Machine intelligence in insurance
Our sigma edition 1/2020 provides a comprehensive overview of the changes that digitisation will enable in the re/insurance industry, including affordable and accessible products. We shared more information on this process in other contributions, also discussing some of the challenges lying ahead.
For example, in the article “Why data and machine intelligence will become the new normal in insurance”, authors from Swiss Re Institute drew attention to the increasing importance of personalisation and the need to get this right. A potential pitfall is to assume homogeneity across specific groups and to develop solutions based on superficial group characteristics. What will be paramount, in contrast, is to tailor services and online experiences to individuals rather than groups.
Care must also be taken if vulnerable groups are to be reached as soon as possible, for example people in lower income brackets or with chronic mental health conditions. If efforts focus too much on millennials, who currently constitute the majority of digital consumers, there is a risk that vulnerable groups are not represented and visible in the data on which customer surveys are based. Products will then not be adapted to their specific needs.
Blog: Data and machine intelligence in insurance
Later in 2020, Swiss Re Institute published a sigma edition on “Machine intelligence in insurance” (5/2020). This looked at a key challenge surrounding the transformation to digital insurance: the lack of quality data and data engineering which has so far prevented the insurance industry from fully harnessing advances in machine intelligence. The sigma authors argue that this is not because the data are not available, but that they are not being curated, transformed and processed adequately. Addressing this shortcoming will require a major effort to build up the necessary data architecture.