One of the biggest trends affecting the analytics sector at the moment is the emergenceRead More
Insurance sector ‘must be careful’ in how it uses big data
The increased use of big data in the insurance sector to conduct more personalised risk analysis and tailor quotes accordingly could lead to the create of a new 'underclass' of consumers who struggle to secure coverage unless the industry treats the technology with care.
This is the warning of a new report from the Chartered Institute of Insurance (CII), which said the use of the technology could result in some people being refused insurance altogether if they are deemed to be too risky.
The Financial Times reports that big data analytics is increasingly being viewed as a key part of the future of insurance due to its ability to give providers a more complete picture of their customers, thereby leading to a more personalised service.
Much of the discussion surrounding this so far has focused on the ability to offer discounts on premiums for activities such as careful driving and healthy lifestyles, but at the other end of the scale, this personalised approach could leave people priced out of the market.
"While in some cases this may be to do with modifiable behaviour, like driving style, it could easily be due to factors that people can't control, such as where they live, age, genetic conditions or health problems," the report stated.
Therefore, insurers need to be very careful about how they approach the use of big data analytics. While there are undeniable benefits to the technology, insurers must be wary about the extent to which they rely on this.
"Data is a double-edged sword," said David Thomson, director of policy and public affairs at the CII. "The insurance sector needs to be careful about moving away from pooled risk into individual pricing. They need to think about the broader public interest."
He added that if the industry cannot ensure that coverage is available to everyone – particularly in areas such as health insurance – intervention from the government may be required.
This has already been seen in some areas, such as home insurance. The Financial Times noted that improved mapping and data analysis has allowed insurers to much more accurately identify homes and businesses that are at highest risk of flooding.
This led to complaints from many people that cover became unaffordable for these areas, so the government created the Flood Re organisation, which aims to lower the cost of insurance for people living in high-risk areas.
"Regulators are trying to catch up on this issue," said Mr Thomson. "So there is a huge emphasis on insurers to guard their own reputations and business models. As in banking, algorithms can be good and bad."
At the moment, there are some restrictions on the data insurers can take into account when calculating premiums. Health and life insurers, for example, cannot use predictive genetic test results under an agreement between the government and the Association of British Insurers. This is currently set to expire in 2019, although a review is due next year that could see it extended.