(Image source: NeuralMetrics SmartRatio page.)
Nationwide (Columbus, Ohio) has selected NeuralMetrics (New York) to help agents serving the small commercial segment save time in the quoting process, improving their profitability as they focus on growing their businesses, according to a joint statement from the companies. NeuralMetrics is an InsurTech data provider using natural language processing to power a real-time quoting experience. The company’s Smart Ratio platform uses machine learning to extract actionable information from hard-to-access, unstructured public data.
Nationwide reports that it has deployed NeuralMetrics technology to boost its small commercial quoting tools, now enabling agents to enter client information just once and leverage pre-fill data to evaluate underwriting exposures and quickly generate a precise quote.
“Small commercial accounts are an important growth segment for many independent agents, but historically many have shied away due to high time commitments and other factors,” comments Dawn Thompson, AVP, expedited underwriting, commercial lines, Nationwide. “With the NeuralMetrics tool, we’re able to streamline the quoting experience for agents serving small commercial clients, creating more lucrative opportunities to grow their books of business in the small business sector.”
Thompson adds that the key to the technology’s success is ensuring accurate inputs on the front-end. “When the initial information, like business name and location, is entered accurately and the business is visible online, we’re able to achieve a 70 percent success rate or higher with bypassing the data entry and classification processes to provide a fast and accurate experience for agents and their customers,” she says.
Customer-Centric Experience in Small Commercial
“Through our partnership, NeuralMetrics had the opportunity to work closely with the Nationwide team and imagine a customer-centric experience in small commercial,” comments Prakash Vasant, CEO, NeuralMetrics. “Together we were able to build a way for underwriters to automate much of the classification work and improve the transparency to the underlying data source that validates underwriting decisions.”