Getting Millennial To Purchase Life Insurance

When it comes to life insurance, many millennials understand the financial risk of not having it — the need — but might not be aware of what kind of policy they need or how to procure it. Current obligations, like student loans, mortgages and other debt, also can be roadblocks. It's about affordability and share of the wallet. Equally inhibiting are the lack of awareness about what they need to secure their financial future and how to go about doing that.

As I've learned while leading digital transformation at my company, technology could help clear several of these roadblocks and enable insurers to create a personalized customer experience that includes awareness of policy issues and ongoing engagement. Artificial intelligence, specifically machine learning on rich data sources and natural language processing, and an integrated environment driven by an application programming interface are the key technology components in this context.

Let's get to the roots of life insurance: What's the purpose? At its core, insurance provides peace of mind. This fundamental realization will help insurers navigate the roadblocks and be available to help millennials meet their financial needs through a simple and intuitive approach. Here's how technology can help remove some of the roadblocks for millennials who want life insurance.

• Consumer engagement: For millennials, their peer networks or service providers can be their trusted channels. Chatbots driven by AI and integrated with social media platforms or retail websites can help insurers facilitate discussions with customers to determine their needs. Chatbots leverage natural language processing to engage with the consumer while applying needs analysis algorithms based on available products to provide personalized options. Through ML, chatbots can be continuously trained to enhance consumer engagement.

• A simpler and faster application process: The process of data collection and underwriting could be simplified, specifically for low-face-value policies. Instead of consumers filling out applications, insurers, with consumers' consent, could prefill the application with data from different sources. Insurers could start integrating with the increasing number of data aggregators from either personal health records or data from health exchanges. A competitive risk score algorithm could be modeled based on regulatory and the insurer’s underwriting guidelines. A rules engine-based solution combined with the risk score could automate the underwriting process. There are also other innovative solutions now available to automate underwriting. For instance, Chronos from Lapetus Solutions simplifies underwriting by using selfies. With an open architecture, insurers can integrate with a partner ecosystem through which standard APIs could realize quote to policy issuing in less than five minutes.

• Finding the right product: With the amount of consumer data available, insurance carriers could start by creating a risk profile for relatively smaller demographics than traditionally calculated. Make the product personal based on the customer's life stage and lifestyle at a point in time. Insurance technologies like Human API and PHR Plus provide an aggregated view of an individual’s health profile, which could be obtained with the individual's consent. Combined with publicly available demographic information, actuaries could take advantage of the ML technologies to help them model variations of a base product, which then could be configured based on individual needs. While Microsoft Excel is still the predominant tool in the actuarial world, there are explorations even beyond R and Python into machine learning technologies like DataRobot.

The challenge that insurance carriers will have with the predominant legacy technology landscape is the ability to launch products and/or variations in a short time frame and the agility to experiment, learn and change rapidly. Implementing new technologies will take time and effort. To help with this process, consider leveraging an existing ecosystem with a third-party administrator that has a digital platform architecture and can extend that with capabilities from other insurance technologies and third-party services. (Full disclosure: My company is one such administrator.)

Overall, many millennials believe they need to protect their financial future. They just need a partner they can trust: someone who's interested in their well-being and not out there just to sell an insurance policy. Take interest in the overall well-being of the individual and in giving them peace of mind.

Extend the leverage for AI and ML beyond initial customer engagement and into the application process -- and even into modeling a personalized product. Use APIs integrated with ever-growing insurance technologies and third-party services for both data and the capabilities to make customers aware of how their needs can be met, reach out through customers' trusted channels, build value-added engagement, personalize the products and simplify the application process. In short, provide customers with peace of mind.