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1、Insurance PracticeInsurer of the future:Are Asian insurers keeping up with AI advances?AIs potential for competitive advantages remains largely unrealized in the Asian insurance industry.There is a framework for success:invest in AI not discretely but across the value chain.May 2023 zf L/Getty Image

2、sby Violet Chung,Pranav Jain,and Karthi PurushothamanAs the insurance industry undergoes a seismic,tech-driven shift,1 AI continues to push the evolution of how insurers make significant service and operational gains.Indeed,McKinsey estimates that AI technologies could add up to$1.1 trillion in annu

3、al value for the global insurance industry:approximately$400 billion could come from pricing,underwriting,and promotion technology upgrades and$300 billion from AI-powered customer service and personalized offerings.2While most large insurers are on the path to AI-enabled personalization at scale,3

4、the industry remains at an early stage of transformational AI adoption.For most Asian insurance leaders,traditional organizational structures with multiple intermediaries and limited in-house tech and data resources make it difficult to visualize,let alone quantify,the potential benefits of investin

5、g more broadly in AI.This matters because cross-functional investment in AI can be game-changingand it will increasingly become a source of competitive advantage.AI adoption has more than doubled in the past five years,and investment in AI is increasing across industries.Among 1,492 respondents to a

6、 December 2022 McKinsey Global Institute survey,those who reported the most significant gains from AI adoption 20 percent or more EBITtend to employ advanced AI practices,use cloud technologies,and spend efficiently on AI,and they are more likely than others to engage in a range of AI risk mitigatio

7、n efforts.4The challenge for most insurers is to determine the optimal path from where they are now to where they need to be when it comes to AI maturity and enterprise-wide integration.Drawing on McKinseys AI maturity assessment model,in this article,we both outline how Asian insurers can assess th

8、eir readiness for AI and offer a road map to becoming an AI-powered insurer of the future,realizing gains in profitability,agility,at-scale personalization,and innovation.The basis of this framework is a layered approach to investment in AI across four focus areas:engagement,AI-powered decision maki

9、ng,core tech and data,and organization and operations(Exhibit 1).AIs potential for insurers:Benchmarking success The four layers of our integrated AI-capability-stack framework for insurance encompass front-,middle-,and back-office functions.Just as these functional areas are essential to and interr

10、eliant within an organization,the layers of the framework are mutually supportive:together,they form a robust structure that benefits internal and external stakeholders.The global companies setting the benchmarks for AI maturity and capacitysuch as Google,Netflix,Tencent,and Uberillustrate the poten

11、tial gains that could be realized by insurers that integrate AI holistically across their organizations.Reimagined engagement layerA reimagined engagement layer employs AI tools and solutions to create digital-ready engagement and distribution channels that can help provide customers with a consiste

12、nt,personalized experience.To envision leading-edge personalization at scale,consider Netflix.Each Netflix user has a distinct,customized view of available contenton the platform as well as in emailsthat reflects their interests and becomes more extensive,targeted,informative,and engaging over time.

13、AI-powered decision-making layerAI and advanced data-and-analytics capabilities can augment complex decision making,allowing businesses to automate repetitive tasks,analyze significantly more data,increase processing speed and accuracy,and create predictive models to improve procedures and enhance p

14、erformance.Uber Technologies exemplifies the leading edge in AI-enabled predictive analytics,bridging the gap between ride demand and driver supply by using historical ride data and key metrics to ensure every 1 Ramnath Balasubramanian,Ari Libarikian,and Doug McElhaney,“Insurance 2030The impact of A

15、I on the future of insurance,”McKinsey,March 12,2021.2 “The executives AI playbook,”McKinsey,accessed March 20,2023.3 “How personalization at scale can invigorate Asian insurers,”McKinsey,December 2,2022.4 “The state of AI in 2022and a half decade in review,”McKinsey,December 6,2022.2Insurer of the

