Q&A with Vishal Srivastava, a “40 Under 40” Honoree for Work in Artificial Intelligence

Vishal Srivastava, a vice president in our Consumer and Investment Management Division in New York, was recently named to Analytics Insight Magazine’s 40 Under 40 list, which honors professionals who work in artificial intelligence (AI) and data science.

Vishal is head of data science and analytics for Marcus by Goldman Sachs'® Digital Storefront, which includes Clarity Money®. He and his team design and build algorithms and models for apps and websites that help users with personal financial management decisions.

Early in his career, Vishal knew he had a passion for technology and how it could make lives easier. He joined IBM Labs after college as a software engineer and worked on its flagship software for data processing. He later pursued his masters from Columbia University, concentrating in cloud computing and machine learning.

We had a chance to sit down with Vishal and ask him some questions.

What excites you most about your job?

The most exciting and motivating aspect of my job is the positive impact that our work has on the financial lives of our customers. My team builds algorithms and models that help our customers make better financial decisions to maximize the value of their hard-earned money. We use data to help improve the customer experience as well as to optimize our business operations and decisions. In my role, I am constantly energized by getting to work with an incredibly talented yet humble group of colleagues.

What has your experience been working in technology within a bank?

My experience working at Marcus, the firm’s digital consumer business, has been very enriching. The problems that we are solving today touch critical aspects of our customer’s life, helping how they manage their finances and plan for the future. For instance, our algorithms help identify recurring expenses and can estimate income to help our customers optimally plan their budget and maximize their savings.

In your 10 years working in AI and data science, what has surprised you about the evolution of these fields?

I’ve been surprised by the speed of innovation and adoption. In the past decade, AI has been applied to a wide variety of industries and now touches almost everyone’s life through chatbots, voice-based devices, smartphones, cameras, just to name a few examples. There are huge opportunities to innovate with AI and algorithmic engineering to help our digital banking customers even more in the future.

In your view, what is the next frontier for AI and data science overall, and specifically within financial services and personal financial management?

AI has the potential to unlock innovation, increase efficiency, accelerate digital transformation and improve the customer experience. While the technology is mature enough and has made a huge impact already, I believe the ongoing R&D in areas such as Explainable AI, Responsible AI and AI model productionizing will unlock numerous layers of adoption especially in regulated industries like financial services.

Responsible AI focuses on ensuring the ethical and accountable use of AI and helps form new regulations and monitoring that is consistent with the values and expectations of the modern world, with fair consideration towards speed of innovation and positive impact. On the other hand, the research on Explainable AI aims to make the AI models more transparent, making it more clear on how the model came up with a certain outcome. This can help firms adhere to the regulatory guidelines. Lastly, reliable productionizing of AI models makes it easier to maintain the lifecycle of model deployment. In combination, these areas will be the next frontiers for AI.