WTW draws chief data science officer from LV= to unlock value

Broker  WTW (Willis Towers Watson) has tapped a new leader to help advance its global data science capability, and drive further market adoption of artificial intelligence (AI) to unlock new insights and opportunities that can provide “significant value” to the business and potentially “transform” the insurance market.

Pardeep Bassi (pictured) has been appointed to the company’s Insurance Consulting and Technology business in a newly created role of global proposition leader in data science.

Bassi will lead the advancement of the unit’s data science capability globally, building on WTW’s analytics and data science software, Emblem and Radar.

He most recently served as chief data science officer at LV= General Insurance, where he was responsible for creating and delivering the insurer’s advanced analytics and machine learning strategy; working across all business functions to identify and implement solutions for new opportunities where machine learning can provide value to the business.

Prior to LV= General Insurance, Bassi has spent time at AXA and Domestic & General, where he built and led data science teams and initiatives.

Charlie Kefford, global product leader, P&C Insurance Technology, WTW, said: “ WTW is a market leader in insurance analytics with decades of experience of drawing insights from data to support client decision making. We continue to invest, to ensure that our data science capability remains at the cutting-edge of market practice.

“I am delighted that Pardeep has joined our team to drive further market adoption of AI. He has an outstanding track record of applying innovative techniques to P&C insurance challenges, unlocking significant value.”

Bassi commented: “ WTW has a rich history of developing and delivering cutting edge data driven solutions within insurance. I am very excited to join the hugely experienced and talented individuals at WTW and am looking forward to collaborating to drive global industry wide machine learning adoption. We will turn theory into practice to unlock the enormous potential of machine learning and transform Insurance.”

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