16、future:Are Asian insurers keeping up with AI advances?user of the Uber app has access to a ride within their expected timeframe.Core tech and data layerModernized core tech helps deliver complete,high-quality,real-time data for advanced decision making,facilitating a seamless customer and stakeholde

17、r experience.It provides the ability to integrate with multiple third-party platforms for data and intelligence.Tencent,a leading Chinese multinational technology and entertainment conglomerate,has been using its advanced-API platform in its WeChat app to integrate data and decisions,thus providing

18、a seamless,efficient,integrated service experience for more than one billion monthly active users in China.The initiative Exhibit 1Web 2023AI insurer of the futureExhibit 1 of 31AI for IT operations.There are four layers to the full-stack AI capability that will defne the AI-enabled insurer of the f

19、uture.McKinsey&CompanyReimagined engagementIntelligent products,tools,and experiences Advanced analytics Customer acquisitionNatural-language processingVoice script analysisVirtual agents or botsComputer visionFacial recognitionRobotics Behavioral analyticsUnderwritingServicing and engagementRetenti

20、on and cross-and upsellingClaimsConversational AIDigital marketing and personalization Digital channelsHybrid agencyBancassuranceDirect-to-consumer distributionOmnichannel enablementPartnerships and ecosystems(eg,integrated life and health propositions)Smart service and operations(eg,conversational

21、AI-enabled services,predictive customer experience,ZeroOps)ProftabilityAt-scale personalization Omnichannel experience Speed and innovationDigital marketing and personalization AI-powered decisioningCore technology and data modernizationPlatform operating modelIntelligent infrastructure(eg,AIOps1 co

22、mmand,hybrid cloud set up)Modern API architectureTech-forward strategy linked to businessHollowing the core(core modernization)Cybersecurity and control tiersCore tech and data Autonomous“biz tech”teams Agile way of working Remote collaborationModern talent and hiringCulture and capabilitiesVendor a

23、nd partner managementOrganization,operating model,and ways of workingAI-enabled insurer of the future3Insurer of the future:Are Asian insurers keeping up with AI advances?significantly expanded WeChats proposition by being more personalized and providing context-specific offers across payments,retai

24、l,and its social networking and chat functionality.Organization and operating model layerThis crucial layer enables the innovation,agility,and flexibility needed to harness AI-powered capabilities.Cross-functional teams,new talent and skills,flat organization structures,and shared goals have enhance

25、d impact from AIparticularly in aiding frontline adoption and solving crucial frontline decision problems.In Googles relatively flat and cross-functional organization structure,small project teams operate in an agile manner with shared goals and empowered decision making,and talent and skill are val

26、ued over seniority.All are vital to Googles reputation as an AI-driven organization and its continued product innovation and growth.AI readiness for Asian insurers:Building layer depth and strength While some insurers have achieved select wins by implementing AI solutions within individual layers,th

27、e transformation required to achieve the full-stack capability that powers the companies mentioned above remains elusive in insurance.Often,the problem insurers face is identifying where to start.The first step is to determine how AI can support the organizations strategic goals and then assess the

28、organizations current state of AI readiness across each of the four layers.A simple scoring methodology can help insurers identify their readiness on a scale from one to five for each layer,with stage five signifying the highest level of AI maturity(as articulated in this article).Insurers with in-d

29、epth insight into their AI readiness are better equipped for the next step:creating a road map for implementing AI solutions across the front-,middle-and back-office functions of their companies.This road map allows company leaders to calibrate expectations as well as the resources,time,and investme

30、nts needed.Consider a four-phased plan to implement AI in underwriting,for example(Exhibit 2).Value is added in each phase,but it increases dramatically in the third and fourth phases,when greater AI capacity helps enable continuous,personalized engagement and prescriptive actions to support better

31、outcomes for customers.While the path to becoming an AI-powered insurer of the future will vary based on an organizations stage of readiness in each layer,the end goal remains the same:a more innovative,profitable,digital-forward organization that meets and anticipates customers evolving needs with

