Data and information is exploding in the insurance industry. Is the growth of data from third-party and digital “data exhaust” (from social, multi-media, telematics, sensors and other devices) helping or hindering the settlement of a claim? Understanding and interpreting this information through advanced analytics, visualization and “learning” methods is of strategic importance to claims operations to ensure claims are validated and paid appropriately while minimizing fraud and leakage. Additionally, the importance of customer ‘claim sentiment’ is a key component of the customer satisfaction equation. During this session we will discuss techniques and customer use cases to drive business value from your claims data through advanced analytics and machine learning enabled by Hadoop.
Cindy Maike is GM of Insurance at Hortonworks, and is responsible for the center of excellence for insurance and the go-to-market strategy for the industry. She has over 25 years of finance, consulting and advisory services experience in the insurance industry assisting clients globally with their business and IT strategy with a specific focus on the business strategy and the usage of analytics to drive results.
Dr. Gray is CTO at Skytree and Associate Professor in the College of Computing at Georgia Tech. His work has focused on algorithmic techniques for making machine learning tractable on massive datasets. He began working with large-scale scientific data in 1993 at NASA’s Jet Propulsion Laboratory in its Machine Learning Systems Group. He recently served on the National Academy of Sciences Committee on the Analysis of Massive Data, as a Kavli Scholar, and a Berkeley Simons Fellow, and is a frequent advisor and speaker on the topic of machine learning on big data in academia, science, and industry.