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Today’s claims processing involves a great deal of manual effort. Claims managers and adjusters often spend most of their time looking for claims data scattered in different systems instead of focusing on analyzing claims and delivering optimal service to customers. In addition, many tools for claims processing lack the ability to quickly distribute analytics and actionable insights to the users who need them most to drive informed decisions. As a result, insurers are left with poor operational efficiency, increased cost, greater risk exposure, and low customer satisfaction scores.
An end-to-end claims analytics solution that automates data collection, performs predictive analytics and distributes insights can not only alleviate the burden of manual processing, but can also provide more comprehensive understanding of claims to support better decision-making.
During this session Neal Silbert, insurance industry veteran and advisor, and Mark Rusch, VP of Insurance, GoodData, discuss how an advanced analytics solution powered by machine learning and AI can:
- Enable a 360-degree view of the claims that drives intelligent decision-making
- Provide deeper insights into your new and existing claims to effectively identify fraud and reduce future losses
- Automatically deliver continuous improvement of the overall claims process based on a closed-loop feedback system
- Improve business agility by quickly aligning your operations with the ever changing business environment
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