32、highly personalized,omnichannel experiences.Reimagining the engagement layer Leaders in other industriesGoogle,Netflix,and Uber,for examplehave achieved stage-five AI maturity within their engagement layer while most leading insurers are at or below stage-three maturity.Some Asian insurers have used

33、 micropersonalization based on consumer personas to realize gains in overall engagement;nonetheless,most have fallen short of employing dynamic,one-to-one customer targeting to create the personalized,consistent,omnichannel customer experience that characterizes mature AI-powered engagement.In other

34、 words,personalization at scale.At-scale personalization.Personalization underpins all facets of a reimagined engagement layer and is central to every interaction between products and customers.Creating exceptional customer experiences dominates senior-management agendas,and insurers continue to wor

35、k toward building personalization at scale to gain a better understanding of customer behavior and offer customers advice on the products best suited to their needs.AI is now being used to generate highly personalized offerings across industries,tailored to customer specifics such as location,indust

36、ry,age,and financial history.Customer interactions are also personalized using demographics and past interactions.Most large insurers are halfway along the path of achieving personali-4Insurer of the future:Are Asian insurers keeping up with AI advances?zation at scale,5 prioritizing key metrics suc

37、h as the following:Measurement and attrition.Attribute click-through rates,conversion rates,and other metrics to different digital channels,and measure improvement to help identify customer preferences and drive personalization to serve the customer.Omnichannel breadth and flexibility.Build customer

38、 data platforms that aggregate data for individual customers from multiple sources,and create a single,more accurate source of information.Next-best action.Apply a suite of analytics models to support customer acquisition,cross-selling,and other sales functions.Tailored content.Deliver individually

39、curated,personalized content to customers at every interaction and point of contact.As Asian insurers seek to deploy personalization strategies successfully and augment AI initiatives 5 “Personalization at scale,”December 2,2022.Exhibit 2There are four layers to the full-stack AI capability that wil

40、l defne the AI-enabled insurer of the future.Web 2023AI insurer of the futureExhibit 2 of 31Segmentation,targeting,and positioning.There are four layers to the full-stack AI capability that will defne the AI-enabled insurer of the future.McKinsey&CompanyValue created across stakeholdersIncrease in n

41、et new value poolsExisting value poolsTransactional and episodic customer engagementPersonalized and continuous engagementPhase 1Phase 2Phase 3Phase 4Phase 1:Digital underwritingAll applications submitted digitallyNear STP1 and auto-issue for majority of products(6070%or more)Phase 2:Accelerated sim

42、plifed underwritingDramatic reduction in number of applicants requiring invasive fuid and paramedical examsSignifcant reduction in number of questions on applicationPhase 3:Continuous underwriting with prescriptive actions to drive desired outcomesPersonalized products and packages based on continuo

43、us engagement and interventions to signifcantly infuence underwriting qualityPhase 4:Microsegmentation and personalizationGranular view of risk categories using holistic data sets(eg,external open data,connected devices)and enhanced AI algorithms to improve risk profling and lead generationMore-pers

44、onalized ofers and propositionsNew segments of traditionally underserved risks5Insurer of the future:Are Asian insurers keeping up with AI advances?and investments across the engagement layer,three distribution models are worthy of note.Digital hybrid agency.Globally,agents continue to be the larges

45、t distribution channel for most insurersbut retaining an edge and driving growth in agency will require competitive investment in digital and AI solutions.It can be done:a global insurer that redesigned its agency channel to be AI-ready realized an incremental impact of several million dollars over

46、the subsequent years.Specifically,the insurer used geospatial network optimization to identify geography-specific agents demand and capture growth opportunities and then used this data to inform its local recruitment strategy.Ramp-up time from newly hired agents to full productivity fell significant

47、ly,and retention rates rose.The company increased activation and productivity among agents with a behavior-driven,next-best-action recommendation engine and customized learning plans based on agents individual performance.Another leading insurer in Asia optimized its agency channel by shifting from

