Insurance Analytics & How its Useful in Insurance

Feb 22, 2019 | 1 month ago | Read Time: 4 minutes | By iKnowledge Team

Data analytics is changing the way that insurance companies are interfacing with customers and the types of covers that they are offering them. Insurance covers are getting more customer-centric.

If a life insurance company called you up and instead of just trying to sell you a fancy cover at a reduced price told you that you had the liberty to decide on the type of cover you wanted as a customer, you could decide the inclusions and exclusions and what is more, you could even decide the premium you wanted to pay based on the cost, what would you think?

That it is a pretty utopian idea?

Well, that could be a reality because insurance companies globally are increasingly using the customer data that they get from insurance professionals, insurance agents and financial planners to devise life insurance plans that are uniquely customised towards the needs of individual customers.

For instance, two 30-year male individuals, both with a family consisting of a wife and two kids each, but living in different cities, one a bank executive and the other a freelance photographer with a hectic travel schedule would not be sold the same kind of a life cover or a health cover.

That is what data and data analytics does for the insurance industry, which is increasingly becoming customer-centric.

Customer Insights

At present insurance policies are sold on the basis of age, a rudimentary medical history (in most cases even that is dispensed with), the amount of cover decided based on the individual’s disposable income and how much he or she is willing to pay annually as premium.

Claims data, customer (profile) data, etc., has always been available but all along, this data has been sitting unattended with underwriters (those who evaluate the risk and evaluate the cover needed based on that) not having the wherewithal to sift through the data and analyse them. However, with sophisticated computer systems it is becoming easier to access the data and run them through analytics programs and gain insights on customers from that.

Big data analytics firm, Exastax[1] says, “Gaining customer insight with big data analytics not only provides predictions about when a customer is likely to leave, or shapes a customer’s policy; it can also help insurers to develop trusted relationships and engage customers in the right way with the accurate information,” adding that it helps in solving the problems faced by customers while it augments marketing efforts by facilitating in the cross and upselling of products.

A person who exercises regularly and has a healthy diet should not be the same risk as a person of comparable age but with an unhealthy lifestyle. Or, a person who works in a hazardous environment will not be assigned the same risk as opposed to one who works in a safe office environment. A person who drives recklessly is a higher risk than someone who is a cautious driver. Insurance companies, armed with this kind of data, are now tailoring their products to factor in these variables.

Customer-centric

An insurance agent with access to information on a particular client can get alerts on a change in the client’s circumstances and assess whether the existing coverage is adequate or there is need for an increase. The client will appreciate a call from the agent at this point since he will feel that the insurance agent is acting in his interests rather than just trying to make a sale.

Some insurance companies in the US have introduced portals for their customers where they can do self-servicing of their policies, including topping up their cover, adding or deleting riders and so on. Data analytics and automation is leading to handing over more control to the policyholders.

iGuarantee Insurance Plan, for example, allows individuals to avoid tedious paperwork and buy their policies online without any medicals too. It’s a hassle-free process. This policy has guaranteed annual payouts at 135% of the annualised premium on maturity, while on death the insured gets 10 times the annualised premium.

Insurance companies are also providing their customers with apps that can track their activities throughout the day and this feed can be analysed by them and help them in pricing their products accordingly.

In India, there has been an attempt to use telematics in the case of vehicular insurance but this has not taken off, largely due to issues connected with restrictions on data privacy, the cost of the tracking devices as well as that of pricing of insurance policies. Indian regulations mandate fixed price premiums and there is no scope for variable premiums.

Big data is also helping insurance companies to phase out expensive products that serve no useful purpose (except to agents who earn fat commissions) or covers that are not popular.

A spinoff to the monitoring of customers is that it also helps in influencing customer behaviour. According to a McKinsey report, “Real-time monitoring and visualization is fundamentally changing the relationship of insurers and the insured. By agreeing to let insurance companies monitor their behaviour, customers can learn more about themselves, and insurance companies can leverage the data to influence behaviour’s.[2]

Citations

[1] “TOP 7 BIG DATA USE CASES IN INSURANCE INDUSTRY”, Exastax, April 2017

[2] ‘Unleashing the Value of Advanced Analytics in Insurance”, McKinsey, Aug. 2014

 

II/Feb 2019/4845


Calculate premium for your Term Plan

  • Y N
    • Annual Income
    • Sum Assured
    • Select Cover Upto Age
    • Name
    • Mobile
    • Email ID
Your Annual Premium for Aegon Life iTerm Insurance Plan
Prev
cyber security insurance What is cyber security insurance and why is it gaining in popularity
Next
Five Ways to Leave behind a Financial Legacy for Your Children

RELATED ARTICLES