The THiNK Blog

Welcome to Part 3 of the Impact of AI series. To recap, Part 2 of this series looked at the impact of selling and distribution and Part 1 looked at the impact of underwriting and risk.

Part 3 of this series will focus on the impact of the product development phase of an insurance product. 

At a recent talk I did at the CIU in Ottawa (How’s Bragging Camp? It’s going very well, thank you), my goal was to illustrate that when training is complete for a new underwriting hire, it does not mark the end of learning. Does an existing or seasoned underwriter require less knowledge acquisition or skills training once on the job? Of course not! With changes in medical advances, industry policy changes, and new products on the market, the very nature of the underwriting profession requires learning to be ongoing. Unfortunately there are some challenges and barriers that get in the way. However, as you'll discover by the end of this article, you can create high impact learning experiences by implementing low stakes activities. Let's first explore the challenges... 

You have a gap on your underwriting team and are recruiting to fill the position. What kind of person are you looking for? What kind of person are you not looking for? While you have a set of skills and knowledge in mind, the recruiting process isn’t always as simple as finding a candidate with x years of experience or y and z qualifications. Plus, qualifications aren’t the ‘be all, end all’.

We are firm believers that hiring for fit is paramount - especially when you are hiring someone into a team environment. To cultivate a high performing team – being able to work collaboratively and demonstrate a thirst for learning are key assets.

In Part 1 of our Artificial Intelligence (AI) Impact on the Insurance Value Chain series, we looked at the impact it has on underwriting and risk. However, before an individual can be underwritten, an insurance product still needs to be sold and distributed, which is what Part 2 of this series will focus on. According to McKinsey, this step of distribution and selling is the most crowded in insurtech, with nearly 40% of startups attempting to change how consumers buy insurance. 

The Insurance Industry is changing every day. These changes present themselves in our collective value offerings, in the methods of how we are able to buy and sell insurance, or even in how insurers are able to underwrite and classify risk. Regardless of the change, they all have implications on the evolving roles of Life Underwriters.

The hottest category of Insurtech in 2017 has arguably been artificial intelligence (AI) as 5 of the largest 15 deals have gone to AI startups. This builds off a strong 2016 that saw 45% of investments in Insurtech going to startups utilizing big data analytics and AI (Rise of the Insurtech – Accenture report). The increased interest and investment in AI is largely due to the prevalence of human interaction and manual processes throughout the insurance value chain.

As you may recall, I recently wrote a blog post on Sudden Cardiac Deaths in Young Athletes. In that article, I walked you through the history of marathoning, the (potential) increased risks for young athletes, and the particular case of Ryan Shay. We left off with the question:

Are athletes in fact at increased risk for sudden cardiac death?

Although sudden cardiac death is the leading medical cause of death in athletes, it is rare. Most athletes do not “drop dead” while competing in their sport.

Sudden cardiac death (SCD), a very quick unexplained death due to the loss of heart function, is the leading medical cause of death in athletes.

As both an underwriter and an athlete, this sounds scary!