Data ... Outside In
2012/07/02
Increasingly, when it comes to the world of data, what lies outside of the traditional core insurance system landscape is fast becoming more interesting than what lies within it. For years, insurers have relied on their own data capture mechanisms to create unique insight enabling them to outperform the market when understanding the characteristics that make up a good risk versus a bad risk, and the end customer's propensity to buy. Size was important - the more data an insurer had access to, the greater its chance of developing unique insight.Now, I am not going to argue that insurer size is no longer important when talking about data, when simply it still is. However, there are a growing number of external data sources fuelled by the connected social generation, geospatial data and initiatives targeted at making public data more accessible that may benefit insurers when combined with existing internal sources for use in underwriting risk selection, pricing and claims validation. Some insurers, both large and small, are starting to look seriously into how this data can be used to drive growth and profitability.Typically, these external data sources are supplied through local government, industry sponsored initiatives, commercial organisations specialising in the aggregation and analysis of data as a service, and now also through open data markets, such as InfoChimps and Windows Azure Marketplace. Knowing how to navigate this market, and its associated legal aspects, is a major challenge for many insurers. Potential considerations:
- Build internal capabilities, or partner, to specialise in the search, acquisition and modelling of new data sources;
- Undertake effective due diligence to validate the authenticity of external data sources, permissions of use and jurisdiction;
- Combine data from a variety of sources, both internal and external, to test validity, build new models and discover new insight;
- Use data not only for risk selection and pricing, but also for incentivising good risk behaviour and practices; and
- Agree internally the ethics around using some of the data in risk selection and pricing - especially in relation to the use of social network data.