New Vanity Metrics vs. Old School KPIs: Evaluating InsurTech Performance

Since I began a quarterly discussion of U.S.-based InsurTech carriers’ financials based on their public filings last year, many have responded that these players needed to be evaluated on other metrics too. I agree, so let’s look at one of those measures and talk about some questions to determine if the measure really stacks up.

Misleading Vanity Metrics

The insurance value chain is complex and difficult to compare across models. This can lead to comparisons between very different companies. Take these two hypothetical companies:

• Company A, aka Flashy Startup Insurance Co., uses outsourced call centers, bots, incessant Instagram ads, comparison rater websites, third-party claims administrators and a slick app. It sells only one line of insurance—personal—with low limits and has no complicated old claims (yet). If your house burns down, you open an app and wait. The company has a low expense ratio, high acquisition costs and a high loss ratio.

• Company B, aka Old Traditional Insurance Co., uses a mix of direct sales, captive agents and independent agents. Claims are handled mostly by agents and in-house staff. If your house burns down, your agent turns up with a reservation for a nearby hotel, billed directly to the insurer. It sells 12 lines of insurance including small commercial and offers a wide range of products within each line, with bundling encouraged. The company has a high expense ratio, high acquisition costs, strong customer loyalty and losses less than the industry average.

A “vanity measure” could easily make one of these companies look better than the other.

The startup, for example, may claim performance several times better than the incumbents on a “policy per human” KPI, considering in the count of “humans” agents and brokers.

Why does a policy-per-human number matter at all? And why is more policies per human better than fewer?

Company A and Company B are two different business models, with two opposite approaches about humans—neither of which is necessarily best. I say this despite the fact that I wrote a heartfelt defense of the model based on agents, brokers and other distribution partners a few months ago—”At Long Last, an Insurance Company Proud of Its Human Agents—and Telling the World,” co-authored with Steve Anderson.

To measure efficiency, I prefer to use the two traditional components of the expense ratio:

• General operating expense ratio = General operating expenses ÷ earned premiums
• Acquisition ratio = total acquisition expenses divided by the earned premiums (for a high-growth company, it’s acceptable to do the division by written premium). This metric includes advertising, other marketing expenses, commissions and other distribution expenses. However, this number (like CAC, or customer acquisition cost) can be difficult to compare. For example, are fixed marketing expenses included or excluded? And the economics of customer loyalty are different between direct (where initial CAC is high but renewal is low) and agent sales (where initial CAC is lower and variable but renewal commissions are significant).

I love numbers and, as I shared in an interview with Carrier Management, the absence of quantitative elements in self-promoting website articles, conference keynotes, white papers and social media exchanges has been one of the reasons for starting the publication of articles about the full stack U.S. InsurTech startups.

Although I’m sometimes described as a “critic” or “cynic” about InsurTech companies, I’m only critical of the misuse of numbers. I’m a big fan of those who get the old-school insurance KPI right. I’d love to see the innovation succeed in the insurance sector, and I wish all the best to these three players and their investors.