48、experience-driven operations to digital operations.It reformed its business outlet operation with embedded digital tools to support and optimize agent activity,improving productivity and growth by 5 to 10 percent.The insurer also empowered customer acquisition and conversions using AI-based audio an

49、d video illustrations of insurance knowledge,illness explanations,and more to complement agents interactions with customers.The insurers AI-based assistants support online interactions in real time and record a monthly average of approximately 100,000 client-meeting hours,enhancing customer experien

50、ce and acquisition efficiency.AI-facilitated policy issuance at this company was more than$100,000 in 2021,and agent productivity improved,as measured by a 25 to 30 percent increase in net book value per agent.Digital bancassurance.Bancassurance remains the second-largest channel driving life insura

51、nce sales globally and,due to legacy bank systems,is perhaps the most challenging to transform.Nonetheless,a leading Asian bank redesigned and simplified the insurance journey for its insurance partner,using customer analytics and microsegmentation-based customer personas to personalize lead nurturi

52、ng.Based on these analytics,journeys selected were either“fast”(moved directly to the product list)or“long”(with content integration),depending on customer preferences.Within four to five years,bancassurance penetration almost doubled and first-year premiums increased by 30 to 40 percent.Digital D2C

53、 distribution via ecosystems.Several insurtechs are paving the way for embedding insurance offerings in ecosystems and supporting multiproduct offerings on a single platform.Partnerships with leading players(generally the top 15 percent)to offer select products with simple terms,a short process,and

54、fast and convenient claims can help meet specific user needs for health,auto,life,accident,and other types of coverage.User data analysis can provide insurers with customer insights to inform product innovation and achieve differentiation in the market.A leading insurtech harnessed its parent groups

55、 traffic and data capability to create a competitive advantage in the insurance business.Insurance services are embedded in the parent companys mobile app,which has more than a billion monthly active users.The insurtech integrated its mobile apps ecosystem,expanding its distribution channels and pro

56、viding app users with access to offline medical networks not restricted to policyholders.Creating an AI-powered decision-making layerAlthough the insurance industry generates a massive amount of data across various levers and channels,this data is not,for the most part,being leveraged to build a sop

57、histicated decision-making layer that provides a highly personalized customer experience.AI technologies could be used to complement existing pricing and underwriting decision making.Specifically,these technologies could help support claims decisions and identify claims leakages by dynamically colle

58、cting and evaluating data points such as adjuster notes,damage images,text submissions,submitted documents,and patient histories.In a mature AI-powered decisioning layer,a suite of state-of-the-art analytics tools and edge capabilities is supported by a solid database 6Insurer of the future:Are Asia

59、n insurers keeping up with AI advances?system with clean,well-structured,analytics-ready data;a defined agile-delivery process;and a well-developed,analytical organization deeply connected to the business.Advanced analytics can simplify and augment decision making across the entire insurance value c

60、hain.In our experience,significant gains in efficiency,critical metrics,and more can be realized throughout the value chain:Marketing.Insurers can use AI-driven customer lifetime value(CLV)management to sift through large amounts of data.This can uncover insights to help identify high-potential cust

61、omers early enough to take action at all four stages of the customer life cycle:acquisition,onboarding,engagement,and retention.For example,an insurer using AI-driven CLV management achieved a major increase in gross written premiums.Underwriting.Using AI to support risk scoring can enable continuou

62、s underwriting and achieve multiple desirable outcomes.The insights resulting from continuous engagement,microsegmentation,and personalization,for example,can help develop customized products and packages.Pricing.Employing built-in pricing models that use machine learning for risk selection and deve

63、loping data domains for governance can help provide granular monitoring of KPIs and real-time monitoring of emerging loss,pricing trends,and shifts in the portfolio risk mix.Claims.One insurer is using AI to help identify fraud,waste,and abuse in health insurance claims,driving reductions of more th

64、an 5 percent in overall claims spend.Servicing.An AI-supported customer complaint journey powered by real-time sentiment analysis,smart workflows,and other capabilities helped one insurer significantly reduce the number of repeat complaint calls.New technologies such as generative AI amplify the imp

