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A multi-line insurance firm has knowledge management and training challenges with its claims processes. This Slide provides a brief explanation of how Nuvento sorts things out their customer requirements. Know more!
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An insurance firm had knowledge management and training issues with their claims operations. At each stage of the claims process, the claims adjuster required a dependable source of reference. They envisioned a solution that would allow for quick and simple access to their knowledge base.
The organization hired Nuvento to design a self-learning system to answer adjusters' questions about the claims processing steps. The system was built to be trained using historical data in order to provide the claims adjuster with a proactive lookup. Nuvento implemented a self- learning system that constantly trains its model with historical data.
A chatbot interface was used by the adjusters to interact with the system. The system was organised with a claims system database to capture all data collected thus far for a claim and give a prediction or lookup of the next steps needed.
The adjusters could ask a question about the application via a chat interface, and the system would respond using the trained model. If the system cannot provide a reasonable level of confidence, it will summon one of the available experts. This greatly reduced their training needs and knowledge management issues.
PROJECT HIGHLIGHTS Efficient claims processing Significant reduction in dependency on individuals Significant hours of waiting time saved Made scalability simple Reduced continued training efforts by 40% Reduced wait times on the claims process steps significantly
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