The Customer Journey of a Lifetime: Step-by-Step Modernisation to Maximise Retention

Customer experience is the insurer’s latest hot topic. Improving it at existing touchpoints and finding new opportunities to deliver it beyond purchase, renewal and claims dominate discussions. McKinsey found in the B2B sector that improved customer experience lowered churn by 15%, increased win rate from 20% to 40% and lowered costs to serve by up to 50%.

But understanding how to deliver great insurance customer experience, whether on mobile, in a contact centre or at a repair shop means far more than finessing an individual point of interaction. How the customer experiences each interaction and how it colours past and future interactions is critical to building a successful customer experience.

In other words, if you don’t give your customer the best journey, they’ll never arrive at the desired destination.

In this paper we look at the latest research supporting customer journey analysis and speak to three insurance executives who are putting this strategy at the heart of their customer experience and engagement policy. Progress towards the optimal customer journey is examined in the following stages:

  1. Proof points for customer journey analysis
  2. Embedding effective customer tracking
  3. Solid data collection practice
  4. Assessing and enhancing the availability of information
  5. Upskilling the organisation to manage the journey
  6. Discovering and mitigating pain points in the customer journey
  7. An atmosphere of continuous improvement

Proof points for customer journey analysis

Customer journey analysis and optimisation is so important because of the multiple channels and external influences involved in the buying process. So much can happen between intent and purchase. No-one is exempt. Google and Ipsos found that 90% of people move between devices in a sequential fashion to accomplish a goal. In online shopping, 61% of internet users and 80% of online millennials start shopping on one device but finish on another.” This is a pretty simplistic view. If we turn to research by user experience research house, GfK, the customer journey looks even more convoluted:

CX Survey

From this infographic, we note that most insurance customers use branded search but also go across around eight touchpoints including social media and email. Only 14% don’t do any research and for those who do, most will research online covering around five different websites. Further research on the insurer journey from GfK found that hardly any purchasers bothered with word of mouth (5%) but price comparison sites (PCS) wield a strong influence (26%).

This diagram only relates to the insurance purchase journey. There are many more influences on customer retention such as claims journey, customer engagement campaigns (increasingly popular under the influence of internet of things (IoT) technology).

Embedding effective customer tracking

The business case for journey analysis established, insurers need to make sure they are tracking all the essential touchpoints.

ERGO Group AG’s Head of Customer and Sales Service Health, Dr. Carsten Rahlf explains his process: “If a phone number is saved in the database we can see the customer’s profile upon calling, their historic interaction points, so we know where he is in the process. If he went to the doctor, paid him and wants to be reimbursed, also we can see when and how he submitted his bills. He may have sent them by post or used the app. He and we can see through the online portal that his request has been accepted and the customer and the agent can then track it to see if it has been executed.”

Wesleyan’s Group Head of Marketing Robin Gibson is in the middle of bringing CRM data into a Microsoft Dynamics system to improve their single view of the customer – vital to make any sense of customer tracking data. Executives looking to follow his lead should be aware it is a long-term project: “We spent the last three years on integration, migrating all the data into new CRM systems. The first part is to allow financial consultants and the customer to jointly have a single view of finances. »

« The next part is to allow customers to self-serve on their devices. Next, we need to put marketing plugins into the system to simulate interactions and use the database to find new customers.” He adds that a manageable, clean source of customer information is vital to comply with May 2018’s GDPR legislation which requires explicit data consent ongoing. It’s clear that tracking the customer journey means not just focusing on points of customer interaction such as cookies on a website or calls to a call centre but also looking internally to see what processes are helping or hindering that customer journey.

This will never be an exact science. Explaining where tracking begins and ends in MyCustomer, SEO expert Martin Calvert admits a degree of arbitrariness is expected “The start and end points of a customer journey are always going to be debatable. Does the journey ultimately start when they see one of your brand’s adverts years ago…does it end after they’ve bought their last product from you in their 80s?”

The learning is to track what you can and hunt out two specific areas:

  • one, where gaps in the customer journey appear
  • and two, where customers appear to experience pain points that are unaccountable – so far.

To get reliable pictures of this, insurers need to access as much data as possible.

Customer Journey

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By investing heavily in start-ups and technology, (re)insurance companies appear to have assumed a semblance of control over the InsurTech revolution

Who Benefits from Modularization?

