Artificial intelligence applications are now commonplace in the insurance industry. However, many insurance executives are not 100% comfortable with implementing an AI-based solution within their organizations.
On Tuesday, September 17th, Dr. Nilesh Karnik, Chief Data Scientist at Aureus Analytics held a live Masterclass in which we explored the applications of artificial intelligence for the non-technical business user. Upon laying the foundation, we focused on examples of actual implementations of AI applications that are in production today, followed by best practices for developing and maintaining practical applications in the insurance industry.
Examples of what artificial intelligence is and what it is not, including the history of AI development, from initial AI-based systems and the progression to present day
The breadth of AI applications at present: machine learning, language processing, voice analytics, computer vision, optimization, robotics, and games
“How” is it done: a deeper dive into the “how” part with a focus on learning systems, i.e. machine learning, neural networks, deep neural networks
Case studies of real implementations of AI applications of insurers using predictive models for customer retention and fraud detection
Practical considerations for building stable, maintainable AI applications
Whether you view AI as a business advantage or a potential risk to your organization, this Masterclass is designed to help non-technical senior managers and executives gain a better understanding of how practical AI applications can be deployed in the different insurance organizations.
Typical attendees include:
Insurance executives seeking to better understand AI
LOB owners from Underwriting, Operations, Claims, Marketing
Customer Experience and Customer Service senior management
Service Center and Call Center senior managers and executives
Business users of predictive and sentiment analytics applications
Chief Data Scientist, Aureus Analytics
Dr. Karnik is responsible for the development of algorithms and mathematical models that power Aureus' platform and products which help large organizations with advanced analytics solutions.
Nilesh holds a Doctorate in Electrical Engineering from University of Southern California (1998). His PhD dissertation made a substantial contribution to the theory of Type-2 Fuzzy Logic Systems and his work is still widely referenced.
In 2015, Analytics India magazine named Nilesh one of the top 10 data scientist to watch.
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