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IBM Global Business Services“Conocimiento y Análisis del Cliente, basado en lasPerspectivas del Mercado Local de Seguros”Driving Customer Analytics Based on Local CustomerPerspectives on InsuranceJohn Medellin, IBMPartner Global Business ServicesDavid Notestein, IBMFinancial Services Sector lead for IBM’sInstitute for Business ValueMéxico D.F., Mayo 19, 2009 2009 IBM Corporation

IBM Global Business ServicesSummaryInsurers need to account for the varied attitudes, values andbehaviors in today’s markets to reach tomorrow’s customersSummary of Findings Overcoming the animosity issue is of central importance Customer price sensitivity is a convenient excuse for inaction Product innovation is of less importance than clarity and honesty A single marketing strategy is unlikely to work because THE uniformcustomer does not existCustomer centricity and customer value mean askingwhat the customer expects from the insurer2Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesHow customers differ - cultureCustomer types are spread fairly evenly when usingconventional demographic segmentation criteriaCustomer types by age18 - 29 years1930 – 39 years1940 – 49 years212750 – 59 years212360 80%100%Customer types by incomeVery low income20Low Income20Lower middle class20Upper middle class1618Very high income0%392672922High IncomeSource: own survey data, n 24002926232312111417283091824819242227291810% 20% 30% 40% 50% 60% 70% 80% 90% 100%Support-seekingindividualistsProduct optimizersUninterested minimalistsPrice-sensitive tional segmentation criteria do not reflect thedifference in customer needs described by typesDriving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesHow customers differ - cultureCultural differences across the globe lead to a widely divergentspread of the customers types per country125529MEX18136316BRA13Support-seeking individualistsProduct optimizersUninterested minimalistsCHI17135524Price-sensitive analyzersRelationship-oriented traditionalistsARG0%20%Source: own survey data Latin America, n 1600441363040%60%24980%100%Considering the huge difference in customer needsdescribed by types, a single global marketingstrategy is highly unlikely to workDriving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesHow customers differ – Latin AmericaFor Latin America, price is not even in the top ten – meetingindividual needs in a convenient way is consumer's priorityAttitude or value factorLatin America responseTailor made productsDifference to averageU.S. Europe 31%58%Large selection of products / servicesComprehensive insurance protection forall risksFlexibility of insurance coverage 22%70% 18%80% 12%79%Support in preventing accidents 24%82%Availability "around the clock" 29%85%Local proximity of insurance company 32%65%Availability "around the clock" 29%85%Competent / w ell trained agents 5%76%Agent w ho has time for my requests 10%81%Trusted relationship w ith my agent74%All insurance w ith 1 company75%Agent of a similar age / education 15% 13% 23%38%Low premiums- 7%64%0%20%40%60%80%100%-20%0%20%40%Source: own survey data Latin America, n 160055Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesHow customers think insurance – price and valueAttitudes – MexicoInsurance against all risks1189Support in preventing accidents1288Internet insurance for 20% reduction in premiums20Submit data for additional services802377All insurance with 1 company2674I know exactly what I need267429Submit data for lower premiumsSystematical comparison of insurances712674All insurance companies the same3664Treat all customers identical3763Tailor made products30Trust in insurance companies7043As little as possible657590%6don't agreeagree20%4140%60%Driving Customer Analytics Based on Local Customer Perspectives on Insurance80%100% 2009 IBM Corporation

IBM Global Business ServicesHow customers think insurance – price and valueValue – Mexico909Honesty and trustworthinessTransparent and clear documentation1087Availability "around the clock"1187Fast and uncomplicated claims procedures899Agent who has time for my requests1385Comprehensive insurance protection for all risks1485Flexibility of insurance coverage1484Service-oriented customer service1483Competent / well trained agents1582Trusted relationship with my agent1681Large selection of products / services7720Agent of a similar age / education43400%7high value7224Low premiumssome value7422Local proximity of insurance company7little value20%40%60%Driving Customer Analytics Based on Local Customer Perspectives on Insurance80%100% 2009 IBM Corporation

IBM Global Business ServicesBehavioral trends - informationMexican consumers are quite on the Latin American average,preferring personal over anonymous informationRecommendation family /friends41Recommendation insurance agent545334524950Price comparison via Internet33Recommendation bank14Offers in advertising267Recommendation independent broker190834262620MEX838312911Offer from a vehicle dealer / estate agentSource: own survey data, n 4400666540LA Average6080EU US AverageIn Latin America, advertising actually seems to belistened to, in contrast to Europe and the UnitedStates.Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesMarket dynamicsOur data show that customers are perfectly willing to accept newvalue propositions if they seem reliable, fair and innovativeOvercoming the gapscustomer quotes"In life, something’s boundto happen, so peopleshould be able to rely ontheir insurance."trusttransparencytechnology9"Why can't they come upwith something simple andclear, written plainly.""Online would be good.You can pick and choose.See what’s there."resultsinsurance is reliableinsurance is fairinsurance is innovativeDriving Customer Analytics Based on Local Customer Perspectives on Insurancecustomers trustwithout knowingeverythingcustomers makeinformed decisionscustomers are able to“co-create” insuranceservices 2009 IBM Corporation

IBM Global Business ServicesMarket dynamicsChanging market dynamics – questions to ask yourself: Do you really know your customerstoday and how they are changing? Are you investing in a climate of trust andtransparency, internally and externally? How are you preparing your company for a futureof technological, economic, and cultural change? Do you have a vision for the future that is basedon quality data and analysis?10Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesDriving Customer Analytics Based on Local Customer Perspectives onInsuranceCustomer Analytics as a powerful tool 2009 IBM Corporation

