Service center automation using the state-of-the-art NLP
Who is this presentation for?
- Data scientists, AI developers, and architects looking to integrate AI into their systems
Insurance agents send over a million emails per year, requesting endorsements, cancellations, and quotes to their in-force policies. Opening the email, understanding its intent, triaging, routing, and creating a work task for the next step of the process is very manual, which can add hours of turnaround time.
Building an email processing orchestration engine driven by text convolutional neural networks (CNNs) for classification and BERT for entity extraction yielded a significant reduction in manual processing time of inbound emails. Douglas Calegari provides an end-to-end walk-through of how his team acquired and preprocessed the right data for the training sets and evaluated and selected state-of-the-art NLP models, demonstrating how the data pipeline architecture was vital during the development lifecycle and in production.
- A basic understanding of NLP models and the machine learning development lifecycle
What you'll learn
- Learn techniques and best practices when developing NLP solutions that integrate with complex transaction based systems
Douglas Calegari is a director of architecture and strategic development at a Fortune 500 insurance company. In a career that has spanned several decades, Doug has worked for multiple startup companies, insurance, and financial services institutions.
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