With technology moving forward at an unprecedented pace, incumbents are increasingly electing to outsource functions to highly specialized new entrants, renting evolving modules of technology that can be tailored to suit their individual needs. Though this approach may be more cost effective, it further fuels the question of whether incumbents will allow value in the industry to shift towards new entrants. In time, market participants will come to understand which module in the chain generates the most value. It is plausible that automation in distribution will shift value towards efficiency of internal processes that support cutting-edge modeling and underwriting engines.

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The State of InsurTech

InsurTech funding volume increased 36% year-over-year in 2017, demonstrating that technology driven innovation remains a core focus area for (re)insurance companies and investors heading into 2018. However, perhaps contrary to many of the opinions championed in editorial and press coverage of the InsurTech sector, further analysis of the growing number of start-ups successfully attracting capital from (re)insurers and financial investors reveals that the majority of InsurTech ventures are not focused on exiling incumbents by disrupting the pressured insurance value chain. According to research from McKinsey & Company,

  • 61% of InsurTech companies aim to enable the value chain,
  • 30% are attempting to disintermediate incumbents from customers
  • 9% are targeting full scale value chain disruption.

Has the hype surrounding InsurTech fostered unjustified fear from overly defensive incumbents?

We have taken this analysis a step further by tracking funding volume from strategic (re)insurers versus financial investors for InsurTechs focused on enabling the value chain relative to their counterparts attempting to disintermediate customers from incumbents or disrupt the value chain altogether and found that 65% of strategic (re)insurer InsurTech investments have been concentrated in companies enabling the value chain, with only 35% of incumbent investments going to start-ups with more disruptive business models. What does it mean? While recognizing the subjective nature of surmising an early stage company’s ultimate industry application at maturity from its initial focus, we attribute this phenomenon to the tendency of incumbents to, consciously or subconsciously, encourage development of less perceptibly threatening innovation while avoiding more radical, potentially intimidating technologies and applications.

Recognizing that this behavior may allow incumbents to preserve a palatable status quo, it should be considered in the context in which individual investments are evaluated – on the basis of expected benefits relative to potential risk. We have listed several benefits that InsurTechs offer to incumbents :

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Segmenting the InsurTech Universe

As InsurTech start-ups continue to emerge across the various components of the insurance value chain and business lines, incumbents and investors are evaluating opportunities to deploy these applications in the insurance industry today and in the future. To simplify the process of identifying useful and potentially transformational technologies and applications, we have endeavored to segment the increasingly broad universe of InsurTech companies by their core function into four categories:

  1. Product & Distribution
  2. Business Process Enhancement
  3. Data & Analytics
  4. Claims Management

This exercise is complicated by the tendency of companies to operate across multiple functions, so significant professional judgment was used in determining the assignment for each company. A summary of the criteria used to determine placement is listed below. On the following pages, we have included market maps to provide a high level perspective of the number of players in each category, as well as a competitive assessment of each subsector and our expectations for each market going forward. Selected companies in each category, ranked by the amount of funding they have raised to date, are listed, followed by more detailed overviews and Q&A with selected representative companies from each subsector.

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Technology Driven Value Generation in Insurance

The evolution of financial technology (FinTech) is reshaping the broader financial services industry. Technology is now disrupting the traditionally more conservative insurance industry, as the rise of InsurTech revolutionises how we think about insurance distribution.

Moreover, insurance companies are improving their operating models, upgrading their propositions, and developing innovative new products to reshape the insurance industry as a whole.

Five key technologies are driving the change today:

  1. Cloud computing
  2. The Internet of Things (including telematics)
  3. Big data
  4. Artificial intelligence
  5. Blockchain

This report examines these technologies’ potential to create value in the insurance industry. It also examines how technology providers could create new income streams and take advantage of economies of scale by offering their technological backbones to participants in the insurance industry and beyond.

Cloud computing refers to storing, managing, and processing data via a network of remote servers, instead of locally on a server or personal computer. Key enablers of cloud computing include the availability of high-capacity networks and service-oriented architecture. The three core characteristics of a cloud service are:

  • Virtualisation: The service is based on hardware that has been virtualised
  • Scalability: The service can scale on demand, with additional capacity brought online within minutes
  • Demand-driven: The client pays for the services as and when they are needed

cloud

Telematics is the most common form of the broader Internet of Things (IoT). The IoT refers to the combination of physical devices, vehicles, buildings and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these physical objects to collect and exchange data.

