SBIR Phase II: Rapid Calculation of Earthquake Repair Costs for Pricing of Building Risk

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is that it will enable a group of customers we call Risk Pricers (specifically, property and casualty insurance underwriters and mortgage bankers in financial firms) to profit from tailoring pricing on their products. They can do this by rapidly predicting financial losses for buildings having specific configurations, using the software developed in this proposal. These customers can then tailor pricing of earthquake insurance and mortgage terms based on refined analyses that we facilitate. Besides offering a clear financial benefit to Risk Pricers, this new analysis approach will also fundamentally change market forces and incentives around building safety. If a building's owner is incentivized to improve its earthquake performance (via lower insurance and mortgage costs), then high-performance buildings become more appealing and this will encourage design of better buildings. As the company's software makes more explicit the links between building properties and financial costs, society will benefit from more efficient resource allocation, ultimately leading to increased societal resilience. This Small Business Innovation Research (SBIR) Phase II project will develop algorithms and software tools that provide financial guidance to customers interested in repair costs and closures of buildings due to earthquakes. To complete the development of its tool, the company will focus on calibrating statistical models to predict displacements and accelerations in a wide range of building types, when they are subjected to earthquake shaking. The company's method for rapid estimation of structural responses utilizes principles of engineering mechanics, but applied in a domain where academic research does not focus (i.e., estimating response of a structure whose properties are not fully known to the analyst). The key identified need is to calibrate a statistical predictive model for the response of a structure that is effective over all popular construction types of interest to customers in the insurance and mortgage banking markets (i.e., light frame wood, steel, concrete, concrete tilt-up). The company will also develop loss metric and calculation outputs that incorporate insurance contract conditions such as deductibles and limits, in order to link the calculations to customers' workflows.