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holistic planning
program. Dacadoo’s program is white labelled, so cus- tomers can interact with the insurance brand.
Wellness programs align with an insurer’s objective to be relevant to the client when they’re healthy, not just when they have a claim. “You don’t have to be sick or dead to benefit from insurance,” Hill says.
He describes wellness programs as win-win, because clients get healthier and save insurers money. The pro- grams can also benefit hard-to-insure clients with existing conditions or family histories of disease: if those clients share their health data, insurers could potentially include them in their risk pools at better price points, Hill says.
Wellness programs can also help set advisors apart, he says, because they transform a transactional exchange — buying life insurance — into one that fulfils higher- order needs (such as improved health). While it can be difficult to follow up with a client about an insurance prod- uct that essentially doesn’t change, advisors can check in with a client using a wellness program to chat about their experiences, setbacks and successes.
Insurers might even feed advisors relevant client data (assuming clients opt in to share it), such as health score increases. Wearables thus create “avenues for more upsell and cross-sell” of insurance products, Hill says.
It also falls to advisors to explain how tech innovations like wearables work and comply with privacy laws, says James Colaço, partner, national insurance sector leader, at Deloitte in Toronto. He expects advisors will play an important role in the distribution and adoption of client- focused innovations.
Hill says there is typically a segment of clients who won’t share their data because of security concerns.
That segment might shrink as privacy regulation evolves globally, allowing clients to remain owners of their data. (Right now, insurers own client data.) Dacadoo is ready for this trend: the platform complies with Europe’s Gen- eral Data Protection Regulation, and client data can be permanently deleted.
Those who share data might also benefit from dynamic pricing of group life and health insurance, based on wellness program participation. Dynamic pricing has been available globally for decades and in North America for about five years, Hill says. Sood says he expects it to be relatively common by mid-decade.
As insurtechs continue to solve client needs, trad- itional insurers will look to work with them, Sood says. “More and more insurance companies are identifying the right places in the value chain to partner with tech startups and leverage their capabilities.”
AI-enabled service
Many insurtechs harness artificial intelligence (AI) to analyze massive amounts of data and make accurate pre- dictions. In Prediction Machines: The Simple Economics of Artificial Intelligence (2018), authors Ajay Agrawal, Joshua Gans and Avi Goldfarb explain that AI lowers
the cost of prediction, allowing it to be widely applied
to problems not traditionally considered prediction prob- lems (such as navigation and translation). The result is widespread disruption.
While AI disruption will ultimately require that some businesses upend their strategies, others can use AI
to execute their current ones. The latter is likely true of insurance, which has always used prediction, says Gans, a professor of strategic management at the University of Toronto’s Rotman School of Management.
He says he expects AI to “help the insurance industry but not disrupt it.” For example, as noted in the book, arguably the most important marketing activity for insur- ers and financial services firms is managing customer churn. “The first step in reducing churn is to identify at-risk customers,” the authors write. “Companies can use prediction technologies to do that.”
Dacadoo, for example, has plans for further client engagement. As the platform partners with more insurers and gains access to more data, its AI will be able to pre- dict how long it takes a client to change their mind after refusing a suggested offer from its chatbot. Clients may also get “a future look at themselves” as AI predicts what their health scores could be if they achieved certain goals over the next three to six months, Hill says.
Leveraging data for advisors to incorporate into cus- tomized advice is “the next frontier,” Sood says.
This will allow advisors to have “richer, better con- versations with their clients,” Colaço says. As mobile platforms improve, advisors will receive real-time data on the client’s needs and preferences, the client segment and relevant market characteristics. As a result, he says,
Who says insurance is boring?
Globally, insur- ers are high-tech leaders, not staid institutions. China’s Ping An Insurance, one
of the world’s largest insurers, “offers something for everyone,”
says Rohit Sood,
a senior partner
at McKinsey & Company. In addi- tion to insurance, banking, asset management and healthcare servi- ces, the insurer is a tech superstar, with several star- tups and mobile apps to its name. For mobile loan approval, for example, a credit app assesses appli- cants’ micro- expressions within milliseconds for signs of lying dur- ing the application process.
Such apps require harnessing the power of artificial intel- ligence. “Some insurers are getting better at using big data,” Sood says. “Others still don’t know how.”
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