Kavitha is a Data & Intelligence leader with 25 years of experience in the Life Sciences and Insurance industries. With over two decades of global experience with Cognizant technology solutions, she has experience performing various roles. Her accomplishments include driving double-digit growth through offering based sales, managing large-scale programs, applying lean startup methodology to turn ideas into innovative software products, and playing an advisory role in helping clients monetize their data and digital transformation. As the Global Offerings and Products leader in Data and Intelligence practice, her focus is to drive rapid business growth through Data Modernization and Intelligent Decisioning offerings. In addition to being the Alliances Leader, Kavitha enables solid partnerships and alliances with cloud, data technology, and AI partners worldwide.
Kavitha Lokesh
Vice President @Cognizant Business & Technology
All Sessions by Kavitha Lokesh
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NDR June 8 2021
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15:40
Increasing Accuracy of Industry Classification for Commercial Insurers Using Ontologies
15:40 - 16:20A goal of commercial insurers is to accurately classify small businesses according to the risks they face and thereby determine the correct insurance premiums. Setting the proper compensation is essential because charging too much or too little can harm insurers and their customers. 50% of the business applications required the industry classification code correction. This mainly was a manual exercise of looking up business details on the internet or purchasing business classification codes from 3rd party providers. The recent advancements in computational power and machine learning have led to vast improvements. However, the accuracy level was still less than the industry norm until the Cognizant team experimented with business ontology. The Cognizant team coded the ontology model for restaurant business using the NAICS and ISO industry manual. With details around the business name, address, and URL Cognizant team extracted the data about the company from its corresponding website and 3rd party data providers. It was able to classify the restaurant business with >90% accuracy. This session describes ontologies and their use in computational reasoning to support the precise classification of small businesses for insurance applications.