsegmentationandbetteridentificationofclients’needs.Inadditiontobettertargetingtheexistingcustomerbase,newtechnologiesalsoofferthepotentialtoreachnewcustomersegments.

Digitalisationandthespreadoftheinternetandmobiletechnologyhavetransformedanumberofindustries.Lifeinsurers,however,havebeenslowadoptersoftheinnovationsthattechnologyadvancesoffer,withchangeshappeningonlygradually.Thesectorlagsbehindotherindustriesinofferingconsumersapositiveonlineexperienceandmeetingcustomerexpectationsinthedigitalage.

Technologyandthedigitaldatarevolutionwillfundamentallychangethebusinessofinsurance.Togrowtheirbusiness,insurerswillneedtoreviewtheirinvestmentsintechnology,rethinktalentstrategyandadapttheirbusinessmodels.Somelifeinsurersarepartneringwithstart-upstobuildtheirowndataanalyticscapabilities.Technologicaldevelopmentscouldspurnewoperatingmodelsforexistinginsurers,allowingthemtobecomepurelydigitalandtoprovidenewservicesbeyondtraditionalinsurance.

Newtechnologypresentsopportunities,butalsogivesrisetonewchallengesthatlifeinsurersneedtoaddress.Oneisregulation,withlackofclarityandconsistencyarounddataprotectionandprivacy.Therearealsoregulatorychallengeswithrespecttotheuseofdigitaltechnologyincross-borderselling.Further,lifeinsurerswillnotwanttoalienateconsumersthroughtheiruseoftechnologyanddataanalytics.Finally,non-traditionalplayersareenteringthemarket,presentinganopportunityforpartnership.However,theycouldalsoeventuallycompetewithtraditionalinsurers.

Newdataandtechnologiescanradicallytransformthewaylifeinsuranceisunderwrittenandsold.

Forunderwriting,thereispotentialtoreducethelengthandinvasivenessofriskassessment,improveriskselectionandrefinepolicypricing.

Newtechnologiescanalsofacilitateimprovementsindistributionthroughstrongerconsumerengagement.

Lifeinsurancehaslaggedbehindconsumerexpectationsinthedigitalage.

Insurerswillneedtoreviewtheirinvestmentsintechnology,rethinktalentstrategyandadapttheirbusinessmodels.

Technologypresentsnewchallengesforlifeinsurersalso.

2 Swiss ResigmaNo6/2015

Introduction

Digitalisationandthespreadoftheinternetandmobiletechnologyhaveimpactedanumberofindustriesinrecentyears,transformingthembeyondrecognition.Sectorswithlowbarrierstoentry,genericproductsandlowmarginalcostssuchasthemusic,publishing,retailandtravelindustries,havebeenmostaffected.Digitaltechnologyisnowrevolutionisingindustrieswithmorecomplexproductionprocessesandhigherbarrierstoentryalso.Inthefinancialservices,forexample,innovationisdrivingdisruptioninpaymentsystems,consumerlendingandwealthmanagement,amongothers,leadingtoimprovedfunctionalityandlowercosts.

Theinsuranceindustryhasbeenslowtoadoptsomeoftheinnovationsthatdigitaltechnologyoffers.Therehasbeengradualacceptanceofcertainaspectssuchasdigitaldistributionoverthepastdecadebutchange,especiallyinthelifesector,hasbeenatthemarginsonly.1Customer-centricityisnotyetthenorminlifeinsurance:a“one-size-fits-all”approachandafocusonagentsratherthanconsumersisstillwidespread,limitingconsumerchoiceandproductcustomisation.Moreover,alengthyandconvolutedbuyingprocessoftenleavesconsumersconfusedandlackingtrustininsuranceproviders.2

Yetconsumerpreferencesandbuyingbehavioursarechangingrapidly,notleastbecausemanyindustrieshavealreadyadoptedmorecustomer-centricandtechnology-inspiredbusinessmodels.Theyoungergeneration(GenerationY,bornbetweentheearly1980sandlate1990s,andsubsequentgenerations)inparticularhavegrowntoexpecteasyandquickaccesstoinformationincommercialinteractions,transparencyaboutcostandvalue,andhigh-qualityservice.Notsurprisingly,consumersurveysshowinsurancelaggingbehindmostotherindustrieswhenitcomestocustomersatisfactionfromonlineexperiences(seeFigure1).

Source:Delivering Digital Satisfaction ©2013,TheBostonConsultingGroup(BCG)

1 sigma2/2014:Digitaldistributionininsurance:aquietrevolution,SwissRe.2 sigma6/2013:Lifeinsurance:focusingontheconsumer,SwissRe.

Digitaltechnologyhasalreadytransformedmanyindustries…

…buttherevolutionhasbeenslowtotakeoffininsurance.

Theindustryalsolagswhenitcomestoofferingconsumersapositiveonlineexperience.

Figure 1 Consumersatisfactionwithonlineexperience,byindustry

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Thedigitaluniverseandtechnologicaladvanceshavethepotentialtoradicallychangethewayinwhichlifeinsurersinteractwithconsumers,andalsohelpthembetterassessandpricerisks.Theirrapidspreadisadisruptiveforce,enablingnewinterfacesandformatsforcommunication,sharingofinformationandinteractingwiththephysicalworld(seeFigure2).Abundanceofdataonconsumersandnewwaystoevaluateitcreateopportunitiestoinnovateinunderwritinganddistribution.Intheemergingmarkets,mobiletechnologyallowsforconnectingwithbillionsofpeople:inmany,communicationsystemshavejumpedfromtherebeingvirtuallynoconnectivitydirecttothemobileandevensmartphoneage.Advancesinartificialintelligence(AI)andnewanalyticaltoolsaremakingitpossibletoaugmentorautomatecertainaspectsoftheworkofinsuranceprofessionals.Also,advancesinmedicaltechnologyhavegreatpotentialtofacilitateearlydiagnosticsandpreventionofdisease,improvethehealthofpeoplewithchronicdiseases,andextendlives.

E=estimates.

Source:ITUWorldTelecommunication/ICTIndicatorsdatabase

Somelifeinsurershaveuseddigitalcommunicationstoofferinsurancethathadbeenunaffordableorunavailablepreviously.Theuseofreal-timedataisenablingcompaniestostreamlinetheunderwritingprocessandreducerelianceoninvasivetestingsuchasbloodsamples.Otherinsurersaretakingactiontocapitaliseontheopportunitiesthatnewtechnologiescanprovideinthefuturebyformingpartnershipswithtechstart-upsasameanstobuildtheirownBigDatacapabilities.Thereisanawfullotmorethatcan,andwill,happen.Thissigmaeditionprovidesanoverviewofkeytechnologicaldevelopmentsrelevanttothelifeinsuranceindustry.Itdiscussesthepotentialimpactofthesedevelopmentsonunderwritinganddistribution,andassessesthelonger-termopportunities,risksandchallengesthatnewtechnologyanddataanalyticspresenttolifeinsurers.

However,thelifeinsurancesectorissettoundergofundamentalchange,drivenbytechnology.

Figure 2 Globalgrowthintechnologyandconnectivity,2001–2015E

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Thissigmaassessestheimplicationsofnewtechnologiesforlifeinsurers.

4 Swiss Re sigma No 6 /2015

Key technology developments impacting life insurers

A wide range of technological changes will affect the future of the insurance industry. These developments include data and analytics, artificial intelligence and cognitive computing, new medical technologies, wearable devices and digital health, and the Internet of Things.

Data and analytics

The amount of data generated in the world today is increasing exponentially as the range of devices capable of sending and receiving data over the internet – computers, tablets and mobile phones and their applications (“apps”), cameras, embedded sensors and others – continues to expand. According to IDCʼs Digital Universe Study, from 2013 to 2020 the digital universe will grow by a factor of 10 – from 4.4 trillion gigabytes to 44 trillion – roughly doubling every two years.3

A large share of the digital data is generated automatically, inexpensively and non-intrusively by devices capable of sending and receiving information, and from transaction records, social media platforms and web logs. Much is unstructured, collected in real time, updated frequently, variable and not always useful. For example, the IDC study said that in 2013, only 22% of the digital data bits generated would have provided value if tagged and analysed.4 Two-thirds of the data were generated by use of devices by consumers and workers, but enterprises had liability or responsibility for 85% of that.5 Of the data generated in 2013, only 5% was actually analysed, according to the IDC. It is a widely-held belief that the competitive advantage in business will go to those firms able to use Big Data and predictive analytics to identify consumer preference trends early, to gain insights into consumer preferences and make operations more efficient.

However, the ability to gain useful insights from the ever-increasing amounts of data is challenging. Big Data broadly refers to data sets so large or complex that it is critical to have the right tools and techniques to manage and analyse them effectively.6 As data variety and diversity push the limits of technological innovation, new data management techniques and frameworks are being developed. This discipline is called “data science”, loosely defined as the extraction of knowledge from large volumes of structured and unstructured data. Many firms recognise the strategic importance of Big Data analytics and are building large teams of data scientists.7

3 In the report, the estimates consider data generated by more than 40 types of devices including radio-frequency identification devices (RFID), sensors, supercomputers, supercolliders, PCs, servers, cars and planes. See The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things, White Paper, IDC (sponsored by EMC Corporation), April 2014.

4 By 2020, it is thought that the useful percentage could grow to more than 35%, mostly because of the growth of data from systems embedded in computers and small devices.

5 For example, Facebook’s users had uploaded more than 250 billion photos on its website by 2013, and an additional 350 million new photos were being uploaded each day. See "A Focus on Efficiency - A White Paper from Facebook, Ericsson and Qualcomm", internet.org, 16 September 2013, http://www.meducationalliance.org/sites/default/files/internet.org_-_a_focus_on_efficiency.pdf

6 There is no one definition of the term Big Data. For an overview of definitions, see J. S. Ward and A. Barker, Undefined by Data: A Survey of Big Data Definitions, School of Computer Science, University of St. Andrews, 20 September 2013.

7 T. H. Davenport and D.J. Patil, “Data Scientist: The Sexiest Job of the 21st Century”, Harvard Business Review, October 2012.

New technologies to transform the industry.

The amount of information generated through various devices is set to roughly double each year.

Digital data can be a competitive advantage in business but currently, much of the information generated is not useful.

That’s why many firms are hiring data scientists with the ability to extract useful insights from large volumes of digital information.


What is data science? Datascienceisaninterdisciplinaryfieldincorporatingcomputerscience,modelling,statistics,businessanalyticsandmathematicstoanalysemassiveamountsofdatatoextractinsightsandknowledge.8Inadditiontotechnicalskills,datascientistsmusthavesufficientexpertisetoformulatethequestionstobeaskedofthedataandtointerprettheresults.

Theprocessiscircular,startingwithobtainingasufficientamountofdatafrommultiplesources,thenatureofdatabeingsearchedforitselfdeterminedbyexistingbusinessinsightsandobjectives.Thedatathenneedstobecleanedandputintousableformat.Thisisespeciallychallengingforunstructureddata(eg,datafromTwitter)duetoitscomplexityandnon-representativeness.

Themodellingstage,whichcaninvolvestatisticalanalysis,dataminingandmachinelearning9,comesnext.Thechoiceofanalysistechniquedependsonthenatureoftheendgoal,forinstancewhethertheaimistoexplaincausalrelationshipsortopredict.Exploratorydataanalysisoftenusesstatisticaltoolstofitthemodelandinvestigatecausalityrelationships.Predictivemodels,ontheotherhand,usemachinelearningalgorithmsanddataminingtoolsthatautomaticallysearchthroughthedataandlearnhowtorecognisepatternsanddiscoverusefulrelationships.Theseareusedtotrainthemodelandimproveitsabilitytomakepredictions.Inthefinalstage,theresultsfromthedataanalysisareinterpreted,visualisedandreportedsoastobeusefulforbusinessdecision-makingpurposes.Theseinsightsarealsousedtoinformthefocusofdatasearchesforsubsequentbusinessinitiatives.

Source:SwissReEconomicResearch&Consulting(adaptedfromvarioussources).

Todate,thenumberoffirmsacrossallsectorsactuallydeployingsolutionsderivedfromBigDatatechnologiesarerelativelyfew.AccordingtoasurveybyGartner,theshareofcompaniesthatinvestedorplannedtoinvestinBigDatainthenext24monthsgrewto73%in2014,from64%in2013.However,only13%ofthosehaveactuallydeployedapplicationsandsolutions,withmuchoftheworkrevolvingaroundstrategydevelopment,thecreationofpilotsandexperimentalprojects.10

8 SeeWhat is Data Science?,NYU,http://datascience.nyu.edu/what-is-data-science/andH.MasonandC.Wiggins,"ATaxonomyofDataScience",dataists.com,25September2010,http://www.dataists.com/2010/09/a-taxonomy-of-data-science/

9 Machinelearningisasubfieldofcomputersciencewhichdealswithalgorithmsthatcanlearnfromandmakepredictionsondata.Inabusinesscontext,machinelearningmethodsareoftenreferredtoaspredictiveanalyticsorpredictivemodelling.SeeWikipedia,https://en.wikipedia.org/wiki/Machine_learning.

10Gartner Survey Reveals that 73 Percent of Organizations Have Invested or Plan to Invest in Big Data in the Next Two Years,Gartner,17September2014,http://www.gartner.com/newsroom/id/2848718

Datascienceisaninterdisciplinaryfieldfocusedonextractingknowledgefromdata.

Theprocessinvolvesmultiplesteps,includingdatacollectionandcleaning,…

…modelling,reportingandvisualizationofresultstosupportbusinessdecision-making.

Figure 3 Thedatascienceprocess

OnlyarelativelyfewcompaniesfromallindustrieshavesuccessfullydeployedBigDataapplications.

Reportingandvisualization

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transformation

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http://datascience.nyu.edu/what-is-data-science/



Theinsurancesectorhasbeenslowerthanmanyothersectors,butmanyinsurerssaytheywillmakemoreuseofdataanalytics.AccordingtoaStrategyMeetsAction(SMA)surveyofinsurersinNorthAmerica,theshareofcompaniesthatinvestedinBigDatainitiativesmorethandoubledto25%in2014from10%in2013.11ThemostpronouncedincreasewasatfirmswritingmorethanUSD1billionofpremiumsannually.Inthissegment,39%reportedinvestinginBigDataprojectsin2014,upfrom14%theyearbefore.AsFigure5shows,insurersusedataanalyticsmainlyforsalesandmarketingpurposesbutexpecttoincreaseitsuseacrossallfunctionsinthenext3–5years.

Source:Big Data in Insurance,SMAResearch,June2014.

Note:Note:ifaninsurerchose“today”butnot“in3–5years”,the“3–5years”optionwasconsideredtobechosenaswell.

Source:Global Digital Insurance Benchmarking Report 2015,Bain&Company,2015.

11 In2014,SMAconductedastudyonbigdataininsurance.75NorthAmericaninsurersparticipatedinthesurvey,representingalltiersandmajorlinesofbusiness.Formoreinformationsee:M.Breading,Big Data Takes Off in Insurance,SMA,10September2014,https://strategymeetsaction.com/news-and-events/sma-blog/big-data-takes-off-in-insurance/

Surveyevidencesuggeststhatmanyinsurersexpecttomakemoreuseofdataanalyticsinthecomingyears.

Figure 4ShareofallNorthAmericaninsurersinvestinginBigData

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Survey question:TowhichfunctionsdoyouapplyBigDataanalytics?

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Artificialintelligenceandcognitivecomputing

Softwareintelligenceorcognitivecomputingisthesimulationofhumanthoughtprocessesinacomputerisedmodel.Cognitivesystemsapplyartificialintelligence(AI)12andmachinelearningalgorithmsencompassingvariousdatamining,patternrecognitionandnaturallanguage13processingtechniquestomimictheworkingsofthehumanbrain.Cognitivetechnologyisnotanewconcept.AIemergedasafieldinthelate1950sandbecameahottopicinthe1960swhencomputerscientistssetouttobuildintelligentsystems.Therewasapushtodeveloping“expertmachines”inthe1980sbutlimitationstocomputingpowerbroughtprojectstoahalt.Sincethelate1990s,theAIandcognitivecomputingfieldshaveseenrapidbreakthroughsenabledbyseveralkeydevelopments,includinganexponentialincreaseincomputationalpower,14adeclineinrelatedcosts,andtheavailabilityofvastquantitiesofdigitalinformation.Thesehavefacilitatedthedevelopmentofadvancedmachinelearningtechniquessuchaspatternrecognitionsystems.

Cognitivesystemscontinuallylearnfromlargesetsofdataandapplythatknowledgetofuturesituations.Theexpectationisthatthesystemswillbeabletoanswercomplicatedquestionsinfasterandmoreefficientwaysthanhumansinallsortsofindustries,includinghealthcare,pharmaceuticals,finance,insuranceandlaw(seeBox:“It’selementary,mydearWatson”).

