Has Big Data Ushered Out the Age of Insurance Segmentation?
In days gone by, the insurance sector boasted a number of niche insurance agencies and brokers underwriting risks for specific demographics - such as women or young people. However, in recent years, the dawn of “Big Data” has given rise to exceptionally large sets of data, allowing companies to analyse such a vast range of different information that basic diversifying factors such as age or gender are no longer viable ways to segment the market. Underwriters are now able to build an individual risk profile that is not based on such sweeping generalisations, but rather on very specific details about lifestyle, finances, interests and habits, as well as a wide range of other factors.
This new age of Big Data and the loss of traditional customer segmentation, gives lots of scope to insurance companies wanting to appeal to new and existing customers, through a number of approaches:
In the past, life stages have been largely predictable, with people studying, marrying, starting families, working and retiring - mostly in that order. Now these stages of life can happen in any order, or not happen at all, or some stages can happen more than once. Within these life stages, personalities, income and priorities are different, giving an almost infinite number of different variables and therefore an almost infinite number of different risk profiles.
While risk and policy pricing is no longer driven by segmentation, there may be new ways to segment clients; by the way they like to receive product information; advertising likely to appeal to them; the payment methods they will want to use; the amount of paperwork they are likely to have the patience to complete and many other factors that may assist with successful marketing and advertising.
A personal profile
While access to Big Data runs the risk of companies viewing clients as mere sets of facts and figures, there is also scope for the opposite. With effective analysis of the data, policies and prices can be personalised, due to the ability to analyse risk far more accurately. Underwriting based on gender stereotyping is long gone, with other common demographics, such as age, also being phased out.
Research has found that only approximately 50% of insurance customers trust that a claim will be paid out in the event of a loss. The least trusting age group is 16-29 year olds, with a mere 37% trusting that a claim would be paid.[i] These individuals see insurance as an inconvenient necessity – but this is the consumer group that over the next decade will be needing insurance for everything; from cars to holidays, business to life insurance. Engaging with them and gaining their trust by treating them as individuals is vital to winning their custom, and Big Data can help to ensure that they feel comfortable with a company that has personalised them and treats them as an individual.
Research shows that 64% of customers are concerned that brands come to conclusions about them based on a one-off interaction.[ii] Big Data gives an opportunity for a company to evidence an in-depth knowledge of a client, rather than a superficial understanding.
Using Big Data responsibly
It is natural that Big Data may spark privacy fears and it is important to ensure that data is collected, used and stored responsibility. Recent GDPR legislation already mandates a certain amount of care, but companies would do well to make data collection and analysis clear and avoid collecting data in a way that makes customers feel that their privacy is being invaded. Investing in infrastructure and technology that protects data thoroughly is vital, to avoid risk of cyber attacks.
Investing in technology to collect and analyse data
There are many types of disruptive technology that have recently entered the market, offering a variety of different data sources as well as ways to analyse them via artificial intelligence. The Internet of Things (IoT) has a large place in the future of data gathering. Already it is possible to give drivers a means by which their driving style and habits can be closely analysed via a telematics device. Insurers are able to gather information about the time of day and amount of time an individual spends driving, as well as braking times, speed and distance. This offers a groundbreaking way to analyse risk, far ahead of any outdated stereotyping such as age or gender.[iii]
Artificial Intelligence can be used to analyse data and predict risk in a way in which no human analyst could – allowing far swifter responses based on a much more accurate and specific data set.
Investing in a team
Big Data and computerised analysis offers huge benefits to the insurance industry but it requires a team of tech savvy individuals to understand the systems and utilise them accordingly, as well as underwriters who are able to oversee particularly complex risk profiles and customer care operatives who can continue to build personal relationships with clients. Specialist recruitment agency, Aston Charles, recruits candidates with a wide range of skills, knowledge and experience, who can help you push your company forwards in an age of Big Data and disruptive technology.
Has Big Data really ushered out insurance segmentation?
The answer to this is both yes and no. Segmenting clients into categories of risk by demographics such as age, gender or job is no longer efficient. There are however, non traditional forms of segmentation that may guide insurance companies in the way that they target marketing.
It could be argued that Big Data has paved the way for the ultimate segmentation; risk profiles for every single individual, based on their unique data set. This gives insurance companies potential to appeal to new and existing customers, using information from Big Data to show customers that they are able to treat each policy holder as a unique and valued individual.
[i] Insurance Times. 2017. Insurance Times. [ONLINE] Available at: https://www.insurancetimes.co.uk/only-half-of-british-consumers-trust-insurance-companies-to-pay-claims/1425151.article. [Accessed 14 June 2018].
[ii] Karen Wheeler. 2017. Insurance Business UK. [ONLINE] Available at: https://www.insurancebusinessmag.com/uk/opinion/is-it-time-that-insurers-change-the-way-they-segment-their-customers-84528.aspx. [Accessed 14 June 2018].
[iii] Rakesh Shetty. 2017. Digitalist Magazine. [ONLINE] Available at: http://www.digitalistmag.com/iot/2017/07/19/iot-lowers-costs-improves-risk-assessment-for-auto-insurance-industry-05221322. [Accessed 14 June 2018].