Insurance Transformed

Naylor introduces exponential change and then explores the concepts which underlie it. He argues that people in general expect change to be linear when in fact technological change tends to be exponential. He explains that this means that people consistently make mistakes about what the future will be like. For most technological changes, people tend to over-expect change during the initial 2/3rds of the period and are then shocked when change occurs faster than they expect during the last 1/3rd. The chapter explains that this contrast between linear expectations and exponential technological change underlies the Gartner Hype Cycle, which illustrates how most technological changes are over-hyped during their initial stages, and then as actual progress falls behind expectations, there is disillusionment, before actual useful products are produced. The chapter concludes by arguing that the current disruption facing insurance companies is disruptive rather than incremental, and therefore, insurers have to be careful not to be caught out by misreading which stage of the Hype Cycle their industry is at.

Naylor provides a useful summary of the key technological innovations which underlie the looming technological disruption of the insurance sector. These include the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Hyperscaling, Voice and Visual Recognition, Block-chains, and cultural generational change. He argues that while each of these are important, disruptive change only occurs when they all combine. This is because the success of each depends on the others.

Naylor provides a summary of the types of insurance available. This is useful for non-insurance sector readers.

Naylor explains and explores the impact of the looming waves of disruptive technology on the insurance sector. The chapter starts by arguing that the combination of disruptive drivers explored in an earlier chapter means that change is likely to be disruptive than incremental. It explains how these changes will mean a shift in cost of production toward high fixed cost and low marginal cost. The chapter points out that incumbent insurers are struggling to understand the scale of the transformation required. The chapter then draws in data and analysis from a diverse range of sources and explores how the production cost change and other changes will impact of the change on areas like legacy IT systems, customer relationships, and disintermediation. The chapter then explores the implications of the creation of big data via telematics and its analysis by AI systems for various aspects of the insurance value chain. The chapter has a strong focus on how the automation of administrative processing can be combined with insights gathered from big data and used to individualize policies and provide superior customer service. The chapter explores the inherent changes required from a big data-based process. The chapter then argues that the changing cost structure combined with the increase in customer engagement implies that insurance has to move toward real-time continuous interaction, which it calls dynamic insurance. The main conclusion is that a transformation is required in how the insurance sector views itself.

Naylor provides a useful analysis and summary of what incumbent insurers need to do to survive the looming waves of disruptive technological innovations and the competition by InsurTech entrants. This is placed within the framework of innovation disruption theory and uses a number of industry studies. The chapter analyses each stage of the insurance process and outlines what is required. The insurance sector is seen as requiring a transformation in the way it views its output, in the style of management, and in its engagement with customers. The major theme of the chapter this that intensive end-to-end automation will transform costs of production. The chapter argues that combining this with telematic-based big data and AI analysis means that the current insurer model is likely to be outmoded. Naylor argues that the way forward is to transform insurance from a product-based model to a data-based service model. This will allow incumbents to survive and enhance profit streams. The chapter outlines how there will be a need for increased flexibility and rapid response to changing customer expectations. The chapter then lays out a series of transformation pathways. These will include being more actively involved with customers and creating a wider business ecosystem. The management requirements of moving to an AI data-based approach are explored. The lessons learnt from a number of successful and unsuccessful business case studies are integrated throughout.

Naylor examines the likely impact of the insurance transformation required by each sector of insurance. There is a particular focus on the looming transformation of automobile insurance as this is seen as the first sector to be transformed. There is then a discussion on other insurance sectors, including Life and Health. The chapter argues that while health insurance may transform slower than automobile, its eventual transformation will be nearly as substantial.

Naylor explores the conceptual issues relating to how fast the transformation in insurance will occur. The dynamics of the demise of the current insurance structure are vital, as while most expert observers agree that transformation is looming, the speed and manner of the process of transformation will determine whether or not insurer incumbents can survive the transformation process or die off. While exact predictions are impossible, this chapter explores the concepts, which will help managers plot a path through the transformation process. Reasons why the transformation process may occur faster than insurers think are explored.

Naylor examines the likely responses of insurer incumbents to the looming waves of disruptive technology and examines successful and unsuccessful responses. Reasons why incumbents tend to be slow to respond to disruptive change are explored, and the conditions which encourage disruptive external entrants are examined. The chapter then explores the stages of disruption and why incumbents often miscalculate their chances of survival. The issues of trying to respond to disruption while minimizing damage to existing markets are explored, as are typical mistakes made by incumbents. The chapter then provides examples of companies who are responding to the looming crisis in successful ways, both incumbents and external entrants. The chapter ends with a vision of the transformation in the insurance market required to enter the new age.

The transformation to an insurance sector run on a dynamic AI big data basis raises a number of complex regulation and legal issues. Naylor outlines what these are and suggests how regulators and insurance companies can resolve these. This chapter also explores ethical issues raised by the new insurance model and explores the issues which insurers will have to be aware of.

The process of change to a transformed insurance sector has multiple implications for those employed in the sector. Naylor explores these issues. While the chapter agrees that most activities will be affected it disagrees with the common argument that process automation implies a substantial reduction in employment. Instead, Naylor argues that insurance incumbents can thrive by proactively migrating staff into providing a far wider array of services. The chapter explores concepts which determine which activities will disappear and which will expand.

This chapter explores the impact of the looming transformation on insurance occupations. There is a particular focus on the impact on insurance advisers and brokers. This chapter explores the concepts which advisers who aim to survive need to understand. Naylor argues that there are a range of activities which humans will continue to do better than software, and advisers who focus on these will thrive and expand their income, while providing a superior level of service to more customers. A number of recommendations are offered.

This chapter concludes the book and speculates as to a more distant future.