Importantly,cognitivesystemscanaddvaluebyovercominglimitationsinhumancognitiveabilities.Forexample,itcanbedifficultforhumanstoprocesslargeamountsofdatarapidly,andtounderstandtheinteractionsofelementsinlarge,complexsystems.Cognitivesystemscanvastlyextendtheabilitytogatherandprocessinformation,andalsotodiscovernewandcontrarianideas,hiddenpatterns,identifypreviouslyundetectedrelationshipsandtomakemoreaccuratepredictions.Theycanalsohelpsubject-matterexpertskeepupwithlatestknowledgeandresearchbyquicklyanalysingandsynthesisingmillionsofdocumentsforrelevantinformation.Andlastly,cognitivesystemscanbemoreobjectivethanhumansinformulatingandtestinganumberofhypotheses.Humans,incontrast,arepronetobiasbasedonexperience,professionalbackgroundandintuition.

Cognitivesystemscarrythepromiseofvastlyenhancingmanyareasofhumanactivity,freeingupresourcestoberedirectedtocapacitieswherecomputersremaininferiortohumans.Theywillinevitablyreplacesometypesofknowledgework.Forexamplealreadytoday,financialadvisersfacecompetitionfromrobo-advisersbuiltonthealgorithmsthatoriginallyservedthetraditionalfinancialadvisorcommunity.Cognitivecommunicationsystemsabletoconductaquestion-and-answerdialoguewithconsumershavethepotentialtocreatenewareasofinnovation.Thisincludestheworktraditionallycompletedbyinsuranceagents,advisorsorclaimshandlers.Technologycanmaketheseindividualsmoreproductiveandtakeawaysomeoftheirmoremundanework.

12Artificialintelligenceiscomputersandcomputersoftwarecapableofintelligentbehaviour.ThemaingoalsofAIinclude"reasoning,knowledge,planning,learning,naturallanguageprocessing(communication),perceptionandtheabilitytomoveandmanipulateobjects.”SeeWikipedia,https://en.wikipedia.org/wiki/Artificial_intelligence

13 “Naturallanguageorordinarylanguageisanylanguagethatdevelopsnaturallyinhumansthroughuseandrepetition.”SeeWikipedia,https://en.wikipedia.org/wiki/Natural_language

14 Inthelast50years,thepowerorcomputing(chip)performancehasdoubledapproximatelyeverytwoyears.Thistrendisdubbed“Moore’slaw”,afterGordonE.Moore,co-founderoftheIntelCorporationandFairchildSemiconductor,whoina1965paperdescribedadoublingeveryyearinthenumberofcomponentsperintegratedcircuit.SeeWikipedia,https://en.wikipedia.org/wiki/Moore’s_law

Cognitivecomputingisthesimulationofhumanthoughtprocessesinacomputermodel.

Cognitivesystemscanbefasterandmoreefficientthanhumansin…

…gatheringandprocessinginformation.

Cognitivesystemscancreatenewareasofinnovationinlifeinsurance.



“It’s elementary, my dear Watson”15

OneexampleofcognitivecomputingfromIBM’sWatson16computingsystem.Watsonisanartificialintelligencecomputersystemcapableofansweringquestionsposedinnaturallanguage.ThesystemwasshowcasedintheTVquizshowJeopardy!whereitcompetedin2011andwonagainstallhumancompetitors.

WatsonisacombinationofAI,machinelearningandnaturallanguagetechnologies.Itdecomposesquestionstounderstandthecontextofwhatisbeingasked,analysesallavailableinformationinresearchandarticles,andcomesupwithplausibleanswers.Ithastheabilitytoquicklyexecutehundredsofprovenlanguageanalysisalgorithmssimultaneously.Itisprobabilisticandgeneratespotentialanswerswithalevelofconfidence.Themorealgorithmsthatfindthesameanswerindependently,themorelikelyWatsonistobecorrect.Watsoncansiftthroughthedataequivalentofabout1millionbooks,analysetheinformationandprovideresponsestocomplicatedquestionsinlessthanthreeseconds.

CommercialapplicationsofWatsontechnologyaregrowing.Inhealthcare,aversionofWatsonisbeingusedtoaccelerateandincreasetheaccuracyofthetreatmentprocessbasedonananalysisofthousandsofpagesofmedicalpapers,treatmentguidelines,electronicmedicalrecorddata,notesfromphysiciansandnurses,researchmaterial,clinicalstudies,journalarticlesandpatientinformation.IBMhaspartneredwithpharmaceuticalcompaniestohelpunderstanddruginteractionsbymakingconnectionsacrossmillionsofarticles,journalsandstudies.Firmsfromarangeofotherindustries,includingfinancialservices,travel,telecomandretail,areworkingwithIBMtocreateappsandservicesembeddedwithWatson’scapabilities.

Medicaltechnologies

Medicalinnovationistransformingthewayhealthcaresystemsoperate.Disruptivetechnologiesinhealthcarearebasedoninterdisciplinaryadvancementsacrossthenaturalsciences,medicineandtechnology.Theyspanmanydomains,includingtheuseofelectronicprocessesanddevices(eHealth),genomics,regenerativemedicine,roboticsurgery,diagnosticandtherapeuticmethodsbasedonmicrosystemsornanotechnology,newmedicaldevices,drugdeliverytools,andothers.Thesedevelopmentsareforcingashiftinhealthcaretowardprevention,earlydiagnosisandmoreeffectivetreatmentoutcomes,whichcouldhavesignificantinfluenceonhealthrisks.Theyarealsohelpingconsumersgainbetterinsightintotheirownhealthstatus,andmotivatingthemtoactionhealthierlifestyles.Thiscouldalsobeanotherimportantconsiderationinthedesignoflifeandhealthinsurancepolicies.Amongthedisruptivemedicaltechnologies,eHealth,genetictesting,andwearablesbearmostrelevanceforlifeinsurancebecauseoftheirdirectimplicationsforriskassessmentandunderwriting.

15ThemostfamousofquotesattributedtheSirArthurConanDoyle’sfictionaldetectivecharacterSherlockHolmes,eventhoughDoyleneveractuallywrotethosewordsforSherlockHolmes.See“SherlockHolmeQuotes”,sherlockholmesquotes.com,http://sherlockholmesquotes.com/Elementary-My-Dear-Watson.html.

16TheIBMWatsoncomputingsystem,however,wasnamedafterIBM'sfirstCEO,ThomasJ.Watson.

AnexampleofcognitivecomputingisIBM’sWatson.

Watsoniscapableofunderstandingquestionsandprovidinganswersbasedonanalysisofallavailableinformation.

Commercialapplicationsaregrowingrapidly.

Medicalinnovationspansmanydomains.


eHealthThetermeHealthisrelativelyrecentandreferstoarangeofservicesorsystemsattheedgeofmedicine,healthcareandinformationtechnology(IT).Keyhealthcarepracticessupportedbyelectronicprocessesinclude:

Systemsforelectronichealth(ormedical)records(EHR),17patientdatamanagement,diagnostictestsandtreatments,andtransmissionofprescriptionsfromdoctorstopharmacists.

Telemedicine,whichisphysicalandpsychologicaldiagnosis,andtreatment,atadistance,includingtele-monitoringofpatientsfunctions.

mHealth,whichincludestheuseofmobiledevicestocollecthealthdata,providehealthcareinformationtopractitioners,researchersandpatients,andtomonitorpatients’vitalsinrealtime.

Healthknowledgemanagementsystems,providinginformationtohealthcarepractitionersforuseinclinicaldecision-making,andalsobest-practiceguidelinesandepidemiologicaltrackingofmedicalresearch.

Note:MultifunctionalhealthITcapacity–useselectronicmedicalrecordandatleasttwoelectronicfunctions:fororderentrymanagement,generatingpatientinformation,generatingpanelinformation,androutineclinicaldecisionsupport.Source:The Commonwealth Fund 2012 International Health Policy Survey of Primary Care Physicians,TheCommonwealthFund,November2012.

17 EHRsystemsenableelectroniccollectionofhealthinformationwiththeprimarypurposeofprovidinghealthcareandrelatedservices.Theinformationcanbetransmitted,updatedorretrievedsecurelyandinreal-timebothatthepointofcareandinremotelocations.

eHealthcoversarangeofsystemsattheedgeofmedicine,healthcareandIT.

Figure 6 InternationaladoptionofelectronicmedicalrecordsandhealthITcapacity

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ThereisgrowingevidencethattheuseoftechnologyinhealthITleadstolowercostsandimprovedhealthoutcomes.This,andpressurestocontainmedicalcostincreases,createsincentivesforeveryoneinthehealthcaresectortousehealthIT.AdoptionofEHRsystemsvariesfromcountrytocountryformanyreasons(seeFigure6),includingtypeofhealthcaresystem,technicalandfinancialbarriers,andconcernsaboutprivacyandsecurity.18IntheUS,theHealthInformationTechnologyforEconomicandClinicalHealth(HITECH)Actfrom2009madeasubstantialcommitmentoffederalresources(USD27billion)tosupportadoptionofEHR.19InEurope,wherehealthcarepracticesarelargelylocalised,areportcommissionedbytheEuropeanCommissionfoundthatapan-EUEHRsystemwouldnotbetechnicallyfeasibleandcost-effective.IthasinsteadurgedmoreemphasisondecentralisedeffortstocreatesmallerscaleeHealthsystems.20

Genetic testingAdvancementsingenomicsholdgreatpotentialtotransformmedicine,bymakingitpossibletoscanaperson’sgeneticprofiletopredictriskareasandcustomisemedicaltreatments.Genetictestingidentifieschangesinchromosomes,genesandproteinstodetectpossiblepresenceofgeneticdiseases,ormutantformsofgenesassociatedwithincreasedriskofdevelopinggeneticdisorders.Mostgenetictestsareusedtoconfirmorruleoutasuspectedgeneticdisease,andtodetectthepresenceofgenesthatpredisposeapersontoaparticularillnessorcondition.

Theavailabilityandvarietyofgenetictestshasexpandedgreatlyovertime,andthecoststhereofhaveplummeted.Nottoolongago,onlysomeresearchlaboratorieswerecapableofconductinggenetictesting.Today,intheUSalonethereareover500laboratoriesthatdoso.21Fifteenyearsago,thecostofsequencingahuman-sizedgenomewasclosetoUSD100million;nowit’saroundUSD400022andisexpectedtofallbelowUSD1000soon.23

Wearables,InternetofThingsanddigitalhealth

Wearabledevicesorsimply“wearables”aremini-computersandsensorsincorporatedinitems(eg,wristbands,watches,glassesorclothes)thatcanbewornonthebody.Similartohandhelddevices,wearablescandisplay,processandstoreinformationandusuallyhavesomecommunicationcapabilities.Forexample,California-basedAugmedixhasdevelopedsmartglassesbasedontheGoogleGlassplatformthatdocumentdoctors’visitstopatients,includingdataentryassociatedwithapatient’sEHR.24Inaddition,patienttestresultscanbedisplayeddirectlywithoutthedoctorhavingtolookatacomputerscreen.Thisgivesthephysicianmoretimetofocusonthepatient.Theglassesalsohavesensoryfeatures,suchastrackingofvitalsthatgobeyondthoseofhandhelddevices.

18MollyPorter,“AdoptionofElectronicHealthRecordsintheUnitedStates”,Kaiser Permanente,February2013.

19Thedeadlineforimplementationis2015andthosewhodonotmeetitwillhavetopaypenaltiestothegovernmentintheformofreducedMedicarepayments.PhysicianswhohavenotadoptedEHRsystemsby2015willreceiveMedicarereimbursementsreducedby1%.Thedeductionrateincreasesto2%in2016,3%in2017,and4%in2018.

20K.A.Stroetmann,J.Artmann,V.N.Stroetmannetal.,European countries on their journey towards national eHealth infrastructures – evidence of progress and recommendations for cooperative actions,EuropeanCommission,DGInformationSocietyandMedia,ICTforHealthUnit,2011.

21Genetic Testing: How it is Used for Healthcare,NIHFactSheet.October2010.22DNA Sequencing Costs – Data from the NHGRI Genome Sequencing Program (GSP),NationalHuman

GenomeResearchInstitute,http://www.genome.gov/sequencingcosts/23RobertKlitzman,“Doctor,HaveYouHadYourDNATested?”,New York Times,5February2015.24ThecommercialviabilityofGoogleGlasshasbeenunderquestion,butAugmedix’ssmartglassesareone

ofseveralin-the-workplaceapplicationsthatareseenasgivingrenewedlifetothetechnology.“GoogleGlassFindsaSecondActAtWork“,MIT Technology Review, 24 July 2015,http://www.technologyreview.com/news/539606/google-glass-finds-a-second-act-at-work/

Governmentsarepushingforadoptionofelectronichealthrecords.

Advancementsingenomicsholdgreatpotentialtotransformmedicine.

Availabilityofgenetictestinghasexpandedgreatlyandcostshaveplummeted.

Wearablesaremini-computersandsensorsincorporatedinitemsthatcanbewornonthebody.


Wearableshavebeenusedinhospitalsforalongtime,forexampletodetecthealthdisorderslikesleepapnoea.Recently,wearableshaveexpandedintotheconsumersegmentalso,forinstancefitnesstrackersandsmartwatches(seeFigure7).25Typicalfeaturesincludetrackingofsteps,caloriesspentandheartrate.

By2025,thenumberofconnecteddevicesinuseisexpectedtototalaround25billion,upfrom5billiontoday.26Theincreasewillcomewiththesignificantdropinhardwareprices,whichisputtingsensors,processingpower,networkbandwidthandcloudstoragewithinreachofmoreusersandmakingawiderrangeofIoTapplicationspractical.Progresstowardubiquitouswirelesscoverageatalowcostandadvancesindataanalyticshavefurtherfuelledthegrowthofand,importantly,willsupporttheproductiveuseofdatageneratedbytheIoT.

Note:Totalnumberofdevices:347,asof9September2015.Source:WearableTechnologyDatabase,VandricoInc.

Thealreadymentionedconsumerapplications,gadgetsthatcreate“smarthomes”withsensorsthattrackoccupants’usagepatternsandadaptenergyconsumptionlevelsaccordingly,andtheself-drivingcarhavesofarattractedthemostattention.However,accordingtoMcKinsey,business-to-businessapplicationsareexpectedtoaccountfornearly70%oftheestimatedvaluethatwillflowfromtheIoTtechnologyinthenext10years.27Thehealthcaresectorwillbeamainbeneficiary.WearablesandIoTtechnologyhavethepotentialtoradicallychangecareservicesandtreatmentoutcomes.Forexample,thetechnologycanmakethediagnosis,preventionandtreatmentofchronicdiseasesmoreefficientwithimprovedremotemonitoringtechniques.Untilnow,mostdoctorshavehadalimitedabilitytocollectandmonitorinformationonhealthstatusonceapatientleavesahospitalormedicalfacility.Inthefuture,theywillbeabletomonitorpatients’heartratesremotelywitheasy-to-usepatchesattachedtotheskin,thusimprovingearlydetectionofheartattackrisk.

25Foradetailedlistingofwearabledevicesareasofmarketfocus,seeVandricoInc’swearabletechnologydatabaseathttp://vandrico.com/wearables

26Ibid.27 Ibid.

TheInternetofThingsisexpandingtheworldofpossibilitiesforremotedevices.

Thenumberofconnecteddevicesinuseintheworldisforecasttogrowfivefoldinthenext10years.

Figure 7Wearabledevicesbyareaofmarketfocus,%oftotal

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Likewise,formanyyearsdiabetespatientshavehadtohavetheglucoselevelsintheirbloodtestedseveraltimesaday.Newcontinuousglucosemonitoringsystems(patchesbearingatinyneedleundertheskin)allowforreal-timemeasurement24/7.Meanwhile,GoogleandAlconareworkingonacontactlensthatmeasuresglucoselevelsintears.28AnotherexampleisSoteraWireless’ViSiMobilesystem,whichhasbeengrantedFDAapproval.29Thesystemallowsclinicianstomonitorpatients’bloodpressureandothercorevitalsignsincludingpulserate,skintemperature,electrocardiogram,bloodoxygenationandrespirationrates.

Anotherareainwhichwearablesofferpotentialforimprovementisadherencetomedicalprescriptions.AccordingtotheCentersforDiseaseControlandPreventionintheUS,inabout50%ofcasesmedicationisnotcontinuedasprescribed,limitingtheeffectivenessoftherapies.30ProteusDigitalHealth,aCalifornia-basedcompany,hasdevelopedingestiblesensortechnology,which–whenusedwithamedication–marksactualintaketime.Thesensorcommunicateswithanadhesivepatchwornonthetorso,whichinturntransmitsthedatatoamobileapp.Inaddition,thewearablesensorcanrecordbasicphysiologicaldatasuchasheartrateandactivity/rest,generatingsomerecordofdrugresponse.31Suchtechnologiescanhelpfine-tuneandpersonalisedrugtreatment,leadingtobetterhealthoutcomesandreducedhealthrisks.Thenewinformationcouldalsobeusedtodeterminethescopeofcoverandpricingofinsurancepolicies.

