Pinpoint Helps P&C Insurer Identify the Presence of Wood-burning Stoves in Homes

How a Homeowners Insurance Carrier Identified Undisclosed Wood-burning Stoves causing Premium Leakage and Total Fire Losses

Published in Bryan Falchuk’s The Future of Insurance: From Disruption to Evolution Vol. III, Pinpoint Predictive partnered with Ohio Mutual Insurance, a regional insurance carrier, to help identify undisclosed wood-burning stoves that were leading to total fire losses on insured homes. As a carrier that is always thinking outside the box to find ways to use technology to augment processes, Pinpoint Predictive offered just the solution they needed.

The Problem

High-severity fire losses caused by undisclosed wood-burning stoves. There was an inability to find undisclosed and newly installed wood-burning stoves for loss mitigation and premium adjustment, and the insurer realized they needed to get a handle on the problem.

The Solution

Build a Loss Prediction Model that predicts an individual’s likelihood of owning a wood-burning stove. Pinpoint would score an entire book of business to target outreach to the top 10% insureds who are most likely to own a wood-burning stove. 

Partnering with Pinpoint

Ohio Mutual came to Pinpoint needing to find undisclosed wood-burning stoves. The carrier struggled for two years trying to find the information that would reduce the instances of total fire losses happening on the homeowners book of business. What they discovered when a loss occurred, was the reason behind the total fire loss was wood-burning stoves they were unaware of, and the presence of the stoves had never been made known to the company.

Ohio Mutual was unable to fully underwrite the situation of these wood-burning stove instances, and for them, it was a safety issue and they wanted to provide the additional value of working with customers in making certain wood-burning stoves were safe to use in the home. The team would be able to check if they were properly installed, properly maintained, and inspected on an annual basis.

Essentially, take all the necessary steps to protect the assets and the safety of their insureds by asking all the critical underwriting questions a homeowners insurance carrier would, in the likely event a risk such as wood-burning stoves existed.

Another issue they faced, particularly with any carrier carrying a mature book of business, there was a possibility they had been insuring a home for the last 20 years, but did not know 10 years ago the homeowner installed a wood-burning stove. The situation was challenging.

How Pinpoint Helped

Pinpoint predicts the behavior of an individual and does it based on understanding the behavioral fingerprint of an individual. When Pinpoint and Ohio Mutual began working together, the question arose, “Could you be able to build a prediction to predict the likelihood that someone owned a wood-burning stove?” It was an intriguing idea, and the first time Pinpoint had built this type of prediction. 

The Custom Prediction Build

Pinpoint and Ohio Mutual embarked on building the model together to see how this type of model performed. Pinpoint used its model-building processes and essentially trained the model as a custom prediction on people Ohio Mutual knew owned a wood-burning stove and then trained it on based on those they knew did not. Similar to any of Pinpoint’s custom prediction models, the process involved blind validation, where the carrier does not disclose the records for the custom prediction. In this way, the carrier can validate the model lift prior to moving into production. 

The Old Way Versus a New Way

Traditionally, identifying these types of risks, let alone capturing them like a wood-burning stove, is handled by a carrier’s direct outreach to every insured in the book, and sending an underwriting questionnaire asking if one existed in the home.

Unfortunately, questionnaires carry an extremely low response rate, require heavy underwriting resources, and are very expensive. Underwriting teams must handle the back-and-forth of every single person who does confirm the presence of a wood-burning stove, and then engage with those customers to fully develop the course of action to accurately underwrite the policy.

The goal then was to provide Ohio Mutual a more efficient way of identifying undisclosed wood-burning stoves in its book. 

A More Efficient Approach becomes Available

Pinpoint offered Ohio Mutual a more efficient option that was driven by the purpose to provide Ohio Mutual a more efficient way to manage the outreach effort and get as targeted as possible on the actual individual homeowners they would be engaging in the wood-burning stove inquiry.

The Outcome

When the custom prediction came through, the results were astonishing. Not only was Ohio Mutual able to focus highly targeted outreach efforts on the top 5-10% insureds who were predicted to likely own a wood-burning stove, they ultimately identified 200 wood-burning stoves they had no previous knowledge were present in homes. Keep in mind, Ohio Mutual is a mid-size regional carrier and those numbers accounted for 21% of the policies they received information back on; which was far above market average wood stove penetration and an extremely unexpected discovery.

In addition to the wood-burning stove discoveries, the targeted outreach helped improve the efficiencies of the carrier efforts, as well as the labor and time requirements typically that stem from traditional questionnaire outreaches.

Through the process, Ohio Mutual was able to fully underwrite all the scenarios, do their due diligence to ensure professional installation of the stoves, and were able to work with customers on loss prevention and loss mitigation.

Premium Leakage Identified

This was a case of premium leakage identified, and although the insured would be paying a higher premium, the amount was negligible compared to the overall preventive financial impact that was gained due to how many possible total fires were avoided due by identifying these new risks.

The project outcome for Ohio Mutual is another great testament to how P&C insurance carriers can utilize the latest data and the latest in predictive modeling to optimize processes in a way that makes considerable financial sense and enables insurers to provide the best service possible for their customers.