SES, Leading the charge towards automated underwriting, Enabled by ATTOM.
The California-based managing general underwriter (MGU) and leading insurance provider for the residential rental investor market, SES began using ATTOM’s community data file last year, leveraging it alongside machine learning tools to better analyze risk.
Focusing on data points like crime rates, unemployment levels, vacancy rates, and more, SES was able to create ZIP code-level risk scores for properties in every part of the country.
Though other insurance providers use a similar risk scoring models, according to Harrison Burka, Director of Business Intelligence at SES, “To our knowledge, no other insurance providers in our space are investing this heavily and creatively in the application of machine learning and deep learning techniques like we are,” Burka said. “They’re buying out-of-the-box risk scores. SES’ scores, on the other hand, are proprietary, innovative, and produced entirely in-house by our data science team.”
The approach is still somewhat new for SES, but Burka believes it will ultimately reduce losses and enhance the company’s underwriting profits over the long haul. In addition, Shaun Shenouda, COO at SES commented “Our approach will also greatly improve the user experience through a streamlined submission process and quicker quote processing times.”
It’s also just one small step toward the company’s goal of full-on underwriting automation.
“Underwriting is one of the last few processes that isn’t fully automated in this industry,” Burka said. “There are rental insurance companies out there that produce quotes just based on an address. We’re trying to get there as well — only on a larger and much more complex and dynamic scale, for real estate investors and other business owners with rental property portfolios.”
According to Burka, SES considered a number of data providers before choosing ATTOM. And so far? There’s been no looking back.
“I did all the evaluations, and ATTOM provided a great value and instilled a high-degree of confidence in the quality of their data,” he said. “They’ve been very collaborative partners along the way.”
The company is currently in the midst of testing out additional data from ATTOM — the building permit file. This includes data like permit status, job costs, contractor details, and more, and could help bolster SES’ efforts to better analyze property-level risk.