28Novartis to license Google “smart lens” technology,Alcon,15July2014,http://www.alcon.com/news-center/news-item.aspx?id=307

29“FDAApprovesViSiMobileSystemforCuffless,Non-InvasiveContinuousBPMonitoring”,medgadget.com,10October2013,http://www.medgadget.com/2013/10/fda-approves-visi-mobile-system-for-cuffless-non-invasive-continuous-bp-monitoring.html

30Medication Adherence,CentersforDiseaseControlandPrevention,27March2013,http://www.cdc.gov/primarycare/materials/medication/docs/medication-adherence-01ccd.pdf

31Withtheincreaseduseofwearablesformedicalpurposes,therehasbeensomedebateaboutwhethersuchdevicesshouldbeunderregulatoryscrutiny.IntheUS,theFoodandDrugAdministration(FDA)issuedadraftguidanceinJanuary2015,suggestingthatlowriskdevicesintendedforonlygeneralwellnessuseshouldbeexemptfromregulatoryoversight.Thevastmajorityofwearabledevices,suchasstepcountersandcalorieintakemonitors,willthereforenotberegulated.Devices,marketedfortreatingdiseases,however,willfallunderFDAscrutiny.Seehttp://www.fda.gov/downloads/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm429674.pdf

…forexampleintheareaofremotepatientmonitoring…

…andbyimprovingadherencetomedicalprescriptions.


Impactsonthelifeinsuranceindustry

Technologywillhaveanenormousimpactontheinsuranceindustryoverthenextdecade,acrossthevaluechainfromproductdevelopmentandunderwritingthroughtodistribution,servicesandclaims.Inthenearterm,thelargestimpactislikelytobeonunderwritinganddistribution(broadlydefined).

Impactonunderwriting

Advancesintechnologyhavethepotentialtoradicallytransformunderwritinginlifeinsurance.Lengthy,complexandinvasiveunderwritingprocesseshavelongbeenviewedasanimpedimenttoreachingandengagingwithmoreoftheun-andunderinsured.Traditionalunderwritingtechniquestodifferentiateandselectrisksareeffective,buttheprocessistimeconsumingandinvolveshighcosts.Newdatasources,platformstostoreandanalysedata,andfast,innovativetechnologiestominethedataorsimplyautomateexistingprocesseshavethepotentialtoreducethelengthandinvasivenessofriskassessment,improveriskselectionandrefinepolicypricing.

Automated underwritingAutomatedunderwritinghasbeenagrowingtrendinlifeinsurance.ASelectXandHankGeorgeInc.surveyfoundthataboutathirdoflifeinsurersgloballyusedautomatedunderwritingin2011,andanotherthirdwereconsideringdoingso(seeFigure8).32ThefindingsareconsistentwithamorerecentglobalsurveybyBainandCompany,33accordingtowhichaboutathirdofthefirmssurveyedsaidtheycanauto-underwritelifeprotectionandsavingsproducts,andslightlymorethanhalfexpecttobeabletodosointhreetofiveyears(seeFigure9).

Source:Underwriting engines: the new strategic imperative in life and disability business, SelectXandHankGeorgeInc.,2011.

32Underwriting engines: the new strategic imperative in life and disability business,SelectXandHankGeorgeInc.,2011.

33Global Digital Insurance Benchmarking Report,Bain&Company,2015.

Changebeckonsacrossthelifeinsurancevaluechain.

Underwritingisgoingtobecomeeasierandmoreeffective.

Automationofunderwritinghasbeenagrowingtrendinlifeinsurance.

Figure 8Currentuseofunderwritingengines

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Impacts on the life insurance industry

Thetechnologyinautomatedsystemsperformsallorsomeofthescreeningfunctionstraditionallycompletedbyunderwriters,thusreducingthehumaninvolvement,timeand/ordatanecessarytounderwriteaninsurancepolicy.Differentlevelsofautomatedsystemsarecurrentlyavailable.Atabasiclevel,automationisusedtoscreenanapplicant’sinformationandflagriskfactorsthatanunderwritermustreviewmorecarefullybeforemakingadecision(forexample,resultsinabloodtestthatareoutsideacceptableboundaries,suchashighcholesterollevels).Thenextlevelofautomationaresystemsdesignedtocompletesimplifiedunderwritingforsmallerfaceamounts(oftenintherangeUSD100000toUSD250000),withoutmedicaltesting.Thesesystemshavebecomemorewidespreadinrecentyears.Theycanacceptorrejectanapplicationforinsurancecover.Insomecases,thesystemcanplaceanapplicantintoastandard,smokerorpreferredcategory,orreferhim/herforfurtherassessment.

Athirdcategoryofautomatedsystemsallowsforfullunderwritingbyessentiallytranslatingacompany’sunderwritingmanualintoprogrammedrules.Applicantscompleteaquestionnaireandundergothecompany’sstandardcriteriaassessment(eg,ageandamountofcoverrequired).Theapplicationisprocessedautomatically,thesystemalsopullinginthird-partyinformationandlaboratoryresults.Thesysteminterpretstheinformationanddetermineswhethertoissue,declineorforwardanapplicationtoanunderwriterforfurtherevaluationifnecessary,forexampleifaphysician’sstatementisrequired..

Developmentsincognitivecomputingwilladvanceautomatedsolutionsbybringingmoreconsistencytounderwritingdecisionsandbymakingtheprocessfasterandmorecost-effective.Integrationofthelearningcapabilitiesofcognitivesystems,andalsotheirvoicerecognitionandtextreadingalgorithms,willmakeitpossibletoextractmeaningfulinformationfromallsourcesofdata,includingunstructuredmedicalreports.Cognitivesystemscanbedevelopedtoreadanapplicant’sinformation,putitincontext,extractallrelevantfacts,comparewiththerulesandguidelinesinunderwritingmanuals,makeadecisionontheapplication,andsetapremiumforcoveriftheapplicationisaccepted.However,giventhatcognitivecomputingisbasedonprobabilitiesanduseofunstructureddata,insurersaremorelikelytouseitasanadvisorytoolratherthantomakefinaldecisiononwhethertoacceptorrejectanapplicationforcover.Insurerswilllikelyuseacombinationofcognitiveandrule-basedlogictostreamlinetheunderwritingprocessforsomewhileyet.DigitalisationinhealthcareandwideavailabilityofEHRwillmaketheuseofcognitivesystemsmoreeffectivetothisend.

Source:Global Digital Insurance Benchmarking Report 2015,Bain&Company,2015.

Automatedsystemscanflagriskfactorsandcompletesimplifiedunderwritingforsmallamounts.

Moreadvancedautomatedsystemsenablefullunderwriting.

Cognitivecomputingwillpushautomatedunderwritingtonewfrontiers.

Figure 9 Percentofinsurerswhocanauto-underwritelifeandhealthproducts.

Survey question:Whatshareofyourbusinesscanyouauto-underwrite?

Medical/healthLife savings and investmentsLife protection

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Swiss Re sigma No 6 /2015 15

Opportunities from new data sourcesThe traditional model of underwriting in life insurance involving evidence from consumers on their own and their family’s medical history, alongside third-party information, has been slow to evolve. The rapidly expanding universe of data in digital form – from EHR, connected devices, social media and other sources – provide alternative data sources which insurers could use to better assess and price risk, and in different ways. Use of non-traditional data will likely become more prevalent and may even eliminate the need for medical exams for many customers.

Some commentators believe EHR hold the greatest potential to transform underwriting in life insurance. EHR contain various types of data including lifestyle characteristics, medical history, family history, clinical biomedical indicators and prospective medical treatments. Getting the medical records of an applicant to underwrite a policy is currently a cumbersome and time-consuming process, with most of the information provided in print format. Because of the vast amounts of unstructured data, the systems are more focused on providing a synopsis for presentation to the underwriter rather than decision making. Ability to instantaneously access medical history with the individual’s consent in digital form eliminates the need for underwriters to search and wait for critical information, greatly streamlining and speeding up the underwriting process, and significantly reducing costs.

Data from health monitoring devices such as Apple’s HealthKit and Jawbone’s UP on physical activity levels, diet, sleep patterns and heart rate etc may also become useful. It is currently challenging to interpret these data for underwriting purposes because there is not enough research and experience to link the indicators to health outcomes with a comfortable degree of confidence. Companies are launching products that make use of these data (eg, the Vitality programme - see Box: Vitality rewards programme on page 24) though at the moment they have a low level of credibility on the underwriting side and are more of a customer engagement/retention tool. But in time this should improve. Growing ability to measure and monitor risks on an ongoing basis could also open opportunities for life insurers to personalise pricing in real time, adapt products over time, and expand insurability or augment pricing for conditions where life and health risks can be mitigated by healthier lifestyles and behaviours. For example, a healthy diet and increased levels of exercise are known to improve outcomes for people suffering from chronic conditions such as high blood pressure and diabetes. People who alter their behaviours in a positive way may qualify for lower premiums rates.

Another prospective source of information is the genetic profile of an individual. Genomic knowledge is evolving rapidly and genetic data, if available to insurers, could facilitate more accurate prediction of risks by illuminating disease susceptibility, disease-specific genes and pre-disposition to certain conditions. Genetic testing is already aiding the diagnosis, prevention and treatment of certain diseases. As its benefits become more widespread, health risks for many individuals may be lowered, making them insurable at a better rate.

One of the challenges for insurers is lack of consistent regulation on the use of genetic data for underwriting in life and health. In Europe, many countries have banned the use of genetic data by insurers. For example, in the UK, there is a moratorium on the use of genetic information until 2019. Meanwhile in Austria, Belgium, Denmark, France, Norway and Portugal, the use of predictive genetic test results for insurance purposes is not allowed. In the US, the Genetic Information Nondiscrimination Act (GINA) bars use of genetic information in health insurance underwriting decisions, but not for life, long-term care or disability insurance. Nonetheless, some states in the US bar the use of genetic test results, others prohibit decisions based on genetic information, and some require informed consent. A more unified approach would benefit all concerned.

New, alternative data sources can be used to assess risk and underwrite life insurance.

EHR may begin to transform underwriting fairly soon.

Data from health monitoring devices could be part of the risk assessment and pricing equation.

Likewise genetic data …

… although first there needs to be more consistent regulation on the use of genetic profile information in underwriting decisions.



Platforms for sharing of data by end consumers Anotherareaoftechnologicaladvanceexpectedtoenhanceunderwritingefficiencyareinterfacesforautomateddeliveryofinformationanddatatoinsurersbyendconsumers.Withtheproliferationofdatagatheredonandviadifferentdevices,severalfirmsaredevelopingsoftwareplatformsthatallowconsumerstoaccessandsharetheirdata.Theideaistogiveconsumerscontroloftheirdataandtheabilitytosharethemwithotherpartiessuchashealthcareprovidersandinsurancecompanies,whileprotectingtheirownprivacy.Forinsurers,theplatformswillreducethecostofcollectinghealthinformationandprovideamorecompleteviewoftheircustomersforuseinriskassessmentandpricing.

Examples of consumer controlled data-sharing platformsDigi.memeisastart-updevelopingsoftwaretoprovideaninterfaceforconsumerstocompileandmanagetheirpersonaldata.34Atpresentdigi.mefocusesonretrievinginformationaboutaconsumerfromhis/herpersonaldataonsocialmediasitessuchasFacebook,Twitter,InstagramandLinkedIn.Itanalysestheinformationtoprovidenewinsightstotheconsumer.Theintentionistoexpandthecapabilitytoretrievingandanalyzinginformationaboutanindividuals'healthandfinancialstatus,amongothers,fromdatastoredinotheronlinesites.Thirdpartieswillalsobeabletopurchaseinformationaboutaconsumerfromdigi.me,withtheconsumer'sconsent.

Human API35isastart-updevelopingasoftwareplatformtoretrieve,cleanandstructurehealth-relateddatafromvarioussources,anddeliveritautomaticallyinrealtimetothirdpartiessuchashealthcareprovidersorinsurancecompanies,withtheexplicitpermissionoftheindividualconcerned.Accordingtoitsfounder,HumanAPIwantstointegrateandautomatedeliveryofhealth-relateddatastoredindigitalformatinmanydisparatedatasets(eg,wearables,traditionalclinicalandlabdata,hospitalsanddoctors’offices,andgeneticlabs).36Thestart-upispartneringwithcompaniesprovidinghealthandactivitymonitoringdevicesincludingFitbit,iHealthandJawboneandhealthcareproviderstomaketheintegrationpossible.HumanAPIwillchargeafeeeachtimeadatauserretrievesinformationusingitsplatform.

Predictive analytics Predictivemodellingistheuseofadvancedstatisticaltechniquesanddataanalysistomakeinferencesoridentifymeaningfulrelationshipsinordertopredictfutureoutcomes.Withadequatedata,predictivemodellingcanbeanalternativemeanstodifferentiateandselectrisks.Forexample,itcanhelpidentifylower-riskindividuals,leadingtoastreamlinedunderwritingprocessthatismoreconvenientandcustomerfriendlyforhealthyapplicants.Useofpredictiveanalyticsinunderwritingcanleadtolowercostsandimprovetheoverallmortalityexperience.Itcanalsobeusefulinclientsegmentation,marketing,claimsmanagementandinforcebusinessretention.

34R.Moore-Colyer,“V3StartupSpotlight:Socialnetworkdatalibrarydigi.me”,V3.co.uk,21July2015,http://www.v3.co.uk/v3-uk/interview/2418321/v3-startup-spotlight-social-network-data-library-digime

35APIstandsforApplicationProgrammingInterface.36“HumanAPICEOOnUnifyingHealthData”,informationweek.com,5November2014,

http://www.informationweek.com/healthcare/electronic-health-records/human-api-ceo-on-unifying-health-data/a/d-id/1317195

Softwareplatformsthatallowconsumerstosharetheirdatawiththirdpartiesarebeingdeveloped.

Examplesofconsumercontrolleddata-sharingplatformsincludedigi.meand…

…HumanAPI.

Predictiveanalyticscanstreamlineandcutthecostsofunderwriting.


Thelifeindustryhasbeenslowtoimplementadvanceddataminingandpredictiveanalyticstechniques,butthiswilllikelychange.A2009study,sponsoredbytheSocietyofActuaries,foundthatonly1%ofNorthAmericanlifeinsurerssurveyedwereutilisingpredictivemodellingintheirunderwriting.37Inotherindustries,suchasbanking,P&Cinsuranceandbancassurance,thesetechniqueshavebecomewidespread.38IntheP&Csector,forexample,manycompaniesusefinancialandcredithistorydatatounderwritepersonalautoandhomeownersinsuranceproducts.

Theuseofpredictiveanalyticsinlifeinsurancehasbeenhamperedbychallengestomodellingrisksthatstemfromthelongerpolicydurationandlowerclaimsfrequency.Sufficient,high-qualityhistoricaldata–acriticalfirstcomponentofanymodel–areoftennotreadilyavailable.39Moreover,itisdifficulttocomeupwithrobustpredictorsofthemortalityrate,whichistheultimatetargetvariable,especiallyatyoungerages.Thuslifeinsurershavefocusedonbuildingmodelstopredictrelatedproxyvariables,suchasunderwritingclass/riskcategory(eg,standardvsnon-standardrisk)orsmokerstatus.Modelsfrequentlyaimtoidentifycustomersmostlikelytobeinthestandardriskcategoryandofferthemcoverwithreducedunderwritingrequirementsatfullyunderwrittenrates.Accordingtoa2014KPMGInternationalsurvey,capturingreliabledataandimplementingtherightsolutionstoanalyseandinterpretthedataarekeychallengesforinsurersusingdataanalytics(SeeFigure10).

Source:Digital Technology’s Effect on Insurance survey,KPMGInternational,May2014.

