Modern consumers are used to having everything at the touch of a button – including personal loans and insurance policies. Gone are the days when insurance agents would visit prospects with lengthy forms and show them various projections with paper and pen. Also gone are the days when insurers would hire telemarketers in bulk to call hundreds of individuals daily with insurance offers.
Today, artificial intelligence-based tools have changed the face of the insurance industry in almost every aspect. From targeted marketing to offering insurance products based on an individual’s lifestyle, age, and profession; online sales, form filling, and KYC; dynamic premium setting with data analytics; and quick claim settlement using chatbots – data is undoubtedly the bedrock of the modern insurance industry.
A seamless user experience, which is fast and reliable, also adds to an insurance company’s bottom-line by improving customer engagement and retention. McKinsey & Company recently reported that US auto insurance companies offering the best customer experience were 30 percent more profitable, recording two to four times more growth than technology-agnostic competitors with an inconsistent customer focus. The same report added that satisfied customers are 80 percent more likely to renew their policies. With data-based insights, it becomes possible to improve the customer experience through digital underwriting, behavior-based benefits, claims prevention, etc.
Data Analytics in Digital Underwriting
As one would agree, there are several factors that an insurer must consider before finalizing the premium and risk cover for any particular client. Risk assessment remains most important to optimize the premium and coverage. Yet, the assessment needs to be swift and accurate to ensure profitability for both the insurer and the insured. Using AI, it is possible to crunch millions of data points in just a few seconds to ensure both accuracy and speed in underwriting. Let’s see a few use cases of data analytics in digital underwriting in different arms of insurance:
Insurers offering home insurance must assess the risk associated with the property, its integrity, and the history of the location in terms of theft and natural calamities. Zensar’s IDRIS (Intelligent Data-Driven Insights for Insurance) makes this process extremely quick and accurate by using telemetry for gathering data from specific locations and automatically transmitting it for monitoring and accordingly incentivizing the policyholders.
Many builders are using IoT sensors in construction, which helps monitor the structural integrity of a building, such as determining the water content in the basement at any time and other such aspects. It is also possible to place a virtual marker at a property site using computer vision and map it to the insured’s policy for enabling first-level authentication in case of any flood or fire.
Technology is also helping in scheduling surveys. During a natural calamity, surveyors have a difficult time assessing the damage. However, with advanced meteorological services, insurance companies like RSA Group are monitoring weather changes to detect significant events. This equips the firm with early warnings on calamities to keep a team ready to work out best how to provide services in the affected area.
Besides fixing the right premium, there are other areas where insurers face issues, like:
- Failure to detect fraudulent or over-inflated claims
- Errors in payments made out to claimants due to disparate data systems and excessive reliance on manual processes
Data analytics is being used to set up behavior-based insurance models, wherein good behavior is rewarded, and negative behavior is penalized through dynamic pricing. This is very helpful in health and vehicle insurance. In the health insurance vertical, this not only allows insurers to cover their risk better but also motivates the insured individuals to adopt healthier and safe habits. For example, for health and annuity insurance, past medical reports can be considered along with real-time data from wearable devices to optimize the premium. To add more value, some insurers are also sharing pre-emptive notifications on health, such as sleep patterns, heartbeat spike, etc., with their customers to improve their health and prevent unnecessary claims.
In the automotive industry, telematics can be used to keep a record of driving speed and behavior, which will automatically impact the risk cover and associated premium for both car and driver insurance. The idea has led to usage-based insurance policies or driving-behavior score driven policies that link premiums more closely with actual individual driving performance. This drives affordability for low-risk drivers by allowing them to control their premiums by improving their driving habits.
Besides risk assessment, another important aspect is customer retention – which can be driven through technology like data-based insights for customized product recommendations. This can be followed throughout the customer lifecycle wherein insurers can share product recommendations depending on the age and stage of an individual. Faster risk assessment, personalized insurance products, contactless application processing, and swift online claim resolution are some other ways in which data-backed models drive customer experience and retention.
Fast-tracked underwriting is yet another aspect of customer retention that deserves more attention. Here, we would like to cite the example of life and annuity insurance. Currently, youngsters (mostly under 30) benefit from a fast-tracked underwriting process for life and annuity insurance. Mostly, they don’t require any medical check-up for term-based plans, if they don’t smoke or have any ongoing medical issues. However, people in every age group are hard-pressed for time, and AI-integration can extend this facility to other age groups as well. With the advent of remote diagnostics, it may be possible to dispense away with medical tests altogether for older individuals entering into a term plan by collecting both historical and real-time data about their health and accordingly assessing the underlying risk.
How Zensar can help Insurers
Zensar’s IDRIS is a plug and play platform to fast-track the underwriting process and help insurers identify new markets and enable behavior-based customer segmentation for targeted marketing campaigns. We have developed various AI-based solutions for different industry verticals, particularly property, automotive, and health, to help organizations meet their evolving customer expectations and their business goals. Insurers looking for a data-based solution to turn around their business can get in touch with us to know more about IDRIS.