65、act possible across the value chain in very quick order(see sidebar,“The potential of generative AI in insurance”).Modernizing the core tech and data layerA modernized core tech and data layer helps uncover as well as deliver advanced intelligence through a seamless front-end experience for customer

66、s and the distribution network.Organizations with mature,AI-ready core tech and data layers have capabilities across the core tech stack,including a well-defined data infrastructure;data governance;advanced analytics tooling;technology operating model;a mature,hybrid cloud infrastructure;API archite

67、cture and linkages;and advanced cybersecurity and controls infrastructure.Once the above elements are defined in this layer,organizations can achieve sustained transformation by hiring talent to build these differential capabilities in-house,rather than outsourcing the foundational stack required.In

68、 The potential of generative AI in insuranceGenerative AI has dominated recent headlines,largely thanks to the growing popularity of AI chatbot ChatGPT.The technology could be a significant contributor to the insurance industrys efforts to redefine business models across the value chain,improving ef

69、ficiency,combating fraud,lowering costs,and hyperpersonalizing customer interactions.In sales and distribution,generative AI could be used to create personalized marketing content and tailor offerings based on customer demographics.It can help create more effective personalized scripts for agents an

70、d bancassurance reps to foster conversions.It could also be used to provide real-time,personalized advice and answers to basic customer queries to support customer relationship management.7Insurer of the future:Are Asian insurers keeping up with AI advances?fact,many players have developed distincti

71、ve stacks that have been monetized across insurers.A leading Chinese digital insurer gathered customer behavioral data to develop innovative products,improve customer profiling and segmentation,and more.Data-driven services also helped the insurer grow its customer base and refine its data analytics

72、,including dynamic pricing,automated claim settlement,and enhanced risk management effectiveness,serving more than 500 million insured customers in 2021.The company redefined the insurance value chain with continuous iterations and upgrades to its system to improve business efficiency,meet the diver

73、sified insurance demands of customers,and create value for stakeholders.A 2020 upgrade to its self-developed cloud system increased the companys processing capacity by more than 50,000 insurance policies per second.The insurers core systems are available to major insurers in Asia,and the company mai

74、ntains wide-ranging partnerships with internet platforms.Insurer customers can connect with various ecosystem partners locally and launch a variety of limited and scenario-based protection products.This technology arm of the company serves more than 30 insurers across life,property and casualty(P&C)

75、,and health,and more than half of its revenue was generated by recurring income.Optimizing the organization and operating model layerA modernized organization,operating model,and way-of-working layer supports AI readiness by providing the right talent,structure,and culture to put AI-powered capabili

76、ties into action.Transitioning from a traditional linear model to a cross-functional operating model facilitates expert-driven AI insights generation and adoption at the front line.The benefits of a cross-functional team structure that integrates business,AI,and technology functions can lead to fast

77、er alignment,increased flexibility,and high adoption of AI in the organization.These benefits are exemplified by data-driven organizations such as Google and Netflix that operate in relatively flat,cross-functional structures.Most insurers,however,have retained their traditional organizational struc

78、tures and implemented AI only on a limited basis.This can impede their AI readiness by reducing their capacity to implement the transformation needed in other layers of the AI capability stack.As demonstrated by a European banking group that adopted an agile business model,obstacles to transforming

79、traditional linear structures can be overcome,and gains in employee engagement,efficiency,speed to market,and client experience can be realized.For example,the banking group was able to release software and updates within two or three weeks rather than five or six times each year,and its employee an

80、d customer satisfaction scores rose dramatically in the first 15 months following its operational shift.The evolution of insurance:Whats ahead?In the short term,organizational shifts like those described above will help carriers prepare for AI-enabled improvements.In the long term,shifts will prime

81、the insurance industry to realize the kinds Transitioning from a traditional linear model to a cross-functional operating model facilitates expert-driven AI insights generation and adoption.8Insurer of the future:Are Asian insurers keeping up with AI advances?of AI-enabled gains experienced in other

