The insurance industry, often cited as a sleepy backwater in the use of large modern data resources, is now heavily engaged in the accumulation of data assets and analytical capabilities for a host of needs: prospecting new markets; developing new products; increasing operational efficiency; refining pricing; and strategizing for future growth. With this growth it is more important than ever that insurers be responsible custodians of data portfolios, which now include information from newer sources such as fitness trackers, as well as mobile communications and personal medical devices, none of which existed even a decade ago.
Insurers need to be aware of both the risks and the tremendous opportunities these data streams can bring. The focus of big data's Four V's – Volume, Velocity, Variety, Variability is the current technical challenge of extracting business value from data. As a complement, we suggest also focusing on the Four R's – Regulations, Reasonable Expectations, Risks and Rewards. These four elements can be used to target the intelligent use of data for consumers, insurers and markets, and also to discover how data can ultimately benefit all insurance industry stakeholders.
The governing of how insurers can use data has already had market ramifications, and more may be coming. The European Union's 2004 anti-discrimination directive, for example, led to gender-neutral regulations by 2011 that obliged insurers to develop new tables and metrics to differentiate risk now that gender was no longer available. The EU's more recent General Data Protection Regulation, which governs exporting of personal data outside the EU, stipulates more explicit consent rules and grants "the right to be forgotten," (also known as "right of erasure") among other things, and could generate substantial regulatory change globally if other countries follow the EU's lead. The right to be forgotten essentially grants individuals the right to have a data controller erase all personal data relating to them.
Consumers are concerned about their data and how it will be used. These expectations include more than just appropriate fairness, confidentiality and transparency in use. Customers also want their data to benefit them. Insurers must be cognizant of these sensitivities, which can vary significantly by country. Germany, for example, has some of the strictest data protection laws in Europe, and the introduction in that country of the Generali Vitality program, which will collect personal fitness data from policyholders, resulted in a great deal of push back from the country's consumer protection media.
Consideration of the pitfalls of regulations and reasonable expectations will highlight significant risks, such as theft, misuse and loss, which can result in considerable consumer detriment and for companies, millions of dollars of reputational damage and potential fines. Commercial risks have to be considered as well. For example, first-mover advantage in introducing a new rating factor can be significant, but if competitors are able to follow suit quickly, then the market may have moved further toward commoditization without wider growth or other benefit. Indeed, in sophisticated markets, which are close to so-called perfect markets, errors in pricing models can be quickly exposed, leading to poor risk results, an issue that has affected several motor insurers globally.
Application of data and analytics, of course, also represents extraordinary opportunities. It is important to consider rewards for consumers, for we are using data they have shared perhaps naively now, but in the future such sharing is likely to be part of a more informed value transaction.