During a recent industry briefing call, the Chief Analytics Officer of a life insurance carrier asked me an interesting question: “Should I try to get funding support for our new analytics initiative on the basis that it’s cool and sexy?”
When I prompted her about what’s sexy and cool about her proposal, she replied, “Well, machine learning is sexy, because especially in our industry, it’s the new hot thing. And it’s cool because I think we can improve how we make underwriting decisions on new policies.”
Then, I followed up with an important clarifying question, ”Do you have the technology support to implement that model, if you did indeed find a better underwriting mousetrap?” She had to admit she didn’t yet know how or whether she could implement such a new model in their production systems, which is maintained by the technology organization. She also didn’t know the best way to work with the underwriters to adopt the pricing policy changes that her upgraded model would support.
Why cool isn’t enough
Here’s why I have found cool doesn’t win the day: In many financial services firms, few executives want to be a guinea pig for an investment that is novel in their industry, especially in fiscally and operationally conservative environments like the life insurance industry. Cool simply isn’t enough.