You fall ill (or worse). You or a family member files an insurance claim. The insurance industry, with two centuries of embedded actuarial experience, calculates what payout your policy entitles.
So far, so familiar.
What those actuaries don’t know is that you were about to fall sick, break something or expire. They can make assumptions, based on your age, your unsavory lifestyle habits, your gender, your income, your home. And they can make a guess about average incidents requiring a claim. Your payout might come under or over the odds. But it’s all about mean reversion on a grand scale.
And your only incentive is to make sure the insurer coughs up the money – but only after you’ve suffered something unpleasant.
Steve Monaghan thinks we can do better than this – to the benefit of the insurers that reinvent themselves, and to the benefit of their policyholders.
Using A.I. to reimagine insurance
“What if, instead of waiting for people to fall sick or die, we use customer information to intervene?” he asked DigFin.
Monaghan is chairman and CEO of Gen.Life, a Hong Kong-based artificial-intelligence company that is working with AIA in Asia and American Family Insurance in the U.S. to develop a new business model for the industry.
The company’s engineers and data scientists are in the U.S. but it sees its business prospects in high-growth Asia. Monaghan is still building the team, and in August hired Daniel Tu as the company’s president; Tu was previously chief innovation officer at Ping An Group of China.
Insurance is proving hard to reimagine, because so much of the industry’s success is built around selling complex and opaque products through wholesale channels, such as agents or banks. Monaghan, who served as DBS Bank’s chief innovation officer for two years, says the insurance industry is a decade behind banks when it comes to digitization.
Making U.X. easy
But the same protests against digitization – that a product is sold not bought, that consumers don’t buy directly, that sales depend on personal relationships – are the same. “But if the price is right and the experience is good, then consumer laziness beats a trip to the store,” he said.
He is working with AIA (where he also once served as its innovation chief) to make the customer experience not just transparent, but easy and proactive. And unlike with banks, insurers have a chance to use technology to earn kudos from their customers.
“The idea of waiting for a claim makes no sense,” he said. Technology can allow an insurer to identify risks early. Do that, and the company can reduce payouts while winning customer loyalty. “The lifetime value of a customer will increase,” he said.
Network effect
To realize this goal requires A.I. tools drawing from many sets of primary data, which lets an insurer generate a starting benchmark for pricing risk. Although a given insurer has some customer data, Monaghan says the endgame is to put multiple carriers on a network. Getting the most out of A.I. requires drawing on exponential gains in processing, data and network effects.
“Gen.Life is working with multiple insurers in order to become the best risk manager in the world,” he said. In addition to AIA and American Farmer, he says he has a pipeline of another 30 insurers and reinsurers.
If he can get more of these on board, his company becomes something like a pooled R&D hub that can establish a new baseline for pricing risk – a baseline that machine learning will continue to make more accurate. From there it can create software that it can license and come up with products that are more proactive.
AIA is an investor in the company – although this was a relationship forged under AIA’s previous CEO, Mark Tucker, and its previous COO, Simeon Preston. The new leadership under CEO Ng Keng-hooi, including Biswa Misra, group technology and operations officer, may have different priorities. Monaghan declined to comment on his relationship with AIA.
An AIA spokesman said, “AIA is an investor in Gen.Life and when available and fit for purpose we could use some of the potential technology outputs from Gen.Life where appropriate…We have a clearly laid out digital strategy and if or when it becomes appropriate to use Gen.Life as a part of the strategy, we will do so.”
