"This study provides a comprehensive overview of how Artificial Intelligence is impacting the insurance industry and how it will support the transformation of the industry in the next 3-5 years"
Artificial Intelligence has gained momentum over recent years and is becoming omnipresent in the insurance landscape. New pilots and proofs of concept are being tested and implemented throughout the entire value chain, with tangible improvements in operational efficiency, customer experience, innovative product/service offering and better performing distribution.
In this study, Roland Berger provides a comprehensive overview and structuring of the main current AI use cases in the insurance industry which provide tangible value in this industry.
Globally, the number of pilots and proofs of concept that are being developed and launched by insurers has been increasing exponentially in recent years.
Our research chassifies the main existing insurance AI uses cases into nine fields of applications (Business model & product innovation, revenue enhancement, underwriting & pricing assessment, risk modelling, risk prevention, claim assessment, fraud prevention, customer service and general operational efficiency) where AI can create tangible value. It is based on the analysis of approximately 150 recent use cases and covers the entire insurance value chain.
The speed of adoption and development of AI in insurance over the next 3-5 years depends on several industry-wide and insurer-specific factors such as maturity of underlying technology, human vs AI-powered customer interfaces and regulatory developments related to AI-driven decision making and use of data.
"AI is a key enabler of competitiveness for insurers: 7 levers are crucial to make it a success."
With the exponential growth in AI use cases comes greater complexity for insurers in terms of IT, technology, systems and processes as well as HR, skills & talent management. Going forward, we have identified seven main hurdles that insurers will need to overcome to fully reap the benefits of AI. For each of these hurdles, specific levers and areas of action have been defined.
AI is bound to become a source of competitive advantage in the insurance industry. Beyond the key hurdles and levers to overcome, our study shows that there are tree main strategic implications for insurers:
1) Build an AI vision and choose your battles: The sense of purpose behind AI developments must be clear and shared within the organization.
2) Develop key capabilities in 3 main areas : HR, Technology and Engagement
3) Scale up and industrialize the AI approach: This is done by putting in place the governance and methodologies that enable you to prioritize initiatives and ensure appropriate focus.
Insurance has been, and is expected to remain one of the industries that will be the most impacted by AI in the coming years. Hence, with exponential development of uses cases and pilots, there is increasing need to have a clear view on where and how AI is creating value in insurance and how insurers can take advantage of the opportunities it creates.
With the exponential growth in AI use cases comes greater complexity for insurers in terms of IT, technology, systems and processes as well as HR, skills & talent management. Going forward, we have identified seven main hurdles that insurers will need to overcome to fully reap the benefits of AI. For each of these hurdles, specific levers and areas of action have been defined.
In this study, Roland Berger provide a comprehensive overview and structuring of the main current Artificial Intelligence use cases in insurance.