InsomemarketssuchastheUS,lifeinsurershavebeenmorecomfortableusingpredictivetechniquestotriageapplicationsandofferstreamlinedunderwritingthatavoidsexpensivemedicaltestsforhealthypeople.40Companiestakingthisapproachuseanalyticalmodelstoreplicatefully-underwrittendecisions.Whereamodel’spredictionsaligncloselywithfullyunderwrittendecisions,itsalgorithmscanbeusedtopredictunderwritingdecisionsforfutureapplicants,bypassingmedicaltestsandstreamliningthepurchaseprocessforsomeapplicants.Forexample,PrincipalFinancialhasintroducedapredictiveunderwritingprogramthatreliesondatafromtraditionalsources.AndAvivaintheUShasusedapredictivemodellingsystembasedpartlyonconsumer-marketingdata,reportedlygettingresultsthatmimickedwelltraditionalunderwritingtechniques.Themodelwasbuiltonthepremisethatmanydiseasesrelatetolifestylefactorssuchasexercisehabitsandfast-fooddiets.41

37Automated Life Underwriting, A Survey of Life Insurance Utilization of Automated Underwriting Systems,SOAandDeloitte,December2009.

38Predictive Modeling for Life Insurance, Ways Life Insurers Can Participate in the Business Analytics Revolution,Deloitte,April2010.

39Ibid.40Ibid.41L.ScismandM.Maremont,“InsurersTestDataProfilestoIdentifyRiskyClients”,Wall Street Journal,19

November2010.

Adoptionofpredictivemodellinghasbeenslowinlifeinsurance.

Challengesstemfromthelongerdurationoflifeinsurancepoliciesandlowerclaimsfrequency.

Figure 10 Challengesfacedbycompaniesusingdataanalytics

Keeping data secureReacting in a timely fashion as insights are identifiedIdentifying the right risk indicators/parameters

Balancing human judgement with data-driven decision making

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Capturing reliable data

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Predictive analytics in underwriting: the Principal Financial exampleIn2014,PrincipalFinancialintheUSrolledoutanacceleratedunderwritingprogramthatreliesontraditionalsourcesofinformationtoidentifygoodrisksandmaketheunderwritingprocessquickerandeasier.TheprogramusesdatafromtheMIBGroup,42motorvehiclereportsandprescriptionrecords.ApplicantsgothroughaphoneinterviewthatusesPrincipalFinancial’sTeleAppelectronicapplicationtocollecttheirpersonalhistory.Qualifyingindividuals’applicationscanbeapprovedwithin48hourwithasuper-preferredorpreferredrating.Eligibleapplicantsincludeindividualsaged18-60applyingforanyretaillifeinsuranceproductwithfaceamountuptoUSD1million.43

Otherlifecompaniesoffersimplifiedunderwritingprocesseswithashortlistofquestionsandinstantapproval,butathigherpremiumratesthanthoseoffullyunderwrittenproducts.WhatdifferentiatesPrincipalFinancial’sapproachisthatitofferseligibleapplicantsthesameproductcharacteristicsandpremiumasafullyunderwrittenproduct.Accordingtocompanysources,50–60%ofeligiblepreferredandsuper-preferredapplicantsqualifyforacceleratedunderwriting.44

Inthefuture,easieraccesstodataindigitalformandfromnon-traditionalsourceswillenableamorewidespreaduseofpredictiveanalyticsinunderwriting.Abilitytoretrievemedicalrecordsinstantaneouslyholdsbigpromise.Itwillacceleratetheprocessandleadtobetterunderwritingdecisions,becauseelectronicmedicalrecordscaneasilygothroughpredictivealgorithmstoproducemoreconsistentresultsthanhumandeliberation.Newtoolsfordataanalysiswillalsohelp.Thepremiseisthattherearecorrelationsbetweenlifestylefactorsandmortality,andthatmoredataandnewdataminingtechniqueswillunearththese.Someearlyexperimentshaveshownthistobethecase,althoughsimplifyingtheunderwritingusingamodelbasedonsuchtechniquesdidnotinducemorecustomerstobuytheproduct.Lifeinsurerscurrentlydonotmakewidespreaduseofthird-partydataonconsumersbeyondthetypesusedtraditionally(eg,fromMIBGroup,motorvehiclereportsandprescriptionrecordsintheUS)duetoconcernsaboutregulatoryandreputationalrisks,buttheacceptanceofusingsuchdatashouldimproveovertime.

Pushing the boundaries of insurabilityTechnologicaladvancementsandafloodofdatawillleadtobetterunderstandingofrisksandashiftfromtraditional,experience-basedunderwritingtoareal-time,exposure-basedapproach.Lifeinsurershavetraditionallyassessedhealthrisksandaskedquestionsaboutlifestylebehaviourslinkedtoahigherriskofmortalityjustonce–atthepointofsellingapolicy.Technologynowallowstrustedinsurerstoaccessdataregularlywiththepermissionofhigh-riskcustomersinexchangeforinsurancethathadatonepointbeenunaffordableorunavailable.Nowitcanbeofferedasarenewableproductwherethepatientneedstoprovidecontinuousproofofgoodhealth.Conversely,low-riskcustomersmaywanttopushdatatotheirinsuranceprovidersinexchangeforlowerpremiumrates.

42MIBGroup,Inc(formerlyTheMedicalInformationBureauInc.)isacooperativedataexchangeformedbytheNorthAmericanlifeinsuranceindustryin1909.MIBistheonlyinsuranceconsumerreportingagencyinNorthAmericaandoperatesadatabaseofmedicalinformationonsomeindividualswhohavepreviouslyappliedforhealthinsurance,lifeinsurance,disabilityinsurance,criticalillnessinsuranceandlong-termcareinsurance.

43A.R.O’Donnell,“ThePrincipalSpeedsLifeInsuranceUnderwritingtoWithin48HoursWithoutLabs,Insurance Innovation Reporter,3March2014,http://iireporter.com/the-principal-speeds-life-insurance-underwriting-to-within-48-hours-without-labs/

44Accelerated Underwriting Program,ThePrincipalFinancialGroup,www.principal.com

PrincipalFinancialusespredictivemodellingtospeeduptheunderwritingprocessforhealthyapplicants…

…andofferthemcoverageatfullyunderwrittenrates.

Newtypesofdataandanalyticaltoolswillhelpexpandtheuseofpredictiveunderwriting.

Betterunderstandingofriskswillpushtheboundariesofinsurability.


Somelifeinsurershavebeenabletounderwriterisksthatpreviouslycouldnotbecoveredprofitably.AnexampleisAllLife,alifeinsurerinSouthAfricawhichhasusedbetterdataandmonitoringtoofferinsurancetopeoplesufferingfrommanageablediseaseslikeHIVanddiabetes.45Tomaintaintheircover,policyholdershavetogoforregularbloodtestsand,inthecaseofHIV,takeantiretroviralmedicationasprescribed.AllLifesendsremindersfortestsandmonitorsresults,pullingdatadirectlyfrommedicalproviderswithaclient’spermission.UnderSouthAfricanlaw,ifapolicyholderdoesnotfollowtreatmentprotocol,benefitsorcoveragecanbeloweredorcancelled.Thecompanyassessesitsriskeverythreetosixmonths.

Impactondistribution

Inthecontextofthissigma,distributionisdefinedastheactualpurchase/saletransactionandallotherinteractionsaninsurerhaswithitscustomers.Theseinclude,forexample,theprovisionofandaccesstoinformationonproductsandprices,negotiationswithconsumers,andafter-salesandcustomerretentionactivities(seeFigure11).

Source:sigma2/2014–Digitaldistributionininsurance:aquietrevolution,SwissRe.

Traditionally,specialistfirmshavebundledtogethersomeorallofthesedistributionactivitiesandintermediatedbetweencustomerandinsurer.Intermediariescontinuetodominatedistributionoflifeinsurancearoundtheworld.Directsalesintermsofpremiums,includingthosebyinsurers’ownsalesforces,typicallyrepresentlessthanaquarteroflifeinsurancesales.Butnewtypesofintermediariesfrombothwithinandoutsideinsurancearebecomingmoreprominent,challengingthetraditionalagent-brokermodel.46

45E.Brat,PClarket.al."BringingBigDatatoLife:FourOpportunitiesforInsurers”,bcgperspectives.com,17July2014,https://www.bcgperspectives.com/content/articles/insurance_digital_economy_Bringing_big_data_life/

46Foradetaileddiscussion,seesigma 2/2014Digitaldistributionininsurance:aquietrevolution,SwissRe.

Withnewtechnology,somelifeinsurersareunderwritingriskspreviouslydeemeduninsurable.

Distributionismorethantheactualpurchase/saletransaction.

Figure 11Activitiesintheinsurancedistributionchain

Intermediariescontinuetodominatedistribution.

Preliminary information search

Other pre-sales activity

Completing the purchase/sale

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Marketing Basicsearch/

informationgathering Productdesign

Assessmentofrisk/underwriting

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Theimportanceofnewdistributionchannelssuchastheinternet,smartphonesandsocialmediainlifeinsuranceisincreasing.Accordingtoarecentstudyofconsumerviewsabouttheimportanceofvariousdistributionchannels,theinternetandmobilechannelsexhibitedthelargestincreasesinimportancebetween2012and2014.47Forthoseaged34yearsandolder,thetraditionalagent-baseddistributionchannelremainsmostimportantbutfor18-34yearolds–thekeyageforbuyinglifeinsurance–onlinedistributionisasimportantastraditionalagents(seeFigure12).

472015 World Insurance Report,CapGemini/Efma,2015.

Theinternetandmobile-baseddistributionchannelsarebecomingincreasinglyimportantininsurance…

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Figure 12Importanceofdistributionchannelbyageandregion,lifeinsurance,2014

Source:World Insurance Report 2015,CapGemini/Efma,2015.

Thiscontrastswiththesatisfactionoflifeinsurancecustomerswithdifferentdistributionchannels.Acrossallregions,theinsuranceagentprovidesthehighestlevelofpositivecustomerexperience(seeFigure13).Today’sconsumers,particularlyyoungerpeople,havebecomeusedtoaninnovativeandcustomer-friendlydigitalexperiencethroughtheirdealingswith,forinstance,onlineretailersandthetravelsector.Theyexpectthesamefrominsurersbutarenotgettingit,yet.Thereisaneedfortheinsuranceindustrytoimproveitsdigitaldeliverycapabilities.

Effectivedistributionisnotaboutfocusingononechannel.Rather,strategyshouldbegearedtowardsreachingpotentialcustomersinatimelyfashionwithrelevantcontentthroughpreferredconsumerchannels.Newtechnologiesandincreaseddataavailabilitycanhelpinsurerstailoramulti-channeldeliveryapproachtooptimaleffect.

…butcustomersatisfactionwiththesenewchannelsisstilllow.

Amulti-channelapproachisneededforeffectivedistribution.


Figure 13Positiveexperiencelevelsbydistributionchannelandregion,lifeinsurance2014

Latin America

Developing APAC

Developed APAC

Europe

North America 51%

40%

35%

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43%

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Agent Phone Internet-PC Internet-mobile Social media

Associating positive emotions with the purchase of a life insurance policySellinglifeinsurancecanbechallenginggiventhecomplexnatureofsomeoftheproductsandlengthyunderwritingprocedures,ofteninvolvingmedicalassessment.AccordingtoarecentstudyinEurope,manypeopledohaveagoodunderstandingoftheriskstheyfaceintheirlives,butthisdoesnotmakethemmorelikelytobuyinsuranceproductstomitigatethoserisks.48

Onewaytoextendthereachoflifeinsuranceistomakethebuyingprocesseasier,andheretechnologycanhelp.Forexample,theapplicationprocessforsimpletermlifecovertypicallytakesseveralweeks,involvesapersonalmeetingorphoneconversationwithanagent,amedicalassessmentandextensivepaperwork.Someinsurersaretryingtochangethat.Forexample,HavenLife,astart-upfully-ownedbyMassMutual,offersafirst-fullyunderwrittentermlifeproductonline.Theapplicationproceduretakesjust20minutesofaconsumer’stime.Thewebsitealsooffersafinancialneedscalculator,andpreliminarycoveragemaystartimmediately.Applicantsstillhavetogothroughamedicalexamination,buttheyhave90daystosoandarecoveredduringthattime.Makingthepolicysimpler,cheaperandusingplainlanguagetodescribecoveragearealsoimportantconsiderations.

48European Insurance Report 2015, Next Generation Insurance,SwissRe,2015.

Sellinglifeinsurancecanbeachallengingbusiness.

Newtechnologiescanfacilitateconsumerengagementwithlifeinsurance,forinstancebymakingtheapplicationprocesseasier.

Source:2015 World Insurance Report,CapGemini/Efma,2015.

22 Swiss Re sigma No 6 /2015


A technique increasingly used by life insurers to engage customers is “gamification”. This is the use of game thinking and mechanics in a non-game environment to increase customer engagement and stimulate desired behaviour through challenges, incentives and rewards.49 For instance US insurer CUNA Mutual Group has developed various apps designed to engage members in the complex process of retirement planning and product choice. “The Zone” is an ipad application that helps financial advisors sell a complex annuity product by visualising the risks and benefits of different product features and by increasing client engagement in the advisory process.50 The app appeals to a younger customer base when applied in the right context and with appropriate advisory services. As Figure 14 demonstrates, there is significant potential interest, particularly among younger people, in games and apps that can help them better understand their risks and insurance needs.

Source: Accenture Consumer-Driven Innovation Survey: Playing to Win, Accenture, 2013.

Big data offers new opportunities for customer segmentationMarketing of insurance has traditionally relied heavily on fairly basic approaches to customer segmentation, ie, aggregating prospective buyers into groups (segments) likely to have common needs and respond similarly to marketing. Typical customer attributes include geography, demographics, psychographics (eg, values, attitudes, lifestyles) and behavioural aspects (eg, price sensitivity). The disadvantage of this approach is that the groups are relatively broad, which can hinder effective targeting of consumers. In the age of Big Data, many new data types are available, which can be combined and analysed to define a more granular classification of existing and prospective customers. These new data types include website tracking information, purchase histories, call centre and customer service records, data from mobile phones and wearables and also social network profiles.

49 Digital Insurance Benchmark, Deloitte, 2014.50 See for example: K. Burger, “From Feeling Processed to Feeling Valued”, Insurance & Technology,

June 2014, pp 4–6.

Gamification can also help capture consumer engagement.

Figure 14Consumer interest in gamification, life insurance.

Survey question: Would you be interested in a computer game that your insurance provider offered to help you better manage the risks you face and to optimize your insurance premiums?

Very interested Somewhat interested

43%43%

35%

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10%13%25%

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0%

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55+35–5425–3418–24

New sources of data offer opportunities for more granular client segmentation.


TheUSmutualinsuranceandfinancialservicescompanyUSAAisamongtheleadersinleveragingitsvastmemberdatabasetomakepersonalisedoffers.Thecompany,whosemembersareactiveorformermembersoftheUSmilitary,hasrecentlyenteredapartnershipwithSaffron,aCalifornia-basedtechnologycompany,tocomeupwithanalgorithmthatanticipatesmembers’upcomingneedsforfinancialproducts.ItisbasedonpredictivemodellingtechniquesandallowsUSAAtodeterminetherightproductofferattherighttime.Dataanalysedincludedemographicattributes,historyofpurchasesofinsuranceandotherfinancialproducts,channelpreferences,recordsfromcallcentres,websitetrackinginformationanduseofmobileapplicationsetc.Accordingtothecompany,Saffron’sproductrecommendationsresultedinovera50%liftinpredictiveperformanceoverothermethodspreviouslyapplied.51

Inadditiontobettertargetingtheexistingcustomerbase,newtechnologiesalsoofferthepotentialtoreachnewcustomersegments.Inemergingmarkets,thedistributionofinsuranceviamobiledeviceshasgrownexponentiallyoverthelastdecade,supportedbytherapidspreadofmobilephoneuse.52Thetwolargestcompaniesdedicatedsolelytomobileinsurancedistribution,MicroEnsureandBima,havealreadyreached15millionand13millionpeople,respectively.StartinginSub-SaharanAfrica,whichhasbeenattheforefrontofmobileinsurancedistribution,theyhavemovedrapidlyintonewmarketsinAsiaandLatinAmerica.Muchoftherecentexpansionofmobiledistributioninemergingmarketshasreliedontherapidgrowthofthird-partytechnologyserviceproviderswhichhaveessentiallytakenoverinsurancefunctionssuchasproductdesign,underwriting,policyadministrationandclaims.53Thedownsideforinsurersisthattheydonothavedirectaccesstotheircustomersandareusedmainlyforlicensingandcapitalrequirements.

Improving customer retention by increasing engagementCurrently,thecompletionofalifeinsurancesaleoftenmarkstheendofcustomerinteractioninmanydistributionmodels,withtheremaininginteractionfocusedonbillingandclaimshandling.However,thiskindofrelationshipmissesopportunitiesforinsurerstoaddressthefullrangeofcustomerneedsovertheirlifetime.Customerrelationshipsneedtobecomemoreinteractiveaftersigningofthecontract,andnotonlyinthecaseoftherebeingaclaim.Frequentaccesstothecustomerandtheirdataprovidesinsurersandintermediarieswiththeopportunitytospotevolvingneeds.

