Spencer funds NYU course to explore insurance data analytics

Spencer awarded a $50,000 grant to New York University’s Center for Data Science to pilot and develop a course that is focused on insurance and insurtech. The course is anticipated to be taught in Fall 2019 and Fall 2020. Michel Léonard, PhD, CBE, who applied for the grant, will create and teach the course.

“We are excited to be investing in curriculum that ties into risk management and insurance industry priorities,” said Spencer Grant Committee Chairperson Andrea Dudek. “Data analytics has become a critical component in corporate and industry decision making. It is critical that our future leaders have the skills needed to make data valuable and actionable. We look forward to working with Dr. Léonard and NYU on this grant.”

Said Dr. Léonard, “The course will showcase the insurance industry’s leadership in expanding the use of A.I. in our daily lives, from self-driving cars to smart homes, cyber security, and predictive modeling, while providing the machine learning skills needed for students to succeed in insurance”

"We are excited to broaden our successful Data Science Masters Program with this offering connecting data science to insurance and insurtech,” said Julia Kempe, Director, NYU Center for Data Science. “This will significantly strengthen the profile of some of our students and prepare them as leading actors in the corporate sector.”

Established in 1979, the Spencer funds the education of tomorrow’s risk and insurance leaders by awarding scholarships, facilitating internship opportunities, providing Risk Manager in Residence programs to universities, and awarding grants to help promote the industry to the next generation. For more information, visit

Established in 2013, under founding director Yann LeCun, the NYU Center for Data Science is a focal point for New York University’s university-wide initiative in data science and statistics. The Center was established to help advance NYU’s goal of creating the country’s leading data science training and research facilities, and arming researchers and professionals with tools to harness the power of big data. For more information, visit