The IoT has evolved from the convergence of

  • wireless technologies,
  • micro-electromechanical systems,
  • and the Internet.

This convergence has helped remove the walls between operational technology and information technology, allowing unstructured, machine-generated data to be analysed for insights that will drive improvements.

IoT

Big data refers to data sets that are so large or complex that traditional data processing application software is insufficient to deal with them. A definition refers to the “five V” key challenges for big data in insurance:

  • Volume: As sensors cost less, the amount of information gathered will soon be measured
    in exabytes
  • Velocity: The speed at which data is collected, analysed, and presented to users
  • Variety: Data can take many forms, such as structured, unstructured, text or multimedia. It can come from internal and external systems and sources, including a variety
    of devices
  • Value: Information provided by data about aspects of the insurance business, such as customers and risks
  • Veracity: Insurance companies ensure the accuracy of their plethora of data

Modern analytical methods are required to process these sets of information. The term “big data has evolved to describe the quantity of information analysed to create better outcomes, business improvements, and opportunities that leverage all available data. As a result, big data is not limited to the challenges thrown up by the five Vs. Today there are two key aspects to big data:

  1. Data: This is more-widely available than ever because of the use of apps, social media, and the Internet of Things
  2. Analytics: Advanced analytic tools mean there are fewer restrictions to working with big data

BigData

The understanding of Artificial Intelligence AI has evolved over time. In the beginning, AI was perceived as machines mimicking the cognitive functions that humans associate with other human minds, such as learning and problem solving. Today, we rather refer to the ability of machines to mimic human activity in a broad range of circumstances. In a nutshell, artificial intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider smart or human.

Therefore, AI combines the reasoning already provided by big data capabilities such as machine learning with two additional capabilities:

  1. Imitation of human cognitive functions beyond simple reasoning, such as natural language processing and emotion sensing
  2. Orchestration of these cognitive components with data and reasoning

A third layer is pre-packaging generic orchestration capabilities for specific applications. The most prominent such application today are bots. At a minimum, bots orchestrate natural language processing, linguistic technology, and machine learning to create systems which mimic interactions with human beings in certain domains. This is done in such a way that the customer does not realise that the counterpart is not human.

Blockchain is a distributed ledger technology used to store static records and dynamic transaction data distributed across a network of synchronised, replicated databases. It establishes trust between parties without the use of a central intermediary, removing frictional costs and inefficiency.

From a technical perspective, blockchain is a distributed database that maintains a continuously growing list of ordered records called blocks. Each block contains a timestamp and a link to a previous block. Blockchains have been designed to make it inherently difficult to modify their data: Once recorded, the data in a block cannot be altered retroactively. In addition to recording transactions, blockchains can also contain a coded set of instructions that will self-execute under a pre-specified set of conditions. These automated workflows, known as smart contracts, create trust between a set of parties, as they rely on pre-agreed data sources and and require not third-party to execute them.

Blockchain technology in its purest form has four key characteristics:

  1. Decentralisation: No single individual participant can control the ledger. The ledger
    lives on all computers in the network
  2. Transparency: Information can be viewed by all participants on the network, not just
    those involved in the transaction
  3. Immutability: Modifying a past record would require simultaneously modifying every
    other block in the chain, making the ledger virtually incorruptible
  4. Singularity: The blockchain provides a single version of a state of affairs, which is
    updated simultaneously across the network

Blockchain

Oliver Wyman, ZhongAn Insurance and ZhongAn Technology – a wholly owned subsidiary of ZhongAn insurance and China’s first online-only insurer – are jointly publishing this report to analyse the insurance technology market and answer the following questions:

  • Which technologies are shaping the future of the insurance industry? (Chapter 2)
  • What are the applications of these technologies in the insurance industry? (Chapter 3)
  • What is the potential value these applications could generate? (Chapter 3)
  • How can an insurer with strong technology capabilities monetise its technologies?
    (Chapter 4)
  • Who is benefiting from the value generated by these applications? (Chapter 5)

 

Click here to access Oliver Wyman’s detailed report

Insurance Data Integrated Platform

The insurance industry today is poised for a paradigm shift in the way that technology is deployed to provide products and services to customers. This has primarily been driven by changing business needs and the innovations brought about by myriad insuretech firms, leading to an inevitable shift towards adopting the new digital innovations.

Analysts have forecast significant investments geared towards the digitalization of the industry and expect such investments to continue pouring in for several years. It is also expected that an increasing number of new insurance companies will be driven by technology companies to bring better products, services, and customer service in the insurance industry.

