The life insurance industry strives to modernize while still relying heavily on data collection through paper forms in order to serve diverse populations. Core to the industry are predictive models that are based on historical data locked in those forms. Divya Ramachandran explains how top insurance companies have used handwriting transcription powered by deep learning to achieve a more than 70% reduction in daily operational processing time, develop a best-in-industry predictive model for assessing mortality risk from decades of archived forms, and enable a smarter claims leakage review, which led to a 10x ROI in its first year.
Divya Ramachandran is the VP of Product at Captricity Inc. where she oversees the creation of effective and impactful product experiences for Captricity users. Her background is in human-centered design, which she practiced as a UX designer at a handful of startups for several years. She is most excited when she is dissecting complex problems to find and solve human painpoints. Divya holds her Ph.D. in Human Computer Interaction, from the University of California at Berkeley, where her research received awards from two prestigious academic conferences. Divya’s areas of interest lie at the intersection of data, design, international development and social good and data. In her free time, Divya loves to cook, experiment with music, and explore sunny East Bay parks with her two young kids.
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