Talk to senior life and annuity (L&A) insurance executives, and you’ll hear a common theme: How best to adapt to the rising customer expectations and disruptive changes underway?
Consumers, especially millennials, who are accustomed to one-click ordering on Amazon or Uber, don’t understand why buying life insurance needs to be so confusing and time-consuming. They expect simplified products, customized advice and the ability to buy easily online.
The instant economy has already arrived throughout the financial services industry. For example, Quicken Loans, which relies on a direct-to-consumer model promising a simplified application process with rapid approvals, is now the nation’s top home lender.
Unless L&A insurance businesses adopt new ways of interacting with their customers, they run the risk of becoming relics. As new digital advice and sales models emerge, their principal competitors may soon be not just traditional insurers but also a digital giant that’s looking to expand into new industries, or an insurtech startup they’d never heard of before.
Using AI to Shift to a New Model
To respond, L&A insurers must simplify the process of selling direct to the consumer, by leveraging the power of artificial intelligence (AI) technologies, such as natural language processing, machine learning, voice recognition and predictive analytics. These technologies can help insurers micro-target customer segments and then automatically develop and deliver customized product recommendations. By employing chatbots and robo-advisors, they can enhance the customer experience, streamline the sales process and slash operating costs. As technology capabilities evolve, insurers will come ever closer to the lofty goal of treating each consumer as a segment of one.
Some L&A insurance companies are already demonstrating what is possible:
- Haven Life, a subsidiary of MassMutual, allows customers to buy life insurance online in just minutes, in some cases without a medical exam, by using machine learning to analyze third-party data such as prescription and driving records.
- By applying predictive analytics to public data, Savings Bank Life Insurance Company of Massachusetts (SBLI) has eliminated the need for medical tests and reduced the average processing time from 25 days to only 24 hours.
- Consumers can get a life insurance quote from Legal & General America just by submitting a selfie photo, which is analyzed to estimate their age, gender and body mass index (BMI). Although the technology is not used for underwriting, it is helping the company attract younger consumers.
Although AI promises to provide more objective advice, as these applications continue to learn from new data, they can develop unexpected biases of their own. Insurers will need to put strong policies and procedures in place to ensure that the decisions made by their AI applications are aligned with the company’s and society’s values.
Speeding the Pace of Change
Many L&A insurance businesses, particularly those that have largely grown through acquisition, will find that implementing a direct-to-consumer strategy will require them to modernize IT infrastructures that currently consist of a patchwork of under-powered legacy systems. While some companies will choose to rely on internal resources to accomplish this, many have been dissuaded by the large upfront capital investment and time required.
For this reason, many insurers are turning to software as a service (SaaS) or business process as a service (BPaaS) solutions, which reduce the investment required since total costs are based on operational expenses (i.e., the number of policies or annuity contracts) rather than fixed capital expenditures. Insurers deploy these solutions to slash the time required to roll out new products by an order of magnitude, while reducing operational costs by 20% or more.
Change is coming fast to the life and annuity business. The insurers that are able to prosper in the turbulent days ahead will be those that embrace the customer-focused, digitally-driven business model now coming into view.