Technologycanfacilitatenewwaysofinteraction.Forexample,somelifeinsurersareengagecustomersthroughprogrammesthatrewardthemforhealthylifestyleactivitiesandchoices,suchasexercising,regularcheck-upsandgivingupsmoking.TheVitalityprogramme,developedbySouthAfricaninsurerDiscoveryhasbeenaleadingexampleofhowtoretaincustomersbykeepingthemengaged(seeBox:Vitalityrewardprogramme).

51 “USAAandSaffrontoSpeakatWharton’sCustomerAnalyticsConference”,reuters.com,28April2015,http://www.reuters.com/article/2015/04/28/idUSnMKWdJPM7a+1dc+MKW20150428

52Mobilesubscriptionsworldwideincreasedfromlessthan1billionin2000toover6billionin2011,ofwhichnearly5billioninemergingmarkets.See:Information and Communications for Development 2012: Maximizing Mobile,TheWorldBank,2012.

53Fordetails,seeMobile insurance distribution in emerging markets: African innovations spreading globally,November2015,SwissRe.

Predictivemodellingtechniquesmayhelpinsurersbetteridentifytheirclients’needs.

Mobiletechnologyoffersthepotentialtoreachnewcustomersegments,particularlyinemergingmarkets.

Lifeinsurersneedtohaveamoreinteractiverelationshipwiththeircustomers.Accesstocustomerdatacanhelpthemdoso.

Someinsurerstrytoincreasecustomerengagementwithrewardprogrammes.



Vitality reward programme

VitalityisarewardprogrammedevelopedbySouthAfricaninsurerDiscoveryandlaunchedin1997.Theprogrammeencouragesconsumerstoengageinhealthyactivitiessuchasexercising,stoppingsmokingandhavingregularmedicalcheck-ups.Inreturn,theygainVitalitypointswhichcanberedeemedfordifferentbenefits.Thosemayincludediscountsongymmembership,healthyfoodpurchases,flightsandhotels,andstorevouchersandcinematickets.Activeclientsmayalsobenefitfrompremiumreductions.Butthekeyisthatmoreengagedhealthycustomerskeeptheirpoliciesforlonger,apositiveinfluenceonportfolioprofitabilityfortheinsurer.

In2004,DiscoveryenteredajointventurewithPrudentialUKtocreatePruHealthandPruProtecttoexpanditsbusinessandtheVitalityprogrammeintheUK.In2010,itpartneredwithChineseinsurerPingAn,beforelaunchingineightAsiancountriestogetherwithAIA,thepan-Asianlifeinsurancegroup,in2013.Andin2015,VitalityexpandedtotheUSbyenteringintoapartnershipwithJohnHancock.VariousstudieshaveexaminedthehealthoutcomesofVitalityprogrammeparticipation.Onestudyshowedthatrebatesof10%and25%forhealthyfoodsareassociatedwithanincreaseintheratioofhealthytototalfoodexpenditureby6%and9.3%,respectively.54AnotherfoundthatthoseparticipatinginVitality’sincentive-basedwellnessprogrammehadlowerhealthcarecosts.55However,clientinvolvementinfitness-relatedactivitiesisgenerallylow.WhereasaboutaquarterofallVitalitymembersintheUKengagedinonlineactivitiessuchascompletinghealthandwellnesssurveys,onlyabout8%hadactivegymmembershipsandlessthan3%engagedinotherphysicalactivitiesin2013.56

Vitalityaimstoimprovepolicyholders’healthandpersistencybehaviouraswellasclaimsexperience.TheynowuseFitbitsintheirprogrammestomotivatememberstostayactive.Note,however,thatpolicyholdersstillhavetogothroughatraditionalunderwritingassessment.Assuch,theprogrammeispredominantlyaclientloyaltyprogrammeratherthanbeingpartofDiscovery’sunderwritingprocess.

The changing role of insurance intermediariesWiththehugeamountofinformationavailableontheinternet,customersareincreasinglywell-informedaboutinsuranceoffersfromdifferentproviders.Astheyalso(slowly)becomemorecomfortablewithbuyinginsuranceonline,theroleoflifeinsuranceintermediarieswillneedtoevolve.

Independentadvisorshavetraditionallyprovidedguidancetoconsumersaroundchoiceoflifeinsuranceproviderandproduct.Theywilllikelycontinuetodoso,particularlyforthepurchaseofmorecomplexproducts,sincecustomersstillderivevaluefromtheiradviceandexpertise.Eveninthecaseofmorestandardisedproducts,someclientswillpreferpersonalinteractionoveronlinemarketresearch,butthisislikelytobecomemoretheexceptionthantherule.

54R.Sturm,R.An,D.SegalandD.Patel,“ACash-BackRebateProgramforHealthyFoodPurchasesinSouthAfrica,ResultsfromScannerData”,American Journal of Preventive Medicine,vol44,no62013,pp567-572.

55D.Patel,E.Lambertet.al.,“TheAssociationbetweenMedicalCostsandParticipationintheVitalityHealthPromotionProgramamong948,974MembersofaSouthAfricanHealthInsuranceCompany”,American Journal of Health Promotion,vol24,no32010,pp199–204.

56TheseresultsrefertoactivitieswithinonemonthafterpolicyinceptionfromMarchtoJune2013.SeeN.Read,Vitality – Managing Risk through the Use of Incentives,TheGenevaAssociation,November2014,https://www.genevaassociation.org/media/908577/ga_11th_healthageing_conference_read.pdf

Vitalityhasarewardsprogrammetoengagetheircustomers.

VariousstudiesfoundbeneficialimpactsofVitality’sprogramme.

Theclient-loyaltyprogrammeaimstoimprovepolicyholders’healthandclaimsexperience.

Ascustomersbecomebetterinformed,theroleofintermediarieswillneedtoevolve.

Advisorswillcontinuetoplayanimportantrole,particularlyinthedistributionofmorecomplexproducts.


Bytakingadvantageofdigitaltechnology,independentadvisorscancombinetheadvantagesofautomationandpersonalisedadvice.Thelifeinsuranceindustryhasputalotofeffortintoautomatingtheunderwritingprocess.Forexample,SwissRe’sautomatedunderwritingsystem“Magnum”allowsforanefficientunderwritingandimprovedcustomerexperienceatthepointofsale.57Inaddition,otherapplicationshavebeendevelopedthatallowindependentagentstoenterclientriskparametersintoasinglesystem,getabindingquotefromseveralinsurersandconcludethetransactionimmediately.58Thisremovestheneedforadvisorstobasetheirassessmentonpreliminaryquotes,dealwithseveraldifferententryformsandtogetbindingquotesfromdifferentinsurers.Streamliningdatacollectionandacceleratingtheunderwritingprocesshelpsavoidinterruptionsandislikelytoincreasethenumberoftransactionsthatreachtheclosingstage.Technologycanbeusedtofurnishagentswithallthedatatheyneedtomakethenextsale.

Tomaintaintheirraisond’être,someintermediariesareprovidingadditionalservicestocustomers.Forexample,Swissstart-upcompany“Knip”haslaunchedamobileappthatallowscustomerstostorealltheirinsurancepoliciesindigitalformat.Besidesprovidingaconvenientoverviewofallinsurancecontractsinoneapp,theserviceallowsforchanging,cancellingandbuyingnewpoliciesaswellasreportingclaimsviatheapp.Knipactsasaninsurancebrokerandreceivesmanagementfeesandcommissionsfrominsurancecompanies.59

Theincreasinguseofmultipledistributionchannelsandthepotentialforconflictsthismaycausemayleadinsurersandagentstorethinktheirtraditionalcooperationmodels,includinghowintermediariesarecompensated.Forexample,aclientacquiredonlinemayrequireadvicefromanagent.Acompensationmodelthatrewardsagentsfortheseservicesviaadvisoryfeesthatconsumersarewillingtopaymayhelpalleviatechannelconflictsthatcouldarisewithinapurecommissions-basedsystem.

57MagnumisSwissRe’sautomatedunderwritingsolutiondesignedspecificallyfortheunderwritingoflifeandhealthinsurance.Itincludesaninnovativeunderwritingapp.formobiledevices.Manyapplicationsareacceptedautomaticallywithconcise,relevantcustomerinformation,makingMagnumMobilestraightforwardfortheagentandtheconsumer.

58Examplesinclude:“UnderwriteMe”,“vers.diagnose”and“EQuot”.59"SwissMobile-FirstInsuranceBrokerKnipPicksUp$15.7MSeriesB",techcrunch.com,26October

2015,http://techcrunch.com/2015/10/26/knip/

Digitaltechnologyallowsforintegrationofunderwritingandsalesprocesses.

Intermediariesalsoofferadditionalservicestotheirclients.

Rethinkingcompensationstructuresmayhelpalleviateconflictsbetweentraditionalanddigitalchannels.


Strategicimplications

Technologyandthedigitaldatarevolutionwillfundamentallychangethebusinessofinsurance.Thechallengeforinsurerswillbetooptimisetheirdatamanagementcapabilitiesandpracticestobestengageconsumers.Togrowtheirbusiness,theywillneedtoadapttheiroperatingmodels,reviewtheirinvestmentsintechnology,andrethinktheirtalentstrategy.

Potentialnewbusinessmodels

Newtechnologiesanddigitaldataprovideinsurerswithanopportunitytoconsidernewoperatingmodels.Theoptionsinclude: Tospecialiseinapartoftheinsurancevaluechain; Tocreateafullydigitalplatformforthewholevaluechain:and Providenon-traditionalservicesaspartoftheinsurancepackage.

Technologycanunbundlethevaluechainsothatinsurerscanprovideone,someorallofproduct,underwritingandclaimsservices.Someinsurersalreadyoffer“white-labelled”productsinspecificsegmentsonly.60Thiscanappealtofirmswantingtospecialiseincertainpartsofthevaluechainoramarketsegmentsuchas,forexample,insurerswithstrongunderwritingbutweakdistributioncapabilities.

Havingadigital-onlybrandisalsoapossibility.Traditionalinsurerswantingtotransitionfromtheirbrick-and-mortarworldfinditdifficulttojettisonlegacysystems,adoptcompletelynewones,andattracttech-savvytalent.Onewaytodealwiththisistoestablishanindependent,self-manageddigitalbusinesswithfullP&Lresponsibility.Someinsurershavedonethis.Forexample,since2010SumitomoLifehasrunasubsidiaryofferingmedicalinsuranceinternetproducts,61 andin2013KyoboLifelaunchedKyoboLifeplanet asastandaloneno-frillsbrand.62

Amanagementchallengehereistoallowtheindependentbusinesstorunitself,effectivelyasastart-up,andtoavoidthetemptationofsubjectingittothebureaucracyofthelegacybusiness,ortakeitbackin-housetoosoon.Also,whileastandalonedigitalbusinessiseasiertomanagefromaninsurer’spointofview,therecanbechannelconflictsanddifficultyinupsellingtraditionalproductstopolicyholdersastheyage.Finally,thereissomeevidencethatcustomersdesirebothdigitalandphysicalinteractionespeciallyforcomplexproductslikelifeinsurance.Bain&Companyfoundthatcustomerswhousebothdigitalandphysicalchannelsassigninsurersamuchhigher“netpromoterscore”thandocustomerswhouseonlydigitalchannels.63

Insurerscanalsousetechnologytoofferservicesoutsidetheboundsoftraditionalinsurance.Somelifeinsurersalreadyofferhealthscreenings,preventativeconsultations,discountcardstopharmaciesandothertypesofassistance,positioningthemselvestoprovidefamily,healthandwealthservicestoconsumers.Figure15depictsarangeofabravenewworldofservicesthatsophisticatedtechnologyplatformscouldopenuptoinsurers.

60“Whitelabellingreferstotheprovisionofproduct,underwritingandclaimsthroughanindependentdistributionchannel.Foranexample,see“UforLifelaunchesindustry’sfirstonlinelifeinsuranceplatform”,theSundaily.my,7May2015,http://www.thesundaily.my/news/1410755

61Annual Report,SumitomoLife,2014,p21.62“Korea’sFirstInternet-onlyLifeInsurertoBeginBusinessinDecember”,The Korea Economic Daily,

31October2013,http://english.hankyung.com/news/apps/news.view?c1=02&newscate=1&nkey=201310311224381.

63Leading a Digical® transformation in insurance,Bain&Company,2014.

Insurerswillneednewbusinessmodels,andgreaterinvestmentintechnologyandtalentmanagement.

Technologycouldspurnewdirectionsforinsurers,fromspecialisationorpuredigitaltotheprovisionofadditional,non-traditionalservices.

Technologycanunbundlethevaluechainininsurance.

Anotheroptionistocreateapurelydigitalbusinesswithcompletelynewsystemsinastandalonesubsidiary…

…butthiscanresultinmanagementchallenges,channelconflicts,andcross-sellingdifficulties.

Insurerscouldoffernon-traditional,complementaryservices.


Source:SwissReEconomicResearch&Consulting.

Artificialintelligencecanenableandenhancethenewpossibilities,suchastheprovisionofpersonalisedclientservices.Forexamplein2014,USAAlaunchedapilotusingWatson’scognitivecomputingplatformtoadviseUSmilitarypersonnelonarangeofdecisions,includingjobsearches,moving,insurancebenefitsandsupportwhentheytransitiontocivilianlife.Theservicewasinitiallyweb-basedandrequiredmemberstotypeintheirquestions.ButasAIandvoicerecognitionimproves,membersmayeventuallybeabletohaveaconversationwithadigitalagent.64

Insurerscanenableaccesstonewer-agetechnologies,suchasplatformsforon-demandaccesstohealthcareandconsultationswithlicensedhealthpractitioners.65Theycouldexplorehomemobilityserviceslinkedtoroboticsandsimilarcapabilities.Exoskeletons–wearableroboticdevicesthatenableindividualswithinjuries(eg,spinalcorddamage)tostandupright,walk,turn,andclimbanddescendstairs–severalofwhicharebeingbuilttoday,couldbepartofaserviceallowingpeopletohaveahigherqualityoflifeastheyageorbecomedisabled.Adeviceofferedbystart-upReWalkisnowbeginningtobecoveredbyinsurers,andhopefullycanhelpinjuredworkersreturntogainfulemployment.66Insurerscanalsoconsiderpartnershipstoofferseniorcareproductslikeedgedetectiontechnology(imagingtechnologythathelpsspothomehazards,eg,steps,sharp-cornertables,etc.),indoornavigation,technologicalmattresspads,andhipprotection.67

Insurersarestillexploringhowtomonetisetheseinteractionsandrecoverthecostofservices,especiallyinprice-sensitivemarkets.Oneoptionisrevenuesharingarrangementswithexternalpartnerswhobundletheirofferingswithtraditionalinsuranceservices.Anotheristoworkwithemployers,sincetheytypicallyhavedeeperpockets.Forexample,GrandRounds,aBigDatadoctor-matchingservicefoundthatemployerswereopentopayfortheserviceaftertheyfoundthat

64USAA and IBM Join Forces to Serve Military Members,IBM,23July2014,http://www-03.ibm.com/press/us/en/pressrelease/44431.wss

65On-demandaccessplatformsincludeDoctoronDemand,HealthTap,FirstOpinion,Talkspace.OtherservicesincludewearableheadsetsthatslowtheeffectsofAlzheimer’s,andhelpingpeoplewholosemusclecontroluseconnectedproductsathomethroughbraincommands(developedbyEmotivandPhilips;seehttp://www.usa.philips.com/healthcare/innovation/research-and-exploration/als-mind-control).

66E.Micucci,“CommercialinsurancebeginsforReWalk”,WBJournal.com,23July2015,http://www.wbjournal.com/article/20150723/METROWEST01/150729971/commercial-insurance-begins-for-rewalk-with-spaulding-patient

67C.Tuohy,“Howtechnologycankeepgrandmaoutofthenursinghome”,insurancenewsnet.com,15June2015,http://insurancenewsnet.com/innarticle/2015/06/15/how-technology-can-keep-grandma-out-of-the-nursing-home.html

Figure 15 Possibletech-enabledproductandserviceofferingsopentoinsurers

Tailoredvalue

addedservices

Conciergeandotherassistanceservices

Accessphysiciansoutsidetheirarea

Chronicdiseasemanager

Vitalsignmonitoring/interventionservice

Hirebabysitters,petsitters

Platformtoconnectthedisabled

Mobilesecurity Edgedetection

technology

Secondopinions Preventative

consultations Discountcardsto

pharmacies

Findingahome Electronichealthvault Accessdoctor’snotes Automatedfinancial

planning

Familytracking “Assistivejogger”

contraptions Robotics

exoskeletons

Coreproducts

Current model Traditional

Life&Health

Just-in-timeinsurance No-medical-exam

Lifecycle-basedpolicies,basedonsocialmediaengines

Offline,non-digitaldeliverymodels

Nextgenerationofconnectedtechnology

Artificialintelligencetechnologycanbeusedtoprovideautomatedyetpersonalisedclientservices

Awiderangeofservicescouldbeprovidedaspartoftheoverallinsurancepackage.