IBM Global Business ServicesWhy is this key to Mexico?Mexican Financial Institutions Can Offer More Services Than Others:AFORE/RETIREMENTTRADITIONALINSURANCEAFORE PENSION DATA ISRESTRICTED TODAY1 PENSIONS2 IRA3 SAVINGS PLANS4 OTHER1 TDA/DDA2 LOC/CR CARD3 COMM LENDING4 MTGE/PERSONAL5 CURRENCY DESK1 LIFE2 AUTO3 P&C4 MEDICAL5 HYBRIDSPRIVATE1 CORRESPONDENT/FOREIGN3 TRUST / ESTATE5 TRADESPROFIT IS HIGHERHERE2 PFP4 HYBRIDS6 PLACEMENTSThere are Numerous Offering Points to Entities Needing Financial Products !!(WE JUST NEED TO KNOW WHO TO TARGET WITH WHICH PRODUCT AND WHY)12Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business Services1st Prob: Getting to a single Party or EntityUnstructured customer data camouflages buyers: Many data stores and accounts, no way to trace Acquisitions, life events, changes in customers Massive, financial institutions have more information than just about anyone !!Who’s right?Normalized Data Is The Only Way To Go True definition of reality Solid foundation Can be used in a predictive manner (we can rely on it)13Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesGetting to unique through normalizationUniqueness is achieved and then enters into a stage of deterioration . We will be there for one instant and then the proverbial change will happen Running it all again is infeasible (machines, time, people)IBM Products-DB2 UDB Server-WCC-WAS-DataStageKey isUCRHomogeneousUnique ClientNormalizationInclude:Algorithms-Inner join matching-Phonetic similarity pairing-Math equation and predictionUCRUCR: Unique Client Record It is not a new concept, it is core to financial institutions The key is the ability to regenerate and audit that entity through algorithms that continuously work ondata integrity and identify discrepancies between what is there and what is detected This integrity program is effectively possible through the deployment of machine efficient searchalgorithms that are deployed at every stage in the UCR Update/Replace processUCR INTEGRITY IS A LIFE CYCLE MANAGEMENT PROCESS !!!14Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesThe Importance Of Reliable DataReliable data is critical for customer analytics: Data at the UCR level must be a valid representation of source systems and transactions During the ETL process, data is typically enhanced and augmented, these rules should approach theenrichment process correctly This cycle of cleansing and enhancing is repetitive and can be enhanced by statistical analysis in orderto confirm reliability Reliability is a mathematical concept and is usually expressed as confidence that a value is within agiven rangeLegacyUCRExtract TransformAnd Load (ETL)DetermineReliabilityReliability can be confirmed by checking expected vs actual results Sample data can be validated vs legacy to determine reliability A critical task is how the sample is drawn from the population (or sub population) Under/over estimating errors can lead to over/under sampling Several tests exist for data sampling based on level of measurement 15Chi squared and anova for nominal/ordinalMultivariate correlation and/or regression for interval/ratioThe ultimate objective is to determine the degree of confidence in the data.Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesInternal data must be enhanced to be usefulInternal data is valid but must be enhanced It is accurate, auditable, reliable but not predictive, static and it erodes quickly It must be augmented with external data and statistical analysisEnhancedCustomerDatabaseHomogeneousUnique ClientiSearchBureauOtherAlgorithmsAnalyze to determine predictors:-Internet and external data-Empirical patterns-Statistical methodsThe methods for enhancement are varied, we have encountered that the following work best: Internet search algorithms and external statistical databases (e.g., mean income by zip code) Empirical analysis algorithms (pattern analysis, customer target profile) Statistical methods: Chi-square, ANOVA and Multivariate Regression to determine predictive characteristics16Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesUse Enhanced Data To Gain Market ShareEnhanced data’s real contribution is in gaining market share through cross selling: Setting channel management strategy Developing lead generation through predictive analysis Sales productivity objectives and realistic target settingMARKET SEGMENTATION LEADS TO CUSTOMER STRATEGYCUSTOMER STRATEGY DRIVESLEAD TYPE AND POTENTIAL SALECURRENTNEWWEBCONTACTCENTERFACE TOFACELeadProfileNEWWe are most productive when we reach our customer through the appropriate channel: Market segmentation drives customer classification and ultimately individual customer strategy The objective is to predict, by customer what additional products or services they might purchase Once that has been achieved we can generate a more qualified lead Higher quality leads translated into higher pipeline yield and ultimately increase our market share17Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business ServicesCustomer Analytics Implementation Roadmap Normalize Data– Consolidate and cleanse– Establish data audit functionNormalizeNormalize Enhance Data– Integrate external data– Conduct empirical analysisEnhance– Conduct statistical analysis Use Data to Gain Market Share– Segment market and drive customer analysis– Establish leads and targetsGain– Develop market acquisition program Establish Sustainability– Define required yield and Customer LTV objectivesSustain– Establish customer analytics function– Define and implement Management Systems Monitor Value– Establish value checking strategyMonitor– Monitor via customer feedback18Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business Services¿Preguntas?19Driving Customer Analytics Based on Local Customer Perspectives on Insurance 2009 IBM Corporation

IBM Global Business eGermanTraditional ChineseThaiKoreanSimplified ChineseJapanese20Driving Customer Analytics Based on Local Customer Perspectives on InsuranceTamil 2009 IBM Corporation

And Load (ETL) Determine Reliability Legacy UCR Reliability can be confirmed by checking expected vs actual results Sample data can be validated vslegacy to determine reliability A critical task is how the sample is drawn from the population (or sub population) Under/over estimating errors can lead to over/under sampling