Mr. Winter, many insurance companies are in a transformation process towards more digital and data-driven processes. What are your observations on how COVID-19 has influenced this process?
The COVID-19 crisis has led to an enormous jump in digitalisation in the public and private sector. Many enterprises had to create mobile working options for their staff and implement digital processes to stay in touch with their clients in times of social distancing. This is also true for a lot of interactions between clients and insurers: the crisis has enforced more digital touchpoints, especially with clients who were not primarily digital before. In this respect, insurers have not only started to collect more but also more diversified data from new client segments.
Do you think the entire industry is on board for this transformation?
In total, the digital landscape in the insurance industry is very heterogeneous. On the one end, we observe insurers who have developed a strong digital footprint in the last couple of years. In Asia for example, some motor insurers are on a very good way towards a complete digitalisation and automation of the claims process based on AI for images, text and structured data. Besides claims settlement, clients can already use apps to simulate tariff adjustments after a claim, to find parking lots or to organise their vehicle inspections. Many other insurance companies all over the world have extended their digital offerings around video consultancy, simplified online underwriting and digital claims handling. On the other end, a smaller number of insurance companies is still struggling to implement first pilots for digital touchpoints and data-driven decision making.
Based on these insights, what trends do you anticipate with respect to digitalisation, data and AI?
Overall, I expect, further and faster investments in the digitalisation of most primary insurance business models and I suppose this will be based on the cost pressure to automate processes and on client demands for more digital touchpoints. And, AI will play a major role in structuring data from images and text and therefore will set the foundation for smarter and more automated decisions in underwriting and claims. The increase of machine learning on existing and even new data will enable insurers to optimise pricing and distribution by predicting customer lifetime values and help to better answer individual demands for more usage-based products.
What kind of challenges do you see for primary insurers who are just beginning their digital transformation process?
In order to achieve this in the near future, many insurance companies will need to become part of larger digital ecosystems. Ecosystems and smart partnering will ensure faster implementation without losing control of costs. However, high investments in compliance, more powerful IT infrastructures, AI and data analytics skills, innovation scouting and data capturing are sizeable financial investments. Insurers most likely won’t want to spend for all of these at once, especially during the current period of economic uncertainty.
So, how does Munich Re address these topics with their clients?
Overall, we have a lot of projects and initiatives with our clients to help digitalise processes and to establish digital touchpoints no matter where they are on this journey. I would like to especially highlight our activities around data analytics and AI. Here, we are supporting our clients with Analytics & AI services, like cross-selling or fraud detection, offered via a platform/ marketplace, through the statistical evaluation of large and/ or special risks, and also with tailor-made consulting.
Could you elaborate on the analytics and AI concepts?
We actively support our clients in analysing data by facilitating Munich Re’s infrastructure and talent pool to provide actionable insights. A good example of this is our analytics platform that helps steer and monitor motor and home owner business. A significant number of clients are already using our platform service, which combines both analytics and AI excellence and Munich Re’s risk know-how. This allows for more informed decisions and an easy and safe IT integration without large efforts. Hand-in-hand with that is our creation of AI centres of excellence that utilise specialised teams for AI-based data management and the analysis of text and images. By streamlining this data for clients, they are able to reduce operational costs while digitising processes. Additionally, while the extraction of text is quite insurance specific, the “trained” models can still be easily adapted for new use cases. So, there is definitely a real synergy.
How does this tie into consultation and the evaluation of risks?
Munich Re’s Global Consulting Unit has always prided itself on offering bespoke solutions to its clients. This comes from many years of primary insurance expertise and a massive investment in people and technology to assure actuarial know-how. Our global inno scouting teams are always actively working to extend our network too. This has helped in making us part of a larger ecosystem of external partners, start-ups and insurtech companies and thus growing our shared insight into analytics exponentially. It has also given us a clear understanding of the importance of digitising the industry. Integrating data analytics into pricing, for example, makes perfect sense for optimally supporting clients globally. And it goes without saying that when it comes to our best-known offering of delivering statistical and evaluatory consultation for large or special risks, our embracing of AI and the digitalisation movement has also led to significantly better data capturing.
Looking further into the future, how else will digitalisation, data and AI influence the way we run insurance business?
As automation, digitalisation and individualisation continue to evolve, we will begin to observe new risks, for example the risk of AI itself. It will be interesting to visualise how insurance for such a new risk could look like. But also, data protection and local regulation will have an effect and could change the ecosystem around data. Imagine, if everybody were to have full control of all of their data in a private cloud. This could require, that smart and intelligent “pre-trained” algorithms move around from one data pool to the next one as data remains in one place.
We have already taken some first steps to explore the possibilities within the insurance industry, while tech companies are already massively working on ecosystems around algorithms. What will be most interesting is the new ways insurers will be able to offer services and solutions in close correlation with the valuable insights and trends derived from data analytics.