82、 industries.As AI applications advance and become fully integrated across the customer industry,the breadth and nature of services and products that life insurers can provide will evolve from simply assessing and servicing claims to prescribing and preventing them(Exhibit 3).From automated processin

83、g to predictive analytics and prescriptive algorithms,AI offers the potential to enhance insurance protections with insights to support integrated life,health,and wealth solutions and personalized preventive strategies.The importance of employing strong risk management practices in insurance cannot

84、be overstated.The reality is that along with its potential Exhibit 3Web 2023AI insurer of the futureExhibit 3 of 3There are four layers to the full-stack AI capability that will defne the AI-enabled insurer of the future.In the future,life insurers focus is likely to evolve toward proactively preven

85、ting adverse events.McKinsey&Company“Assess and service”Pre-2020“Predict and personalize”202025“Engage and share value”202530“Prescribe and prevent”2030 and beyondIndividuals provide data that is used to assess risks and provide standard products and care suggestionsPolicies are priced,purchased,and

86、 serviced in predefned service-level agreements and cohortsInformation collected from external sources and devices is used to proactively assess risk and provide personalized wellness products and care suggestionsMajority of fnancial planning is done through algorithmic platforms,with agents humaniz

87、ing advice and building customer relationshipsAdvanced algorithms match leads to best-ft channel and advisorsPricing sophistication increases,with more-tailored pricing and smaller risk poolsIntegrated engagement platform facilitates data,insights,and transactions across multiple industries,allowing

88、 for value sharing between entitiesHighly dynamic,usage-based insurance products proliferate and are tailored to the behavior of individual consumersLines between life,wealth,and health products blur as integrated solutions come to marketMore than 90%of policies use accelerated and automated straigh

89、t-through underwriting;manual underwriting ceases for most productsAgents use smart personal assistants to optimize their tasks,as well as AI-enabled bots to recommend deals for clientsSmart contracts enabled by blockchain instantaneously authorize payments from a customers fnancial accountPrescript

90、ive suggestions provide interventions for agents or digital channels to actively infuence outcomesPersonalization is used to craft tailored strategies and coverage for each householdRobo and DIY channels can approximate human empathy and conversational capabilities,facilitating a 7090%servicing-cost

91、 reduction and providing a resolution within minutesAABCDEFGHIJLMNOKBCDEFGHIJKLMNO9Insurer of the future:Are Asian insurers keeping up with AI advances?Further insightsHow the Asian insurance market is adapting to the futureContactViolet ChungKarthi PurushothamanPartner,ChennaiKarthi_PurushothamanMc

92、K Senior partner,Hong KongViolet_ChungMcKCopyright 2023 McKinsey&Company.All rights reserved.Violet Chung is a senior partner in McKinseys Hong Kong office,Pranav Jain is a consultant in the Singapore office,and Karthi Purushothaman is a partner in the Chennai office.The authors wish to thank Radhik

93、a Agarwal and Norman Metzner for their contributions to this article.to revolutionize the industry,AI presents insurance players with potential challenges related to data privacy,inherent biases,interpretability,and more.Privacy breaches,intellectual-property infringements,and job displacements stem

94、ming from AI adoption are all too possible and illustrate why companies are better positioned for success when following blueprints based on proven models and best practices to implement and scale AI.The Asian insurance industry stands at a crossroads for AI-powered transformation:technological adva

95、nces can offer new and expanding growth opportunities,and lagging behind other sectors could exacerbate challenges to attracting and retaining top global talent and meeting evolving customer expectations.Though complex,a properly structured,layered approach to expanding AI capacity throughout the in

96、surance value chain can help Asian insurers realize long-standing goals and set new benchmarks for success as AI-powered insurers of the future.Scan Download PersonalizeFind more content like this on the McKinsey Insights AppHow personalization at scale can invigorate Asian insurers How Asian insurers can use digital marketing to fuel growth10Insurer of the future:Are Asian insurers keeping up with AI advances?