As part of the MBA in Risk Management and Insurance at the Wisconsin School of Business, students interact with and are mentored by an Advisory Board of experienced experts in the field. We all spent a full day together on Friday, October 26, 2018. A major portion of the day involved RMI student facilitation of discussions focused on Insurtech, Artificial Intelligence (AI), and General Data Protection Regulation (GDPR). With professionals such as Phil Hoffmann of AON Risk Service, Dan Kaiser with CUNA Mutual Group, Christy Kaufman at American Family Insurance Group, Andy Nottestad at United Airlines, Chikara Sakoda with Seven Corners Insurance, and Amy Yates of Boston Consulting Group, the discussions were rich and lively and informative.
Jenna Herr (MBA ’19) and Mike Mansell (MBA ’19) started off the discussion with the hot topic of Insurtech, sharing how traditional insurance firms are reacting to Insurtech and asking the board members how their companies approaching opportunities and challenges arising out of technological advances. I found Dan Kaiser’s comments especially thought-provoking. He talked about “the innovation paradox,” which is the need for companies to keep up with changing technology in the long run, while still fine tuning the existing models to increase profitability in the short run.
Andy Nottestad added his perspective that it is important not to lose focus on the basics of insurance. Technology speeds up the process for sure, but in some areas, like claim adjustments, customer service may add critical value.
As the conversation continued, it was interesting to see differing views around the table. While one suggested that corporate innovation could be the solution to many fundamental problems, another worried that a bot will not deliver services equivalent to those involving human interaction with the customer.
This led the discussion towards AI. We focused our discussion on the potential for bias in AI, due primarily to the source of data used to train the bot. AI programs often exhibit racial and gender biases because the data used as input come from situations where those biases exist. Bias is a part of the human condition; recognition of those biases is critical as we move forward with AI and any other type of technology.
The conversation became even more intriguing as we discussed big data, monetizing and selling data, data privacy, and regulation changes focusing on issues beyond compliance. Our conversation about GDPR was the most animated of the day. We sensed that each of our Advisory Board members is affected by the regulation, generating the lively discussion.
The meeting was an active conversation on contemporary topics, involving a variety of perspectives coming from the industry experts and the student body. To top it all off, we received valuable advice about career management and negotiation. For me, this meeting was a unique opportunity to leverage the varied perspectives of the board members and analyze their views. I perceive that it resulted in actionable items for both the students and the Board.