Meet an Advisor for Insurance AI Innovation: NVIDIA's Mark Bennett

Domino Data Lab2023-02-03 | 5 min read

NVIDIA's Mark Bennett
Return to blog home

By Domino Data Lab

A major theme in Domino’s Financial Services and Insurance edition of the Data Science Innovator’s Playbook is change – both in the financial industry and the types of models used for a growing array of industry use cases. One example includes opportunities and threats posed by quantum computing to the proprietary algorithms trading organizations use to make money. Few people have a better vantage point to see where AI innovation is going than NVIDIA’s Mark J. Bennett, Ph.D., senior data scientist for AI in the financial industry.

Meet Mark Bennett at NVIDIA

As a former director and senior data scientist for Bank of America, Bennett long led modeling initiatives in financial services. And in his current position at NVIDIA, his role usually involves giving advice on how to accomplish everything from trading applications to fraud detection and market prediction. Bennett helped shape Domino’s approach to this Playbook, which you can download here.

NVIDIA's Mark Bennett

Bennett expects that in the near future, ML will make even more inroads into all aspects of financial services, as heavy hitters in finance become comfortable using AI in more aspects of their work.

“Most quants don’t have a background in machine learning, but that’s starting to change,” he says, as financial companies are starting to see ML as giving them a critical edge as they work on projects kept so secret that full details aren’t even disclosed to partner companies such as NVIDIA.

“A lot of FSI work is all under the cloak of secrecy,” Bennett says. “They’ll ask us questions in very general ways, without giving a lot of detail on the objective.”

Natural Language Processing and Quantum Computing Driving Innovation?

Bennett sees many areas that he thinks will fuel data science-driven innovation in the near future, but two areas in particular could be critical: advanced applications of natural language processing (NLP), and quantum computing.

Many financial companies would love to be able to automate such things as taking information in news feeds—such as jobs reports or financial wire services—and automatically updating trading programs and strategies. Improved NLP holds out the promise that someday, automation will be at least as good as an expert human, but that is still an aspirational goal today.

Some forward-looking businesses are also doing exploratory research on quantum computing. “We’re going through use cases with some customers who want to explore the speed advantages of financial quantum computing,” says Bennett.

Some of these explorations are defensive in nature, he says, because quantum computing has the potential to be so fast and powerful that it could be used in brute-force methods to defeat current cryptographic cybersecurity algorithms. This would make the trusted RSA cypher vulnerable to decryption in a matter of hours rather than hundreds of years as it stands currently.

But the same technology could be used to transform the capabilities of cybersecurity algorithms as well, he says, so the field could open up interesting new possibilities for “the good guys” to get the upper hand.

Download our free eBook to read more details of insights by NVIDIA’s Bennett and other innovators, advisors, and industry experts at the top of their game in data science within the financial services and insurance industries.

Working with Other Innovators Can Be an Exciting Journey

There is a need to execute trades faster at the lowest cost per trade while computing risk more often across more scenarios. And there is a need for multi-cloud and hybrid solutions—whether it’s speeding up training and inferencing for your NLP models, your image and voice recognition models, matrix operations, networking, or quantum computing simulation, new innovations in CPU’s, DPU’s and GPU’s and a full-stack of software packages are helping teams start an acceleration journey with ease. We invite you read Bennett’s story along with profiles of other innovators; download our free eBook here. Their stories will provide you with useful insights on accelerating AI innovation in the Financial Services and Insurance industries.

Domino powers model-driven businesses with its leading Enterprise MLOps platform that accelerates the development and deployment of data science work while increasing collaboration and governance. More than 20 percent of the Fortune 100 count on Domino to help scale data science, turning it into a competitive advantage. Founded in 2013, Domino is backed by Sequoia Capital and other leading investors.


Subscribe to the Domino Newsletter

Receive data science tips and tutorials from leading Data Science leaders, right to your inbox.


By submitting this form you agree to receive communications from Domino related to products and services in accordance with Domino's privacy policy and may opt-out at anytime.