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  • Aegon Insights shares how Big Data and Analytics can transform the insurance industry

Aegon Insights shares how Big Data and Analytics can transform the insurance industry

July 14, 2017

Dr. Hongjuan Liu speaks at the 2017 International Conference on Big Data Analytics and Business Intelligence

Dr. Hongjuan (Juan) Liu, Director, Customer Analytics & Behavioral Insights, at Aegon Insights, was a guest presenter at the 2017 International Conference on Big Data Analytics and Business Intelligence ('ICBDBI2017') in Suzhou, China at the International Research Centre at South Campus of the Xi'an Jiaotong Liverpool University on 26-27 July 2017.

Juan Liu ICBDBI2017 Suzhou China

Dr. Liu presented on 'How Big Data and Analytics is transforming insurance'. He explained that in the insurance industry, analytics is key to understanding customers and how Aegon Insights is using this to drive engagement and sales. He spoke about the vast accumulation of the volume of big data as a result of the many touch points across different channels and devices. Dr. Liu highlighted a new platform, Aegon IRIS, which is being developed by the Aegon Insights team for a true omni-channel customer experience, with data insights as the key driver.

The ICBDBI2017 is a forum for researchers and businesspeople to discuss the latest topics and breakthroughs in the fields of business analytics, business intelligence, big data analytics, algorithms and analytics methods, data governance, data social responsibilities, hybrid systems, intelligent agents and computational intelligence.

Notable keynote speakers at ICBDBI2017 included:

  • Dr. William Yeoh, the Director of Australia's first IBM Centre of Excellence at Deakin University, who is actively undertaking research in Business Intelligence and Analytics, Information Quality, Cloud Computing, Crowdsourcing and Information Systems; and
  • Dr. Jason Dai, currently Sr. Principle Engineer and CTO, Big Data Technologies, at Intel, responsible for the R&D on advanced Big Data analytics (incl. distributed machine/deep learning), as well as collaborations with leading research labs (e.g., UC Berkeley AMPLab), with global engineering teams located in both Silicon Valley and Shanghai.