Alternative data for insurers
Nick Ferguson, Content Editor (London)
![Post feature](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBcDlSIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--2d484967ad3a0263a320296cfe9be3e8d4fd59ea/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRFeU9EQjRPRFV6QmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--4a0ea5eeb6f0e6d47bff3b653fd69e214040023f/optional%20ChatGPT%20image.png)
Insurers face an increasingly complex risk environment characterised by technological advances, demographic shifts, climate change and regulatory upheaval. Alternative data can offer deeper insights and a more granular view of risks, providing a significant competitive edge in risk assessment and policy pricing. We look at some examples of datasets that can deliver these benefits.
In some ways, the commercial insurance industry was founded on alternative data. Lloyd’s of London, for example, likes to trace its origins to a 17th-century coffee shop popular with sailors, merchants and shipowners, whose gossip informed views of maritime risk. Chatter about conditions at sea, incidents of piracy, disruptions at distant ports or emerging conflicts along popular routes could all help improve the ability to predict a sailing vessel’s return.
Similar to the collection of gossip at Lloyd’s Coffee House, alternative datasets typically monitor unstructured data sources and can be used to inform a better understanding of the real world. As such, integrating these datasets can help insurers to understand and anticipate risks more effectively. That means enhanced underwriting accuracy, improved claims processing and more tailored and competitive insurance solutions.
integrating data
Alt data is widely applicable in insurance, but underwriters may find that it is most useful around risks that are less commonly covered – because they are new or complex or are in regions or markets where traditional data might be scarce or less reliable. Such situations are an obvious starting point for insurers interested in using new sources of data to inform their views around risk.
Of course, insurers have access to lots of data already. A benefit of sourcing from the alt data sector is that many of these providers offer datasets that are ready to be ingested directly into analytical models. This allows insurers to embrace digitisation and make more informed decisions faster.
Some of the business lines where alt data may be most effective include:
- Cyber risk
- Shipping
- Supply chain and business interruption
- Property and construction
- Product recall