 "Insuring consumer trust with tech")
Have you recently got married and wish to take a policy for the spouse? Your insurance company is probably aware and will soon send you a host of options. Or, if you live in an upmarket part of town, they might also suggest upgradation of the existing cover.
Insurers are increasingly using data analytics and predictive modelling, to not only understand customer profile but to cross sell and up sell products. They are offering benefits, based on the data collected.
Karthik Raman, head of products and strategy at IDBI Federal Life Insurance, said IDBI had recently implemented analytics as a tool to improve persistency levels. “We have done this to understand how many customers will surely pay the premium, how many would need a follow-up and how many would have to be chased. Because we come to know how many will pay, this helps us save costs.”
He said IDBI were looking for strengthening of relations with customers to cross sell and up sell. Since IDBI’s primary distributors are banks, a certain amount of information can be sourced from the latter. Raman said the focus, going ahead, would be to identify the right trigger for a customer and modify the communication needs to suit this, so that each is only given the products they need.
Companies say a lot of data might already be available to them by way of association with distributors and hospitals, but the key is to use this to create relevant knowledge.
Anuj Gulati, managing director (MD), Religare Health Insurance, says the key differentiator for companies would be the manner in which data is used to create knowledge that can be used to cross sell products and suggest additional ones. Using this data, targeted offers could be made.
While a lot of information shared with hospitals and banks is being used to suggest different products at different life stages, online activity is also being tracked. For instance, if one visits a travel portal and then immediately switches to a general insurer’s website, it is likely they will be offered a travel insurance plan as the first suggestion on their homepage.
Over and above, insurers are using this to also create policies of adequate size. Sanjay Datta, chief of underwriting and claims at ICICI Lombard General Insurance, said all the internal and external data collected are meant to give better risk mitigation and providing of personalised policies.
While a lot of data collection happens through sharing, newer technologies have also enabled real-time data recording. Recently, Bajaj Allianz General Insurance launched a telematics offering, a first in the sector, to look into driving habits and to incentivise customers. The offering, called ‘Drive Smart’, is a USB device that can be fitted into a car and will provide real-time feedback on driving behaviour. Based on data collected, discounts in motor premiums would be provided. MD Tapan Singhel, said this would help incentivise those with good driving behaviour. Since motor insurance premiums are fixed on an annual basis, discounts will be offered only after data is collected over a 12-month period.
Similarly, Cigna TTK Health Insurance has launched ‘Get ProActiv India’ as part of its ‘ProActiv Living Program’. Get ProActiv India is integrated with Cigna TTK’s Healthy Rewards Program, allowing customers to earn incentives by allowing activity-tracking. Customers can track their activity through a ‘Get ProActiv’ app, integrating select wearable devices. ‘Healthy Reward’ points are then earned on the basis of the amount of physical activity, translating into lower health insurance premiums.
Expanding the horizon
Expanding the horizon
- Data analytics by insurers include looking into the customer profile and activities online
- Based on area of residence, the insurer can suggest additional policy size
- Life-stage events like marriage and pregnancy are also noted and appropriate policies given
- Health insurers also look into how fit or healthy a person is and suggest policies based on that
- Fitness apps and trackers are being used to monitor health