Thesenewserviceswouldneedtobemonetised.

http://www.WBJournal.com

https://shp.swissre.com/teams/erc/SharedDocuments/Sigma/15_6 Life and health technology/Text/insurancenewsnet.com


Strategic implications

better-chosentreatmentsoftensavemoney.68Insomecasesthecostofimplementationcouldbeoffsetbylowerinsurerpay-outs,asaUSSenatehearingin2015ontheuseoftechnologyinagingheard.Atthehearing,aparticipantestimatedthathesavedUSD327000onnursinghomeandhealthaideservicesforhis76-yearoldmother-in-lawoveratwo-and-a-halfyearperiod.HedidsobywiringherhomeforaninstallationcostofUSD2189andamonthlyfeeofUSD59.69

NextgenerationofITplatforms

ThedigitalagewillnecessitateanewviewofITarchitecture.Lifeinsurersneedtobuildcapabilitytoseamlesslybundleproductsandservices,anddeliverthemthroughamulti-channelfront-endthatoffersasingleviewofthecustomerandofhis/herexperienceacrossalltouchpointsintheinsurancevaluechain.Anintegrationengineshouldbeabletoviewthecustomerasa“clusterofone”andassesswhatcombinationofproductsandservicestopitch.Ideally,newpredictivemodelscanbebuilttoadviseonproductstopitchandevenberefinedautomatically.Suchtechnologyisalreadybeingdevelopedbystart-ups,someofwhichhavethefinancialbackingoflargeinsuranceplayers.70

Insurersshouldalsocreatealayerwhereacentralisedviewofthedataisstored.Thedatacouldcomefromcustomer’srecordsavailableinthepolicyadministrationsystem,socialmediaanddigitalfootprints,recentpurchases,GPSnavigation,dataonlikes,dislikesandeventsplannedetc.Thedatawillneedtobeanalysedasitstreamsintogenerateinferencesaboutnewsellingopportunities.Thesystemsshouldalsobecapableofdealingwithnewdatatypesfromsocialmedia,blogs,videos,audiosandlocationapps.

Harmonisingdatafromdisparatedatasourceshasprovenchallenging.Lifeinsurershavelongbeentryingtocreateasingleandcomplete360°viewofthecustomer,updatedinrealtime.71AccordingtoresearchfromSMA,35%ofinsurerssaytheyhaveassembledthatview,butonly8%canpresentitinreal-timetotheindividualsinteractingwithapolicyholder.Almosthalf(46%ofinsurers)donotyethavethesingleview.72Someinsurersareworkingwithestablishedtechnologyvendorstobuildthatcapability,whileothershavejoinedforceswithstart-upsfocussedondataharmonisationandplatformsthatuseAItoattempttodoso.73Incidentally,insurershavealsostruggledwithcreatingacomplete,masterversionofcustomers’contactinformation,andarelookingforinnovativesolutionstothischallengetoo.74

68J.Tozzi,“Start-upsthatgiveyouasecondopiniononcostly-surgery”,Bloomberg,20August2015.http://www.bloomberg.com/news/articles/2015-08-20/the-startups-that-give-you-a-second-opinion-on-costly-surgery

69C.Tuohyop.cit.70Forexample,NewYorkLifehasinvestedinastart-upthatisautomatingpredictivemodelcreation.

“ContextRelevantAnnounces$13.5MillioninSeriesB-1Funding”,Business Wire,25September2014,http://www.businesswire.com/news/home/20140925006190/en/Context-Relevant-Announces-13.5-Million-Series-B-1.TransAmericahasinvestedin0xdatawhoseproduct,H2O.ai,isanopensourcepredictiveanalyticsplatformfordatascientists.0xdata is now H2O.ai, Announces Production Customers including PayPal, Nielsen, and Cisco,H20.ai,17November2014,http://h2o.ai/news/2014-11-17-Press-Release/

71The360°viewisofacustomerisobtainedbyaggregatingdatafromthevarioustouchpointsthatacustomermayusetocontacttheinsurer,notjusttopurchasepoliciesbutalsotoaskforserviceandsupport.

72M.Breading,“SingleViewandtheCustomerExperienceinInsurance”,strategymeetsaction.com,9June2015,https://strategymeetsaction.com/news-and-events/sma-blog/single-view-and-the-customer-experience-in-insurance/

73Forexample,Tamr,astart-upinwhichMassMutualisaninvestor,aimsforaunifiedviewofthecustomerbyhelpingunifysiloed,fragmenteddatabasesacrossthefirm.SeeTamr Receives $25.2 Million in Financing from Hewlett Packard Ventures, Thomson Reuters, MassMutual Ventures and Others,Tamr,19June2015,http://www.tamr.com/tamr-receives-25-2-million-in-financing-from-hewlett-packard-ventures-thomson-reuters-massmutual-ventures-and-others/

74Forexample,AXAhasinvestedinEvercontact,afully-automatedcloudservicethatfindsandupdatescontactinformationirrespectiveofwhichchannelitcamefrom.Itdiscoversmissingcontactsinemails,allowsthemtobesharedwithcollaboratorsandkeepsCRMsandaddressbooksautomaticallyuptodate.SeeAXA Strategic Ventures invests in Evercontact,AXA,8April2015,http://www.axa.com/en/news/2015/axa-strategic-ventures-invests-in-evercontact.aspx

Forstarters,lifeinsurersneedtoreconfiguretheirtraditionalITarchitecture…

…toenableasingleandcentralisedviewoftheconsumeracrossalltouchpointsintheinsurancevaluechain.

Gettingtothesingleviewfromexistingdisparatedatasourcesandrepositoriesisnomeanfeat.

http://www.businesswire.com/news/home/20140925006190/en/Context-Relevant-Announces-13.5-Million-Series-B-1

http://www.businesswire.com/news/home/20140925006190/en/Context-Relevant-Announces-13.5-Million-Series-B-1

Swiss Re sigma No 6 /2015 29

Insurers as venture investors in Fin-Tech start-upsTo leverage innovation, insurers’ IT departments will need to acquire adaptive sourcing skills. Procurement teams have traditionally worked with a few well-known vendors, and have little experience of working with specialist start-ups. Some life insurers have begun exploring partnerships with smaller technology companies. Table 1 has some early examples of insurers partnering with – acquiring or investing in – such start-ups that could help them lead their own digital transformation. 75

Source: CB Insights, Swiss Re Economic Research & Consulting.

Sometimes non-insurance companies buy start-ups that could potentially be useful to insurers. For example in 2013 Climate Corp, a start-up focused on weather risk, was bought not by a large P&C insurer, but by the agricultural solutions company Monsanto, for USD 930 million.76

75 For more insight on investors in the insurance tech market, see “Insurance-Tech Start-ups Are Invading The Multi-Trillion Dollar Insurance Industry”, CB Insights, 5 June 2015, https://www.cbinsights.com/blog/insurance-tech-startups-investment-growth/

76 Monsanto to Acquire The Climate Corporation, Monsanto, 2 October 2013, http://news.monsanto.com/press-release/corporate/monsanto-acquire-climate-corporation-combination-provide-farmers-broad-suite. Subsequently in July 2015, Monsanto decided to focus only on the digital agriculture platform and sold the agriculture insurance business of Climate Corp. to AmTrust Financial. See The Climate Corp. Sells Crop Insurance Business to AmTrust Financial Services, Monsanto, 31 July 2015, http://news.monsanto.com/press-release/climate/climate-corporation-sells-crop-insurance-business-amtrust-financial-services-i

Some life insurers are partnering with start-ups to build their own data analytics and technology capabilities.

Table 1 Active venture investors in insurance technology enterprises

Theme Insurers and start-ups

Financing and investing platforms

USAA: Personal Capital, Coinbase, Prosper Marketplace Ping An: e-Toro, Payoneer, Lufax Axa: Widmee, Particeep, Fund Shop TransAmerica: Auxmoney, Next Capital MassMutual: IEX Group NorthWestern Mutual: Betterment, LearnVest

Next generation customer experience

American Family: Image Vision, Mobile Igniter, Shoutlet, Quietyme, Review Trackers, Moot Labs, Networked Insights

USAA: Expect Labs, Narrative Science, CafeX, Saffron Tech, MX Tech

Axa: Volunteer Spot, Evercontact MassMutual: Tamr

Value added services American Family: Abodo, Life360 USAA: Vast, Care.com, Cartera Commerce Ping An:Trafree, Mogoroom Axa: Easy Propreitaire, FLYR

Threat identification, data science, security

American Family: XOR Data, Airphrame, Wireless Registry, Zero Locus

USAA: ID.me Axa: Climate Secure TransAmerica: CipherCloud, H20.ai MassMutual: Recorded Future, Context Relevant New York Life: Skycure, AIG: K2 Intelligence, Algebraix Data

Health technologies Ping An:JMDNA, HealthcareCN, Rainbow Medical Axa: Limelight Health MassMutual: Picwell

There is competition for buying innovative risk-management start-ups.


Strategic implications

Newtalentstrategiestoembracetechnologyinnovation

Attractingandretainingtalentiskeytothesuccessofatechnology-drivenstrategy.Someinsurershaveplacedcertainhumanresourcesresponsibilitiesinthehandsofindividualbusinessunits,andothershavecentralisedthefunctionwithChiefInformationOfficers(CIO)orChiefDigitalOfficers(CDO).AccordingtoaGartnersurvey,9%ofinsurersalreadyhaveaCDO,77taskedwithdevelopingastrategicvisionofhowtechnologywilltransformthebusiness.Thestrategymayincludethecreationofanopen-innovationenvironmentthroughcollaboratingwithresearchinstitutionsandtechnologyvendors.

Insurersneedtorebrandthemselvesastechnologyemployersofchoice,especiallyfortheyoungergeneration.ITgraduatesmayhesitatetojoininsurersheavilydependentonmainframe-basedapplicationswrittenwitholderprogramminglanguages.Thus,partneringorbuyingmoretech-savvycompaniesmaybeanecessarypartofanewstrategy.Insurersalsoneedindustryexpertswhocantranslatetechnologyintoeffectiveuseacrosstheinsurancevaluechainandthismayneedtobedevelopedin-house.

Developingafuturetalentpoolwithskillsin"people-centereddesignprocess"78,datascienceandstart-upengagement,isalsocritical.InsurerslikeAXAhavesetupacceleratorprogramstoattractentrepreneurswithinterestingideas.79Aviva80andAllianz81run“hackathon”eventstoattracttechnologytalenttoinsurance-specificissues.AndMassMutualpartnerswithcolleges,hopingtoattractgraduateswithanaffinityfordatascience.82

InsurersarebringingtalentintoinnovationlabsandinternalA-teamsthatoperateoutsidethefourwallsofday-to-daybusiness.Theaimistoenablenewthinking,whileallowingfortheluxuryoffailure.Theteammemberscouldcomefromotherindustrieswhereinnovationisapre-requisite,soastobeunimpededbytraditionalinsuranceindustrythinkingandproblemsolving.Someinsurershavetakenthefirststepsinthisdirection.AvivabuiltitsfirstdigitalgarageinLondonin2014,andhasbroughttheideatoAsia.83ThisyearMetLifesetupadisruptiveinnovationlab,alsoinSingapore,tocreatenewbusinessmodelsinhealth,wealthandretirementservices.84

77Taming the Digital Dragon: The 2014 CIO Agenda,Gartner,2014,p5.https://www.gartner.com/imagesrv/cio/pdf/cio_agenda_insights2014.pdf

78ThisisatermusedbyGartner.Seehttp://www.gartner.com/smarterwithgartner/digital-humanisms-impact-on-customer-experience/

79AXA Launches Venture Capital Fund to Foster Entrepreneurial Discovery in Insurance and Financial Services, Improve Customer Experience,AXA,25February2015,https://us.axa.com/news/2015/axa-announces-venture-capital-fund-launch.html

80SeeAvivawebsite:http://www.aviva.co.uk/innovation/81SeeAllianzHackRiskappwebpage:http://hackrisk.bemyapp.com82NathanGolia,“HowMassMutualBuildsaDataSciencePipeline”,insurancetech.com,23October2014,

http://www.insurancetech.com/data-and-analytics/how-massmutual-builds-a-data-science-pipeline/d/d-id/1316902

83Aviva announces ‘Digital Garage’ in Singapore,Aviva,27July2015,http://www.aviva.com/media/news/item/aviva-announces-digital-garage-in-singapore-17510/

84“MetLifeLaunchesLumenLab–theFirst-of-its-KindInnovationCentreinSingapore,fortheLifeInsuranceIndustryinAsia”,businesswire.com,16July2015,http://www.businesswire.com/news/home/20150716005707/en/MetLife-Launches-LumenLab---First-of-its-Kind-Innovation-Centre

ManylifeinsurancecompaniesarehiringChiefDigitalOfficers.

Theindustryneedstorebrandtobeseenasanemployerofchoiceforyoungengineeringtalent.

Italsoneedstodevelopapipelineoftalentinotherspecialistareas.

Insurersaresettingupinnovationlabs,anddevelopingfast-fastiterativeapproachestoinnovation.

https://us.axa.com/news/2015/axa-announces-venture-capital-fund-launch.html

https://us.axa.com/news/2015/axa-announces-venture-capital-fund-launch.html


Newchallenges

Newtechnologypresentschallengesaswellasopportunities.First,thereareissuesarounddataprotectionandprivacyandhowthisisregulated.Second,insurerscouldcollaboratewith,orfacecompetitionfromnon-traditionalplayers(NTPs).

Usingdataresponsibly

Data protection and privacyInmonetisingthepotentialofdigitaltechnology,lifeinsurerscouldhaveproblemsfromdataprotectionandprivacy,cybersecurity,fraud,recordsretentionandauthentication.Personaldatacollectedbythirdpartiessuchasdataaggregatorsandretailershasbeenminedforcommercialpurposesformanyyears.Thishasbeenanacceptedpracticeinmanyindustries,butnotsofarbylifeinsurers.Eventhoughtherearenoexistinglegalrestrictions,lifeinsurershavebeenreluctanttoutilisethesedatabecauseofethicalconcernsthatitsusecouldbeviewedasoverlyinvasiveandthusposeareputationalrisk.85Intheabsenceofregulatoryguidanceondataprivacyinthedigitalage,thiscautiousapproachhasbeenprudent.

However,newregulationsarebeingdevelopedinmostcountries.Atthebeginningof2015,109countrieshaddataprivacylawsand,forthefirsttime,mostofthosecountries(56)wereoutsideEurope.86Thescopeofnationallaws,however,differconsiderably(seeFigure16).87Thereisadifferenceintheunderstandingofdataprivacyandthedurationthatthedatashouldbestored.IntheEU,forexample,citizenshavetherighttobeforgotten,anewconceptforUSandAsianinsurers.Thedifferencesraisecomplications,becauseofthelackofinternationalstandardsonconsistentuseandreportingofdatabylifeinsurersoperatingindifferentcountries.

Source:Data Protection Laws of the World Handbook,DLAPiper,2015.

85Consumerreactionstocommercialuseofpersonaldataarenotuncommon.Target,oneofthelargestretailersintheUS,quicklydiscoveredthatpracticesinfullcompliancewithallprivacylawscanmakeconsumersqueasy.See“HowTargetFiguredOutATeenGirlWasPregnantBeforeHerFatherDid”,Forbes,16February2012,http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

86G.Greenleaf,Global Data Privacy Laws 2015:109 Countries, with European Laws Now a Minority,UniversityofNewSouthWales,FacultyofLaw.Report,30January2015availablefromSocialScienceResearchNetworkwebsite,http://ssrn.com/abstract=2603529

87Regulatorydevelopmentsinthefieldofdataprotectionaredynamic.ContactDLAPiper([email protected])forthemostupdatedversionofthedataprotectionregulationmap.

Thenewtechnologyanddataanalyticsalsopresentchallengesaswellasopportunities.

Amainchallengeisdataprotectionandprivacyand,todate,differingnationalregulationinthisarea.

Thingsarechangingwiththedevelopmentofdataprivacylawsinmanycountries,althoughthesestillvarywidelyinscope.

Figure 16 Overviewofdataprotectionlawsoftheworld

Heavy

Robust Moderate

Regulation&

enforcementLimited

Heat map of global regulation and enforcement

http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

http://ssrn.com/abstract=2603529


New challenges

Insurersaregrapplingwithanumberofotherdataprivacychallenges(seeTable2).Thefirstisaclashwiththeprincipleofdataminimisation.Ratherthanstorelimitedamountsofinternalstructureddata,BigDataresearchrequiresfirmstostoreasmuchdataastheycan.Itishardtoapplydataprotectionlawswithoutknowingthenatureofthedatabeingstoredandhowitoriginated.Afurtherissueisthatanindustrythathasprideditselfonworkingprimarilywithhigh-qualitydataisnowdrawingconclusionsfrommodelsbuiltonmessydata.

