- Where Insurance & Technology Meet

Understanding Insurance Consumer Data: Dr. Phil Meets Stephen Hawking

Sometimes it seems that the new recipe for insurance marketing looks like something Dr. Phil and Stephen Hawking would jointly develop:  2 parts rocket science, 2 parts intuitive psychology, and 6 parts alchemy.  A couple of on-line pieces  brought this into stark relief for us recently.  Our question to you:  what path(s) are you following?

Can Insurers Use Analytics to Displace Brokers?

Our colleague in the Insurance 2023 Project, Greg Purdy, recently posted a question on the LinkedIn Group, Canadian Insurance Brokers Strategy Group, which turned into an interesting discussion on how brokers can develop and leverage customer loyalty to defend against incursions by direct marketers.  Here’s some snippets (participants identified by role below;  the actual individuals are identified by name on the Group):

Broker: I would love to understand what their customer loyalty is defined as or really on which group ?? If their basic clientelel (sic) are price shoppers and always have been well then those stats fit her model not mine. …I believe we have the best model to accomplish what you suggest at taking on the direct writers, lets do it.

Consultant: I don’t know how familiar you are with the Quebec insurance market but as a management consultant to the insurance industry coast to coast, I can safely tell you that each region has its peculiarities. In Quebec, for example, Desjardins is considered as “part of Quebec society”,  … the fact remains that across the country, despite broker efforts to date, we’re at a point in time where the broker channel has to make changes to the way it works with its customer base in order to reinforce those relationships.

Group Moderator: Desjardines operates a very effecient (sic) operation and they have invested a great deal in technology and predictive modelling. This investment is paying off on better segmentation and improved underwriting results…

At which point the discussion turned to use of analytic and predictive modelling.  As readers of this blog know, we have identified the use of analytics a a major trend for insurers.  However, we are also passionately convinced that analytics are tools, not strategies. As a former stat teacher once said to his class about a debate based only on statstics:  “You’ve got a chi-square, I’ve got a chi-square.  Someone has to make a decision.”

Do New Data Sources Replace Old?

As reported in Insurance & Technology recently, US based Nationwide Insurance has been developing a corporate data analytics strategy since 2007, and has a high degree of comfort in handling traditional data in admin systems and data warehouses, as well as Big Data in new data structures to produce a variety of statistics on customer behaviour.

The real trick is how to translate these data into actionable insights for all parts of its organization.  To this end, they have employed a behavioural psychologist to join product and marketing specialists on a cross functional team to help interpret insights from (unstructured) Big Data in combination with its existing structured client data.  Tara Paider, associate VP of IT architecture at Nationwide is quoted in the article as saying:  “Looking at big data out of the context of the information you already have about your customers and policies and products is a bad idea.”

What Do You Think?

Clearly, Nationwide (and others) are spending time and money to use new tools, but are not prepared to dispense with well established information sources (including independent distributors).  So our question to you:  How does this model track with your plans?  Do brokers see insurers seeking new relationships to leverage old and new data and relationships?  Do insurers see brokers ready to accept data insights from insurers on their customers?

Leave your comments below.