A forward-looking plan of action, sufficient operational flexibility, an effective implementation strategy, and a willingness to adopt digital disruptions in every aspect of their organization – those insurers that have all of the above can position themselves to leverage the impending digital disruptions to propel their organization to the very forefront of the industry.

DEALING WITH THE DIGITALIZATION OF THE INSURANCE INDUSTRY

These adopters of digital technology will have a clear upper hand against their competition. Suitably equipped to cut costs and design more attractive offerings, the digital insurance carriers are sure to acquire a whole new set of customers, thus increasing market share. Those who fail to quickly adopt the new technologies, on the other hand, will struggle to maintain their competitive positions in the midst of a customer-centric, price-sensitive market.

Data has always been at the center of the insurance industry, and despite the changes that are to come, data will continue to be the focal point of the industry. In fact, it’s set to play a bigger role to play than ever before.

The continued criticality of data in the insurance landscape is ensured by carriers’ need for information-driven strategies in the digitalized business scenario. They’ll have to leverage data as an asset, enabling automated decision-making in critical business processes, in order to thrive. This, in turn, is why a digital business technology platform – one that incorporates information management and analytical capabilities – will become a necessity in the future.

Without a system in place to support the analytics and reporting needs of the business, decision-makers may be left with no choice but to rely on conventional time-consuming manual processes those are more qualitative rather than quantitative in nature. This is bound to cause serious repercussions for the organization, ultimately resulting in missed opportunities and loss of competitiveness.

According to a Gartner study, the two following technology platforms are essential for any digital business:

  1. Data and analytics platform – This platform should consist of data management programs and analytics applications to enable data-driven decision making
  2. Ecosystems platform – This platform’s role should be to support the creation of and connection to external ecosystems, marketplaces, and communities

MFX

 

Click here to access MFX’s detailed White Paper

 

InsurTech Caught on the Radar

The overall picture that emerges from our InsurTech Radar is, first of all, that different business model categories vary significantly in terms of overall level of economic attractiveness and degree of startup activity. While some see little startup activity, others already appear overcrowded. The number of InsurTechs active in a category is not always in line with its relative attractiveness.

Secondly, even in the most attractive business model categories, it is not clear that InsurTechs will disrupt the industry and make the race. The players most likely to succeed vary by category. InsurTechs will not always be the winners. There are several categories in which either incumbents embracing digital change or firms from outside the insurance industry are most likely to succeed.

Thirdly, a number of underdeveloped categories present attractive opportunities. To be successful in these areas will require innovators to get creative on “demand side” thinking creating models that fundamentally change how risk coverage is presented and sold to customers, models that are not merely digital updates of traditional or slightly altered insurance propositions. Such thinking – substantially different from the “supply side” models of the current, first wave of InsurTechs – is essential for uncovering latent customer demand for risk cover.

Segment 1: Proposition

The proposition segment is less than half the size of the others. It is also the most varied in terms of outlook. The InsurTech Radar shows that there is currently a major mismatch in this segment between the categories with the highest level of startup activity and those with the greatest overall potential. Examples include Situational and Community-Based business model categories which we see as over-emphasized. Nevertheless, the proposition segment includes some of the most attractive categories of any InsurTech segment, as they represent true innovation on how risk coverage is presented and sold to customers – some of these currently see relatively little activity so far (such as the Risk Partner business model category). While the news here is good for established insurers, in that they are likely to be the winners in several of these attractive categories, it is also quite clear that InsurTechs are here to stay. The emergence of newly funded and fully digital insurance carriers might bring forward real breakthroughs. It is very likely that the segment will look quite different in a few years.

Segment 2: Distribution

The InsurTech Radar shows the distribution segment to be much better matched in terms of the level of activity and the categories with the highest likelihood of success. On the down side, all but two of these areas have, comparatively only moderate potential at best, due either to limited premium pools, challenges in sustaining value generation, little opportunity for differentiation, or some combination of these (such as B2C Online Brokers). As in the proposition segment, some of the most crowded categories are also likely to see a shakeout.

Segment 3: Operations

The operations segment is the most consistent of the three: Only one business model category here currently shows limited potential (the “Balance Sheet / Financial Resource
Management” category). Most others are highly attractive. InsurTechs are likely to dominate the segment, albeit sharing honors in the underwriting category with reinsurers.

InsurTech OW

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