TheEUGeneralDataProtectionRegulation,expectedtobepublishedin2016,mayhaveastricterregulationontheuseof“pseudonymised”data.Pseudonymisationmeansreplacingoneorafewattributes(eg,name)byanothervalue(eg,randomlygeneratednumber).Anonymisationmeanstransformingpersonalinformationintodatathatcannolongerbeusedtoidentifyaperson.Despitepseudonymisation,thepersonmaybeabletobeidentifiedthroughleveragingotherinformation.Anonymisationismeanttobemoresecure.

Insurersoftenpseudonymisedatabyreplacingthenameofthepolicyholderwithanumberforcertaintypesoftrendanalysis.Initscurrentform,theDataProtectionRegulationisveryrestrictiveontheuseofpseudonymisationandinsurersmayneedtocarryouttheoneroustaskofreachingouttoindividualpolicyholdersforconsenttousedatabeforeperformingananalysis.88Finally,asinsurers’shareandpurchasedatafromexternalproviders,theywillfinditdifficulttotrackhowandwhythedatawasoriginallycollected.Thisinformationmaynotevenbeknowntothedataprovider.


88Caution, Data Protection!,TopicsMagazineIssue1/2015,MunichRe,2015.

Thereareanumberofotherprivacyissues,suchastheclashbetweentheBigDatamindsetandthetraditionalprincipleofdataminimisation.

Further,regulationsaroundpseudonymisationaresettobetightenedup…

..andinsurersmayneedconsentfrompolicyholderstousedatabeforeperformingananalysis.

New world Old world Challenges faced by insurers

Shift in data initiatives

Correlation Causation Shift from rigid principle of causation

to correlation. Accuracy was key, now conclusions from messy data.

Pseudonymisation Anonymisation Re-identification risk. EU directive could restrict pseudonymisation; need to ask for consent.

Big Data (as much as possible) Data minimisation Fundamental tension on central data protection

tenet that data collection must be minimised.

Data sharing Data collection Challenges the principles of purpose limitation and transparency.

Table 2 Changingworldviewsondatacollection


Keeping consumers onsideAlso,lifeinsurerswillnotwanttoalienateconsumersthroughtheiruseoftechnologyanddataanalytics.Forexample,insomecountries,peoplemaybeuncomfortablewithinsurersusinginformationaboutthemstoredinthedigitaluniversetoformulateandmakeunsolicitedandpersonalisedoffersforcoverage.Thisseemstobemorethecaseindevelopedcountriesthanintheemergingmarkets.AsFigure17shows,a2013surveybyAccenturerevealedthatlifeinsuranceconsumersinemergingmarkets(China,BrazilandSouthAfrica)werelesshesitantthanthoseindevelopedmarketstoshareusageandbehaviourdatawithinsurersinreturnformoreoptimisedcoverage,pricingandpersonalisedproducts.89

Source:Accenture Consumer-Driven Innovation Survey: Playing to Win,Accenture,2013,SwissReEconomicResearch&Consulting.

Digital distribution and regulatory concerns Insurerswillneedtomonitorregulatoryconcernsarounddigitaldistribution,especiallyastheindustryisstilldealingwithissuesaroundmis-sellingoflifepoliciesandinadequateadvice.Forinstance,inanopinionpaperthisyear,theEuropeanInsuranceandOccupationalPensionsAuthority(EIOPA)saidthatwithrespecttosalesviatheinternetofinsuranceandpensionproducts,“sufficientadviceisnotalwaysprovidedortheinformationdisplayedisnotfairenough.”90TheEIOPAalsoobservedthatconsumersmaychooseaninsurancepolicybasedsolelyonthepriceoffered,ratherthanonmaterialdifferencesinquality.Anadditionalconcernisthatconsumersmayinadvertentlyenterintounsolicitedcontracts,giventhevariousoptionsandtick-boxfieldsthattheyneedtocomplete.Finally,itcouldbedifficultforregulatorstomonitordigitaltransactionsinrealtimeandgatherthenecessaryinformationtofulfiltheirsupervisorytasksatthenationallevel.

89Accentureinterviewed6135insurancepolicyholdersacross11countriesinJuly2013,intheautomotive,homeandlifesectors.ThedatainFigure17issourcedfromlifeinsuranceconsumerresponsestoQuestion18inAccenture’ssurvey,ie,“Wouldyoubecomfortableforyourinsuranceprovidertoaccessinformationonyourusage/behaviourinordertooptimizeyourinsurancecoverage&insurancepremium,aswellasofferyoumorepersonalizedproducts?”See Accenture Consumer-Driven Innovation Survey: Playing to Win,Accenture,2013,https://www.accenture.com/us-en/consumerdriveninnovation.aspx

90EIOPA Opinion on sales via the Internet of insurance and pension products,EuropeanInsuranceandOccupationalPensionsAuthority,BoS-14/198,28January2015.

Unsolicited,personalisedoffersofinsurancearenotalwayswelcome.

0

20

40

60

80

100

EmergingAdvancedEmergingAdvancedEmergingAdvanced

No

To optimise your coverage

To optimise your premium

To optimise your products

Depends on the information Yes

Figure 17 Consumerscomfortwithinsurersaccesstoinformationonusage/behaviour

Survey question:Wouldyoubecomfortableforyourinsuranceprovidertoaccessinformationonyourusage/behaviourinordertooptimiseyourinsurancecoverage&premium,aswellasofferyoumorepersonal-isedproducts?

Regulatorshaveraisedanumberofconcernsaboutdigitallysoldlifeinsuranceproducts.

https://www.accenture.com/us-en/consumerdriveninnovation.aspx

https://www.accenture.com/us-en/consumerdriveninnovation.aspx


New challenges

Insurersmayalsoneedtokeepabreastofregulationswithrespecttotheuseoftechnologyincross-bordertransactions.Cross-bordersellingisbecomingeasierwithnewtechnologybuttherecouldbephysicalrestrictions,suchasarequirementtohavecustomerssignapolicyinpersonratherthanbye-signatures.Also,insurersmaynotbeallowedtostorecertaintypesofdatainlocationsoutsidetheirhomejurisdictions.Thiscouldbearisingconcernintheageofcloudcomputing:whereexactlydoesthecloudsit?

Broader cyber risksCurrently,thecloudisnotabigpartofinsurers’technologystrategybecauseofsecurityissueswithcloudusage.However,muchofthedatageneratedfromwearables,forexample,willbestoredinthecloud.Toutilisecloud-storeddata,insurerswilleitherneedtoadapttheirtechnologystrategiestoacceptahigherriskthresholdorformulatemoresecurewaysofaccessing/storing/usingthedata.

Additionally,customersoftendependonthewisdomofthemanyratherthanthatofexperts.Tomanagethisrisk,insurerscandevelopsociallisteningtoolsanduseplatformsthatofferpeer-to-peerunderstandingofhowtheyhavefared.ForexampleintheUS,AmericanFamilyhasinvestedinReviewTrackers,asoftwarethathelpsmanagecustomeronlinereviews.Ittracks,generatesandanalysesconsumer-generatedreviewsonallmajorreviewsites,enablinginsurerstolistencloselyandrespondpromptlytowhattheircustomersaresayingonline.91

Assmartphonesandtabletsfindwidespreaduseamongemployeesandagents,theybecomemorevulnerabletocyberattacks.Anadditionalriskcomeswiththebring-your-own-device(BYOD)movement,wherebyemployeesarepermissionedtousetheirowndevicesforbusinesspurposes,alongsideusageforprivatematters.Lifeinsurersneedtocloselymonitortherisksposedbythesedeviceswithoutcompromisingdeviceperformanceinthefield.OneexampleisNewYorkLifewhichispartneringwithanIsraelimobilethreatdefencestart-up,Skycure,toprovideprotectionforits35000mobiledevices.Skycureleveragesmassiveamountsofcrowddatatohelppreventormitigateattacksonmobiledevices.92

91SeeAmericanFamilyVentures’portfolioonhttp://www.amfamventures.com/92Skycure Secures $8 Million Series An Investment From Shasta Ventures for Mobile Threat Defense,

Skycure,24May2015,https://www.skycure.com/pr/skycure-secures-8-million-series-a-investment-from-shasta-ventures-for-mobile-threat-defense/.Crowddatainthiscasewouldbe,forexample,publiclyavailableinformationonmobilephoneactivitywhichcouldbeusedtomonitorgeneralortargetedcyber-attacksonmobiledevices.

Therecouldbealsoberegulatorygreyareaswithrespecttocross-bordersales.

Insurerswillneedtofitcloudusageintotheirtechnologystrategy,fordatafrom,forexample,wearables.

Insurersaredevelopingsociallisteningskillstomanagereputationalriskonsocialmedia…

…andsecuritystrategiesfortheBYODdevicesthatemployeesfavour..

http://www.amfamventures.com/


Anti-selectionOntheflipsideoftheinsurer-consumerrelationship,lifeinsurersaresusceptibletorisingrisksofanti-selection93(oradverseselection)asconsumersbuildmoreunderstandingoftheirownhealthstatuswiththedifferenthealthy-livingappsandhealthtestingdevicesavailableonthemarket.Withthespreadofgenetictesting,forexample,individualswhodiscovertheyareathigherriskofdisabilityordeathmaydisproportionatelyseektopurchaseinsurance,complicatingactuarialriskassessments.Theriskofanti-selectioncouldfurtherincreasegiventheanticipatedmoveofcontrolofpersonaldatafrombusinessestoindividualswiththeriseofaforementioneddatasharingplatformssuchasdigi.meandHumanAPI.94Thiscouldalsoraiseethicalquestions.Ifaninsurerdiscoversthatapolicyholderhasahighprobabilityoffacingmedicalcomplications,isthefirmdutyboundtoinformthepolicyholder.Whataretherisksofbeingwrong?Lifeinsurersarecurrentlydebatinghowtoapproachtheseissues.

Non-traditionalplayers:collaboratorsorcompetitors?

Non-insurancefirms,referredtohereasNTPs,couldbecollaborativepartnersorperhapscompetewithtraditionalinsurers.SomeNTPshaveaccesstohugeamountsofdataaboutindividualsgatheredfromconsumeruseofsmartphones,searchenginesandsocialmedia.Someareestablishedbrandnameswithlargeconsumerfollowings.TheNTPshavethepotentialtomonetisethedatatheyhaveonconsumersandtherebydisruptestablishedindustries.95

ThereareatleastfourareasoftheinsurancevaluechainwhereNTPscanhaveanimpact:Leadgeneration,datamonetisation,distributionanddirectunderwriting.UnderwritingiscurrentlyperceivedtobethemostchallengingtoNTPs.

93Theadverseimpactonaninsurerwhenrisksareselectedthathaveahigherchanceoflossthanthatreflectedintheapplicableinsurancerate.

94Notetoo,forexample,theEuropeancommissionisdraftingnewdataprotectionlegislationthatwillgiveconsumersmorerightstotheirdata.Publicationtargetis2016.

95Thisdiscussiononnon-traditionalplayersfocusesontheimpactoninsurersofinternetgiantsusingnewBig-Datatechnologies.Firmsinothersectors,however,suchastelecoms(particularlyintheemergingmarkets)andretailers,alsocanandalreadydoofferinsuranceservices.

Riskofanti-selectionduetogreaterconsumerknowledgeoftheirownhealthstatusisanotherconcernforinsurers.

NTPsarenon-insurancefirmsmakinganentryintotheprimaryinsurancemarket.

Theycanmakeanimpactinfourareas.

Table 3 RoleofNTPsintheinsurancevaluechain

Presence in the value chain Barriers to greater involvement

Lead generation Alreadyplayakeyrole(eg.AdWords) Allownewentrantsandsmallplayerswider

reachandabilitytocompete Insurersarekeycustomers

Dealwithinvestigationsintoanti-competitivepractices

Fearthatprivilegeddataaccessgivesunfairadvantageovercompetition

Monetisation of data Collaborativeratherthancompetitive. Hassignedpartnershipswithinsurerstomake

betteruseofsocialmedia

Dataprivacyconcerns Righttobeforgotten Falseprofilescreated

Distribution TakingfirststepsinP&C(eg.Alibaba,Overstock,GoogleCompare)

Lowpresenceinlifeinsuranceyet

Limiteduptake(stillsmallvolumes) Needforagencysupport Researchonline,purchaseoffline

Underwriting Unlikelytotakeonunderwritingrisk Businessmodelisthatofmiddlemen

Claimsdatanoteasilyaccessible Cannibaliseexistingbusinessmodel



New challenges

NTPswhichoperatesearchandsocialmediaplatformsalreadyplayaroleinleadgenerationinbothlifeandP&Cinsurance.Theirtargetedadplatforms,amainfeatureoftheirbusinessmodel,provideinsurerswithavehicletoreachcustomersdirectly.NTPswillcontinuetogenerateleadsforinsurers,ascompetitivepressurespushinsurerstospendheavilyonadvertising.

NTPsandinsurerscouldmakefurtheruseofBigData.Insurersarebuildingcapabilitiestomakebetteruseofsocialmediaformarketingandtoengagewithconsumers.Forexample,theyhavepartnershipstoaccesstheskillsandknowledgeofFacebookanalyticsandinnovationexpertsinthemobilefield.96Innovativeproductsarebeingdesignedspecificallyforsocialmedia.AninsurerinAsiaPacificoffersusersfreelifeinsuranceforuptoUSD10000onFacebookforsixmonths.97And,socialmediaplatformsnowownfitness-trackingappswhichcouldbeofferedtopolicyholders.98Collaborationcouldopenupseveralopportunitiesasinsurersbecomeawareofcustomer’slifecyclechanges,andaccordinglyrecommendproductsandvalue-addedservices.

Thiscouldtouchunderwriting,alsoassocialmediadatacanbeusedforcross-checkingpurposes.Forexample,ifaconsumerapplyingforano-medical-exampolicyclaimstobeanon-smokerandthereissocialmediaevidencetocounterthat,theconsumercouldbereferredforamedicaltest.However,itwilllikelybeawhilebeforethispracticeisrealitygivenexistinglimitationsinsettinguptechnicalsystemsthatcananalysethedatainpicturesorvideoscurrentlyavailablefromdifferentsocialmediaplatforms,andindeterminingthecontextinwhichtextphrasesareused.99Astechnologyanddataanalyticsimprovethough,lifeinsurersmaywellinitiatepilotschemesinwhichtheymakeuseofsocialmediatopredictindividuals’riskprofiles.100Atthatpoint,NTPswillbeanimportantsupplierofinformationandplayamuchlarger(ie,potentiallydisruptive)roleintheinsurancevaluechainthantheydotoday.

NTPscanalsoimprovedistributionininsurance,whetherthroughonlinepricecomparisonsites(eg,GoogleCompare)orbydirectsellingfrome-commerceplatforms(Alibaba,Overstock).Inrecentyears,thesefirmshavelaunchedplatformsthroughwhichconsumerscanreceivelivequotes,pickcoverageandtakeoutapolicy.SofarthishasbeenrestrictedtotheP&Csector.Thereisnoevidenceofthesameinlifeinsurance,probablyduetothemorecomplexnatureoflifeproducts,butitcouldhappeninthefuture.AsNTPsincreasinglybecomeafirstpointofcontactforconsumers,theycouldexpandtheirinfluencebeyondpricecomparisontoalsointroducefeaturessuchaspeer-to-peerratingssystems,bywhichconsumerscanratelifeinsuranceprovidersonaspectssuchascustomerserviceandsatisfactionwiththeclaimsprocessingexperience.101Thiswillincreasethetransparencyoftheindustry,posinganewreputationmanagementchallenge.

96AXA announces a strategic partnership with Facebook to further develop its digital, social and mobile footprint in France and globally,AXA,11April2014,http://www.axa.co.uk/newsroom/2014/media-releases/axa-announces-a-strategic-partnership-with-facebook-to-further-develop-its-digital-social-and-mobile-footprint-in-france-and-globally/.

97M.Gray,“InsurergivesawayfreeinsuranceonFacebook”,Insurance Business New Zealand,8June2015.

98MovesisafitnessappownedbyFacebookthatcanbeusedbyVitalitymemberstotracktheirprogressandearnpoints.ForalistofappsanddevicesthatVitalitymemberscanchoosefrom,see:http://www.pruhealth.co.uk/vitality/partners/vitality-activity-tracking/.

