Using Data to Differentiate Our Assets
When I had my first insurance renewal at a self storage company, I thought it would be pretty straightforward to insure some property and employees - I was wrong. As it turned out, most insurance carriers knew little about insuring the self storage category, and subsequently grouped self storage into other categories which didn't apply for catastrophe and loss characteristics. I spent the next 15 years educating carriers about the excellent spread of risk for self storage.
One concern that needed to be addressed was the classification of the property. There was no “self storage” designation for underwriters to use to calculate the exposure. Instead, underwriters picked what they thought was “close enough,” like warehousing. This classification produced incorrect loss projections for our business, leading to higher than necessary premiums. It was challenging to showcase the differentiation of a self storage portfolio, and, needless to say, it was even more difficult to get feedback on premium amounts and modeling assumptions.
However, data enabled us to start improving outcomes for our placements. After eight years, we modeled our losses against actual storms and losses, then compared our actuals with the model loss projections. We were about 40% lower than the model over an eight year period. After sharing this information with our carrier, we were able to get a rate reduction. Going forward, it would be so much better not to wait for an extended period to justify why our losses were lower, or to share granular data that demonstrates our differentiation and allows carriers to action that data more confidently in their modeling. I am excited about the capabilities Archipelago provides to enable this new future.