Diya, digital intelligence for small business insurance customers Qorus Innovation in Insurance Awards 2021

Diya is the sum of all digital intelligence powering the buyer journey for small business customers at B2Z Insurance. The name, Diya (pronounced as dee-uh), is derived from Hindi: "dia" means “lamp” or “light.” For our customers, Diya’s “light” takes the form of an intelligent guide providing education on coverage and mitigating pain points at the source to outclass competing experience. Going beyond an AI Chatbot, Diya provides help at the source of necessary pain points in insurance coverage risk assessment. It also creates a personalized and optimized experience throughout by utilizing multiple technologies and data sources. It is not a fixed technology or singular process: We consider Diya to be the sum of all our digital intelligence, made “better, faster, stronger” by machine learning. Our First Use Case: Selecting the Correct Business Classification Code Business classification is important to both the underwriter and the customer: the underwriter can correctly assess the risk, while the customer is served coverage and pricing that best fits their business. As we reviewed the customer behavior and actions taken throughout the quoting engine, it became clear business class codes were a point of confusion. At that point in the workflow, customers either lingered far longer on that page before continuing on, or they dropped off entirely. And it’s not a surprising finding when you consider there are over a thousand North American Industry Classification System codes (or NAICS codes) and potentially, separate underwriting identifiers used to properly classify and rate the business risk. Building and launching a digital quoting process end-to-end isn’t a destination, it’s a continuous journey of learning, innovating, and deploying. Once launched, we studied recordings of on-site consumer behavior to find areas of confusion in terms of design, verbiage, and overall understanding. It is this post-launch analysis that led us to our first Diya use case and will help light the way to better understanding as a “Do It Yourself Assistant.”