SWEDEN Trends and Developments Contributed by: Viveka Classon, Karin Rättzén and Sara Stålebring, Advokatfirman Vinge KB
Insurtech The Swedish insurtech market includes digital chal- lengers, infrastructure providers and niche actors, such as: • Hedvig, which, beyond digital home insurance, has established partnerships in distribution – eg, with major Swedish bank SEB; • Insurely, which provides open APIs for data port- ability and embedded insurance solutions; • Lassie, which combines pet insurance with preven- tion and behaviour-based models; • Greater Than, offering AI-based risk analytics in mobility/telematics; • Omocom, which supports platform businesses with embedded and on-demand solutions and has gained attention for its licensing developments; • Lumera, which modernises core systems in life and pensions business; and • EIR insurance, a B2B2X white-label insurance company that uses automation, cloud-native infra- structure, open APIs and AI to deliver insurance. The following trends appear to be particularly promi- nent in the insurtech business. • Expansion of embedded insurance and platform- based distribution, with insurance integrated into e-commerce, mobility and banking flows to reduce distribution friction. • Growth of open insurance and data driven ecosys- tems via APIs that enable transparency, compari- son and personalised offerings. • Increased use of AI/telematics for dynamic pricing and prevention, especially in motor and property. • A rise in niched insurtech companies focusing vertically (for example pet, sharing economy, micro insurance), where specialised risk modelling pro- vides an edge. • Modernisation of life/pensions infrastructure towards cloud-based administration, regulatory compliance and product flexibility. The growing MGA market in Sweden The Managing General Agent (MGA) segment has grown in importance in Sweden over the past decade, often focusing on niches, complex risks or technol- ogy driven distribution. International actors such as
tion. Also, complaints handling will remain a continued focus going forward. According to the SFSA, many non-life insurance prod- ucts (eg, product insurance for electronics) and loan/ payment protection policies are sold to consumers who do not need them. It has observed that this is especially prevalent among ancillary intermediaries – such as electronics retailers – who distribute on behalf of insurers and are paid per policy, creating conflicts of interest that can distort sales incentives and undermine the demands-and-needs assessment. As the SFSA notes, this results in consumers paying for duplicate or unnecessary cover already provided by other policies or statutory rights. Market Developments The use of AI in the insurance sector AI is being integrated into an increasing number of core processes such as underwriting, claims handling and fraud prevention, and is used to improve risk assessments in complex or emerging risks including cyber, weather-related property damage and motor behaviour. Sensors and telematics also enable proac- tive loss reduction in real time. Customer-facing applications – such as automated tri- age and conversational interfaces – shorten lead times and improve accessibility. At the same time, super- visory expectations require models to be transpar- ent, traceable and fair. AI is also used to detect fraud patterns, but the technology creates new fraud risks (eg, synthetic documentation) that must be addressed with enhanced verification. The greatest obstacles to safe and compliant AI adop- tion in the insurance sector appear to be cultural and organisational: governance, access to specialised competence and legacy IT environments. Key model risks include data bias, model drift and hard-to-verify outcomes, which require structured model risk man- agement and documentation aligned with the EU AI Act and the SFSA’s expectations regarding govern- ance, transparency and consumer protection.
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