Raymond Au

Head, Allianz Asia Lab (Data Science, Innovation)
Allianz

Raymond is the Head of Allianz Asia Lab for the Asia region at Allianz, where he leads a team of data scientists in harnessing advanced analytics to develop compelling customer and business solutions. Allianz’s Asia Lab is Allianz’s first dedicated innovation hub to build the next-generation digital insurance business model in the region.

Raymond’s team focuses on strengthening Allianz’s digital expertise in Asia Pacific by developing data products and delivering deep insights into customer needs and enhancing the capabilities of our insurance business, in additional to working with Start-ups and tech companies to drive end-to-end business propositions.

Raymond is an avid behavioural scientist with a keen interest in understanding consumer’s behaviour through leveraging data science. Before joining Allianz, he was with Publicis Groupe, where he established their data science services. With cross-industry experience in other roles at Oracle and SAS Institute, Raymond is well-versed in data architecture, sales and channels management, consulting and IT.

Raymond holds a Bachelor degree in Computer Science from NUS, Singapore; an MBA from University of Strathclyde, UK, and he is currently pursuing an MSc in Behavioural Science at the London School of Economics and Political Science, UK.



9:00 AM Workshop C: Nurture, Reskill and Upskill Your Existing Manpower To Enhance The Effectiveness Of Machine Learning Applications

No doubt, technology, data science, machine learning etc will change the nature of current jobs, but that doesn’t mean there will be no jobs. People will continue to play a very important role in putting data into context with machine learning application.
 

This workshop will guide participants on best strategies and practices in re-skilling and upskilling your existing manpower to boost competencies in translating data into actionable insights.
 

Learning outcomes:
  • Identifying areas for machine learning deployment and re-allocate talent for value-added work
  • Equipping your team with appropriate domain knowledge
  • Assessing the impact of machine learning  on the future workforce
  • Taking a proactive approach to nurture, reskill, upskill your existing workforce 

10:50 AM Allianz: Detecting abnormal motor claims using Machine Learning

·         Evaluating traditional methods for reducing motor claims leakages
·         Mimicking human knowledge using Machine Learning to build a workable model for abnormal claims detection
·         Improving adoption of machine learning models through integration with existing processes and systems
·         Reviewing lessons learnt from PoC to Production

2:40 PM Roundtable C: How to attract, nurture and upskill workforce for successful machine learning deployment

  • Identifying areas for machine learning deployment and subsequently  re-allocate talent for value-added work
  • Assessing the impact of machine learning  on the future workforce
  • Taking a proactive approach to talent acquisition, retention and retraining