99Digital Underwriting and Fulfilment, Latest Trends in Digital Underwriting,TheDigitalInsurerandSwissRe,2014,pp9-14,http://www.the-digital-insurer.com/exclusive-digital-underwriting-fulfilment-report-produced-digital-insurer-swiss-re/.

100In2015SocialIntelligence,aproviderofsocialmediariskassessmenttoolsanddata,beganofferingaSocialMediaRiskScoringsolutionforinsurers.See“SocialIntelligenceLaunchesSocialMediaRiskScoringforP&CInsurers”,Business Wire,22April2015,http://www.businesswire.com/news/home/20150422005849/en/Social-Intelligence-Launches-Social-Media-Risk-Scoring.

101AsGoogleCompareisalreadydoingintheP&Csector.SeeD.Jergler,“AgentSupport,RatingsAddedtoExpandingGoogleCompare”,Insurance Journal,5May2015.

NTPscanmakeuseoftheirproximitytocustomerstogenerateleads…

…andopendoorsthroughnewanalyticsandinnovationexperts.

NTPscouldbecomeamuchstrongerlinkinthedatasupplychain,andevenvalidatedataintheunderwritingprocess

DistributioninP&ChasalreadybeeninfiltratedbyNTPs,butthesameisnottrueinthelifesector…yet.

http://www.businesswire.com/news/home/20150422005849/en/Social-Intelligence-Launches-Social-Media-Risk-Scoring

http://www.businesswire.com/news/home/20150422005849/en/Social-Intelligence-Launches-Social-Media-Risk-Scoring


Peer-to-peerinsuranceandhybridmodelssuchasFriendsurance102areunlikelytodevelopasaviablealternativetotraditionallifeinsurance.Thesemodelsworkbestinhighlycommoditisedproductlines,suchasmotor.Lifeinsurancecontractsarefundamentallydifferentduetotheircomplexity,multi-yearnature,potentiallylargeclaimsandtheneedfordiversificationthroughasignificantnumberofcustomerstomaketheinsuranceviable.

NTPscouldalsoenterdirectunderwritinginlife,buttheyareunlikelytodosointhenearfuture.NTPs’maincompetitiveadvantageisaccesstodata,andexpertiseindataanalytics,whichcanhelpinunderwritingbutisprobablyinsufficientforaccuratepricingoflifeinsurancepolicies.Theycannoteasilymatchtheinsuranceindustry’sknowledgeofcausalitywithouttheclaimsdataandhealthinformationhistorythatinsurerspossess.Thus,NTPsarebestpositionedtohelpinsurersindistributionandsharetheprofitsofbetterriskselectionfromcustomersegmentation.

ThereisalsoaquestionofstrategicfitofunderwritingforNTPs.Theyhavebuiltplatformsthatallowthemtofunctionasmiddlemen,connectingbuyerswithsellersandmonetisingthatinteraction.Thisremainstheirdominantrevenuestream,whichtheymaybereluctanttounderminebygoingintonon-coreareas.Thefollowingtableoutlinestheexistingareasofinvolvementofafewcompaniesalreadyinvolvedintheinsurancemarketandtheirpotentialfutureroleininsurance.Theanalysisisbasedonpubliclyavailableinformationfrommediaarticles,journalsandcompanywebsites.

102Friendsurancehasdevelopedapeer-to-peerinsuranceconcept,whichrewardssmallgroupsofuserswithacash-backbonusattheendofeachyeartheyremainclaimless.Seehttp://www.friendsurance.com/.

Peer-to-peermodelswillnotbeviableinlifeinsurance.

NTPscouldgointodirectunderwritinginlifeinsurance,butareunlikelytodoso.

Theircompetitivestrengthistoactasdatabrokers,connectinginsurancebuyerswithsellers.


New challenges

Table 4 Non-traditionalplayersandtheircurrentandpotentialfutureinvolvementininsurance

Current role in insurance Potential future role in insurance

Google Playsakeyroleinleadgeneration.“Insurance”isoneofthemostexpensiveofallitskeywords.103PlaysroleinP&CdistributionthroughGoogleComparelaunchedintheUK(2012)andUS(2015).Nolifeinsurancesupportasyet.104

Couldenterthemarketwitharegulatedinsurerandleverageitssearchdataforimproveddistributionandunderwriting.

Facebook Offersinsurersdedicatedresources,includinginnovation&analyticsteamstodevelopbrandpresenceonFacebook,particularlymobile.105InsurershavebegunusingFacebookasadistributionchannel.Facebookhasalsoboughtafitness-trackingappstartup(Moves),whichinsurersmayrecommendtopolicyholders.106

Couldleveragegroupbuyingpower,especiallyforsimpletypesofinsurance.Overtimecouldgainaccesstoactivitydatafromthefitnesstrackingappsthatitowns.Hasbeguntoofferadstoconsumersbasedontheiractivitiesonother,non-Facebookonlineportals.107

Apple HealthKitisApple’sconnectedhealthhub.Collateshealthandfitnessdatafromvariousappsandprovidesuserswithanoverviewoftheirhealth.108

InsurerscouldsupportHealthKitandAppleWatchfordatacollectionandmaysubsidisetheWatch.Watchcouldbeusedforremotemonitoringofhealthormoreaccuratepricingoflifeandhealthinsurancerisks.

Amazon Amazonhasgooddataonactualandintendedpurchasingbehaviouronmillionsofcustomers.Smallpresenceinadvertisinghistorically,butisnowbuildinganadnetworkthatreachesontomanyothersites.109

Couldgiveinsurersdirectaccesstoinformationaboutindividuals’browsing,purchasing,andproductreviewhistories,butthiscurrentlyseemsunlikely.Instead,couldcreatetargetaudiences,e.g.peoplewhorecentlypurchasedorganichealthfoods.AninsurercouldthenuseAmazon’stechnologytobidfortheabilitytoshowadstoapersoninthatcategory.

Alibaba AntFinancial(affiliateofAlibaba)hassetupanonlineinsurer(ZhongAn),withTencent(asocialmediafirm)andPingAn.ZhongAnunderwritesrisksandalsomanagespolicies.110AlsohasZhaoCaiBao,apeer-to-peerplatformthatallowsSMEsandindividualsaccesstoloansanduniversallifeinsurance.

Itsintegratedplatformisakeycapability.Alipay(onlinepaymentplatform)tomoveintomedicalcareandpharmabyleveragingitsmobileplatformandenablinguserstoregisterforconsultations,monitorqueuesandconductpayments.Canselllowcostmicro-insurance.Distributioncostswouldbeminimal.111

Overstock Offersapricecomparisonserviceforautoandhomeownersinsurance,aswellascommercialpoliciesforsmallbusinesses.112

Seesinsuranceaspartofextendedofferings.Slowuptakeinthecourseoffirstninemonths.Onlyabletosellasmallnumberofpoliciesin2014.113


103 L.Kim,“HowDoesGoogleMakeItsMoney:The20MostExpensiveKeywordsinGoogleAdWords”,wordStream.com,http://www.wordstream.com/articles/most-expensive-keywords

104 CBInsights“Google’sRisingInvestmentsandPartnershipsinInsuranceTech”,cbinsights.com,21October2015,https://www.cbinsights.com/blog/google-insurance-tech-investments/

105 AXAannouncesastrategicpartnershipwithFacebooktofurtherdevelopitsdigital,socialandmobilefootprintinFranceandglobally,AXA,11April2014,http://www.axa.co.uk/newsroom/2014/media-releases/axa-announces-a-strategic-partnership-with-facebook-to-further-develop-its-digital-social-and-mo-bile-footprint-in-france-and-globally/

106 MovesjoinsFacebook!,Moves,24April2014,https://www.moves-app.com/press107 MakingAdsBetterandGivingPeopleMoreControlOvertheAdsTheySee,Facebook,12June2014,http://newsroom.fb.com/news/2014/06/making-ads-

better-and-giving-people-more-control-over-the-ads-they-see/108 HealthKitallowsappsthatprovidehealthandfitnessservicestosharetheirdatawithApple’sHealthappandwitheachother.SeeHealthKithomepageon

https://developer.apple.com/healthkit/109 L.O’Reilly,“Amazonisworkingwiththeadvertisingindustrytomakealladsonthewebbetter”,BusinessInsider,24March2015,http://uk.businessinsider.

com/amazon-dan-wright-interview-ad-week-europe-2015-3?r=US&IR=T110 AsiaInsuranceReview“China:OnlineinsurerZhongAnraisesUS$935mln”,asiainsurancereview.com,12June2015,http://www.asiainsurancereview.com/

News/View-NewsLetter-Article?id=32985&Type=eDaily111 ForadetailedanalysisofAlibaba’sinvolvementininsurance,see:InsuranceandTechnologyInsight:TheEmergingRoleofEcosystemsinInsurance,Morgan

StanleyandBCG,23March2015,pp20-21,https://www.bcgperspectives.com/content/articles/insurance-technology-financial-institutions-disruptive-force-ecosystems/

112 ForanoverviewofOverstock’sinsuranceofferings,seehttp://www.overstock.com/insurance113 AccordingtoOverstock’sCEOPatrickByrne,itsecommerceplatformsoldonlyafewthousandpoliciesin2014,or“theequivalentofasmall-townbrokerage”.

SeeC.Dougherty,“InsuranceviaInternetIsSqueezingAgents”,NewYorkTimes,18January2015,http://www.nytimes.com/2015/01/19/technology/insurance-via-internet-is-squeezing-agents.html?ref=business&_r=2

http://www.wordstream.com/articles/most-expensive-keywords

http://www.wordstream.com/articles/most-expensive-keywords

https://www.cbinsights.com/blog/google-insurance-tech-investments/

https://www.cbinsights.com/blog/google-insurance-tech-investments/

http://newsroom.fb.com/news/2014/06/making-ads-better-and-giving-people-more-control-over-the-ads-they-see/

http://newsroom.fb.com/news/2014/06/making-ads-better-and-giving-people-more-control-over-the-ads-they-see/

https://developer.apple.com/healthkit/

http://uk.businessinsider.com/amazon-dan-wright-interview-ad-week-europe-2015-3?r=US&IR=T

http://uk.businessinsider.com/amazon-dan-wright-interview-ad-week-europe-2015-3?r=US&IR=T

http://www.asiainsurancereview.com/News/View-NewsLetter-Article?id=32985&Type=eDaily

http://www.asiainsurancereview.com/News/View-NewsLetter-Article?id=32985&Type=eDaily

https://www.bcgperspectives.com/content/articles/insurance-technology-financial-institutions-disruptive-force-ecosystems/

https://www.bcgperspectives.com/content/articles/insurance-technology-financial-institutions-disruptive-force-ecosystems/

http://www.nytimes.com/2015/01/19/technology/insurance-via-internet-is-squeezing-agents.html?ref=business&_r=2

http://www.nytimes.com/2015/01/19/technology/insurance-via-internet-is-squeezing-agents.html?ref=business&_r=2


Conclusion

Thelifeinsurancesectorissetforfundamentaltransformation,broughtaboutbytechnologicaladvancementsandnewdigitaldataanalytictechniques.Theimpactisexpectedtospantheentireinsurancevaluechainfromproductdevelopmentandunderwritingthroughtodistribution,servicesandclaims.Todate,thesectorhasbeenslowtoadoptnewtechnologies,butthisischanging.

Therapidspreadofinternet-enableddevicesanduniversalconnectivityhasresultedinachangeinconsumerbehaviourandexpectationsacrossallindustries,particularlyamongtheyoungergenerations(ie,futurecustomers).Thedigitalagehasalsobroughtanexplosionofheterogeneousdatafromdifferentsourcesandplatforms,whichissomethingthatlifeinsurerscanutilisetobroadentheirreachandalsopushtheboundsofinsurability.However,toharnessthepowerofdigitalcapabilitiestobeabletoidentifytrendsearly,gaininsightsintoconsumerpreferencesandmakeoperationsmoreefficient,theywillneedtoinvestinBigDataandpredictiveanalytics.

Technologywillfundamentallychangethebusinessofinsurance.Toremaincompetitiveinthedigitalage,lifeinsurerswillneedtoreconfiguretheirtraditionalITsystemsintoopeninnovationplatformsinordertoaccessthenewdatasources,obtainaunifiedviewofthecustomer,andofferaconsistentexperienceacrossconsumertouchpoints.Theywilldowelltokeeptrackofongoinginnovationbypartneringwithestablishedand/orstart-uptechnologyvendors,andtakelessonsfromhowotherindustriesmakeuseofthenewtoolsandemergingcapabilities.Importantly,insurersshouldalsofocusonsourcingspecialisttalent.

Newtechnologies,however,alsobringnewchallenges.Lifeinsurerswillneedtoimplementnewriskmanagementprocedures,importantlyaroundconsumerdataprotection.Theywillalsoneedtomonitorandadapttoregulatorychangeswithrespecttotheuseofdigitaldataandanalyticsinunderwriting.Theriseofnon-traditionalplayersisanotherdevelopmentlifeinsurersneedtorespondto.Thenewentrantspresentopportunitiesformutuallybeneficialpartnerships,buttheycouldalsoeventuallybecomedirectcompetitors.

Theentirelifeinsurancevaluechangewillbeimpactedbytechnologyanddataanalytics.

Thedigital-ageconsumerhasdifferentexpectations,whichlifeinsurerscancapitaliseon…

…byinvestinginafundamentalreworkoftheiroperatingandITsystems,andspecialisttalent.

Lifeinsurerswillalsoneedtoimplementnewriskmanagementprocedures,andrespondtotheriseofnon-traditionalindustryplayers.


Recentsigmapublications

2015 No1 Keepinghealthyinemergingmarkets:insurancecanhelp No2 Naturalcatastrophesandman-madedisastersin2014: convectiveandwinterstormsgeneratemostlosses No3 M&Aininsurance:startofanewwave? No4 Worldinsurancein2014:backtolife No5 Underinsuranceofpropertyrisks:closingthegap No6 Lifeinsuranceinthedigitalage:fundamentaltransformationahead

2014 No1 Naturalcatastrophesandman-madedisastersin2013:largelossesfromfloodsandhail;HaiyanhitsthePhilippines

No2 Digitaldistributionininsurance:aquietrevolution No3 Worldinsurancein2013:steeringtowardsrecovery No4 Liabilityclaimstrends:emergingrisksandreboundingeconomicdrivers No5 Howwillwecare?Findingsustainablelong-termcaresolutionsforanageingworld

2013 No1 Partneringforfoodsecurityinemergingmarkets No2 Naturalcatastrophesandman-madedisastersin2012: AyearofextremeweathereventsintheUS No3 Worldinsurance2012:Progressingonthelongandwindingroadtorecovery No4 Navigatingrecentdevelopmentsinmarineandairlineinsurance No5 Urbanisationinemergingmarkets:boonandbaneforinsurers No6 Lifeinsurance:focusingontheconsumer

2012 No1 Understandingprofitabilityinlifeinsurance No2 Naturalcatastrophesandman-madedisastersin2011: historiclossessurfacefromrecordearthquakesandfloods No3 Worldinsurancein2011:non-lifereadyfortake-off No4 Facingtheinterestratechallenge No5 Insuringever-evolvingcommercialrisks No6 Insuranceaccountingreform:aglasshalfemptyorhalffull?

2011 No1 Naturalcatastrophesandman-madedisastersin2010: ayearofdevastatingandcostlyevents No2 Worldinsurancein2010 No3 Stateinvolvementininsurancemarkets No4 Productinnovationinnon-lifeinsurancemarkets:wherelittle“i”meetsbig“I” No5 Insuranceinemergingmarkets:growthdriversandprofitability

2010 No1 Naturalcatastrophesandman-madedisastersin2009:catastrophesclaimfewervictims,insuredlossesfall

No2 Worldinsurancein2009:premiumsdipped,butindustrycapitalimproved No3 Regulatoryissuesininsurance No4 Theimpactofinflationoninsurers No5 Insuranceinvestmentinachallengingglobalenvironment No6 Microinsurance–riskprotectionfor4billionpeople

2009 No1 Scenarioanalysisininsurance No2 Naturalcatastrophesandman-madedisastersin2008:

NorthAmericaandAsiasufferheavylosses No3 Worldinsurancein2008:lifepremiumsfallintheindustrialisedcountries–strong

growthintheemergingeconomies No4 Theroleofindicesintransferringinsuranceriskstothecapitalmarkets No5 Commercialliability:achallengeforbusinessesandtheirinsurers

2008 No1 Naturalcatastrophesandman-madedisastersin2007:highlossesinEurope No2 Non-lifeclaimsreserving:improvingonastrategicchallenge No3 Worldinsurancein2007:emergingmarketsleadingtheway No4 Innovativewaysoffinancingretirement No5 Insuranceintheemergingmarkets:overviewandprospectsforIslamicinsurance

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