Technology Driven Change and Next Generation Insurance Value Chains (TECHNGI)

Financial and insurance services contribute more than 7% of UK national income and over one million jobs, with around one third of this employment in insurance. London is the leading global centre for specialist commercial (re)insurance broking and underwriting, with a wide range of specialised skills that supported the writing of £60 billion of gross written premium in 2013. Exports of insurance and pension services were £17.6bn in 2016, some 7% of total services exports.

Our project investigates the opportunities and challenges for the UK insurance industry arising from the application of the new Ai technologies, including machine learning, distributed ledger, automated processing and the explosion of available data for business analytics and modelling including from social media and the connections emerging to the 'internet of things'.

We will explore the implications for the insurance industry of this wave of new digital technologies, with the support of many of the UK's leading insurance companies. We will identify and map the range of opportunities for AI based innovation in business processes and business models, across underwriting and risk analytics, claims processing and customer engagement. We will examine, through engagement with industry on business opportunities and challenges and through a range of case studies, the barriers to adoption and the enablers of change.

We will examine these barriers and enablers both from organisational and industry wide perspectives. At the organisational level we will examine the requirements for successful innovation ("critical success factors") and develop organisation wide assessments of their readiness for adoption. At the industry level we will examine new emerging ways of providing insurance services, including the possibilities for transformative change in insurance value chains, for example with separation of risk and underwriting from customer engagement, and the potential for sharing of services and data.

Finally from these organisational and industry investigations we will develop strategic and policy analysis and recommendations, identifying the steps required from firms and from policy makers to support the adoption of AI technologies and ensure that these support automation and efficiency gains in UK insurance industry and benefit insurance customers.

A distinctive feature of our project is our deep industry engagement, offering us the opportunity to engage with practitioners across the full range of business functions: in strategic roles; in specific business areas across product lines and operational processes; in risk analytics; and in technology. These contacts will support a range of case studies of the deployment of AI in insurance and also interview, survey and forum style empirical investigations to achieve the full understanding from both these organisational and industry perspectives.

WHO MIGHT BENEFIT FROM THIS RESEARCH?

Our research is designed for several different user groups:
(a) Staff working across the insurance value chain. Successful technology based business innovation involves changes in both business process and business models and hence (Stephenson 2018 ch 7) requires a combination of expertise: technological (AI and data science), business (responsible for engagement with customers and suppliers) and analytical (e.g. underwriting and risk pricing). Our research - the Delphi interviews in Phase A, the case studies in Phase B, the frameworks and solutions in Phase C - will directly support these staff by providing relevant knowledge and understanding.
(b) Techinsur startups or in new competing technology based challengers, e.g. major internet platforms, who need understanding the insurance value chain and the potential for AI and data technologies. They will particularly benefit from our Phase A mapping and our detailed Phase B case studies.
(c) Senior management in the industry need to shape an appropriate strategic response to this new emerging landscape. Our integrative workpackages in Phase B (WP4.1, WP4.2, WP5.1, WP5.2) together with our Phase C workpackage 6.3 on implementation frameworks are addressed to their needs.
(d) Regulators, compliance officers and policy makers want to support these technological changes, and where possible use them to better achieve regulatory objectives such as customer protection at less cost to the industry.

HOW MIGHT THEY BENEFIT FROM THIS RESEARCH?

Business line and technology staff in UK insurance can gain insight into the organisational and business challenges arising from the application of AI to their products and business processes. They will be able to learn best practice and the factors for successful innovation from our case studies and research based empirical investigations. Risk analytics staff may also benefit from better understanding the opportunities for data-based improvements in risk modelling and underwriting.

Insuretech entrepreneurs can gain from a better understanding, especially from our case studies, of the business requirements for successful new technologies.

Senior management can also gain strategic insight, in particular into changing business models, into the possibilities for co-operative effort to develop standards and supporting technology and for negotiating the potentially transformative impact of technology on the industry as a whole.

Policy makers and line staff in regulatory bodies can benefit from improved understanding of insurance business models and how they are affected by technological change; on recommendations and opportunities for better alignment of regulations with the new technologies; on developing policies for regulation of new business products and technology supported business models; and from understanding and supporting opportunities for using technology to support regulatory compliance

We offer all of these different user groups practical options for promoting the application of AI and data technologies in the UK insurance industry, in the short to medium term at the level of specific business process and over the longer term by influencing the strategic and policy decisions that shape future business models and support industry transformation.

Our research strategy, based on close engagement with our industry partners and co-production of research, provides assurance that our range of research outputs will be relevant to these targeted user groups and, if we do our job well, have the desired medium and long term impact on the future of the UK insurance industry.