Jing explains how Vanguard uses machine learning and reinforcement learning to deliver personalized "nudges," helping investors make smarter financial decisions. Jing dives into the importance of aligning AI efforts with Vanguard’s mission and discusses generative AI’s potential for boosting employee productivity while improving customer experiences. She also reveals how generative AI is poised to play a key role in transforming the company's future, all while maintaining strict data privacy standards.

Key Points From This Episode:

Jing Wang’s time at Fermilab and the research behind her PhD in high-energy physics.
What she misses most about academia and what led to her current role at Vanguard.
How she aligns her team’s AI strategy with Vanguard’s business goals.
Ways they are utilizing AI for nudging investors to make better decisions.
Their process for delivering highly personalized recommendations for any given investor.
Steps that ensure they adhere to finance industry regulations with their AI tools.
The role of reinforcement learning and their ‘next best action’ models in personalization.
Their approach to determining the best use of their datasets while protecting privacy.
Vanguard’s plans for generative AI, from internal productivity to serving clients.
How Jing stays abreast of all the latest developments in physics.

Quotes:

“We make sure all our AI work is aligned with [Vanguard’s] four pillars to deliver business impact.” — Jing Wang [0:08:56]

“We found those simple nudges have tremendous power in terms of guiding the investors to adopt the right things. And this year, we started to use a machine learning model to actually personalize those nudges.” — Jing Wang [0:19:39]

“Ultimately, we see that generative AI could help us to build more differentiated products. – We want to have AI be able to train language models [to have] much more of a Vanguard mindset.” — Jing Wang [0:29:22]

Links Mentioned in Today’s Episode:

Jing Wang on LinkedIn

Vanguard
Fermilab
How AI Happens

Sama

Vanguard Principal of Center for Analytics & Insights Jing Wang