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Advisors and AI
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Mohan Naidu (left) and Tushad Driver

The Minds Behind the Machines: Mohan Naidu and Tushad Driver, Alphathena

Alphathena can create and backtest direct indexing portfolios in minutes.

Direct indexing and portfolio personalization are gaining popularity, especially among next-gen investors, so it’s likely any advisor equipped to bring the customized portfolios to clients will win a good portion of the so-called great wealth transfer, which may put more than $60 trillion in motion by 2045.

But building a customized rules-based portfolio involves breaking out the stocks, recalibrating them to the client’s preferences and dealing with the tax implications—without incurring high costs or a lot of time. Even with the direct indexing tools currently available, that’s a big ask for any advisor.

Enter Mohan Naidu and Tushad Driver, the founders of Alphathena, an artificial intelligence–enabled platform that can create and backtest direct indexing portfolios in minutes. The turnkey software-as-a-service platform won best in show out of 25 fintech startups at Morningstar’s annual conference, with one judge citing its “potential to disrupt the industry.”

Engineers and computational scientists, Naidu and Driver met at GE HealthCare in 2001 and worked together on data science and analytics. Eventually, Naidu moved to equity research, and Driver joined PricewaterhouseCoopers’ global strategy consulting business, Strategy&—but the pair continued talking about their jobs, their companies and opportunities they saw that larger firms were missing.

“This whole idea actually came about from Mohan’s time in equity research where he realized the vast majority of advisors in that world today still use some fairly rudimentary tools,” said Driver. “They still use Excel for a large amount of their analysis.”

Alphathena can create direct indexes from more than 1,000 ETFs; the platform lets advisors customize portfolios across almost 100 factors, including ESG. The tool generates custom indexes with a simple language command using OpenAI core generative models. The platform reviews and evaluates exposure and performance in real time; it automatically generates alerts and approval requests for the advisor and the client.

Alphathena can synthesize an index from any benchmark ETF or portfolio, shrink it to a fraction of its size and customize it using an AI deep learning platform with so-called “Smart Weights” that reallocate across the remaining portfolio to minimize deviation from the original index, with, they claim, two times less tracking error. It can develop a plan to ensure tax-efficient portfolio transition across multiple cycles, and automatically rebalances and harvests losses through the life of the customized portfolio.

Launched in the fourth quarter of 2022, Alphathena is accessed via the web or plugged right into a tech stack with an API connection. The firm is still in the early stages of working to create seamless API connections with different custodians and portfolio software companies, said Naidu. While the API integration requires a little more work upfront, he explained, it allows for the customizable user interface to be built into the background of any existing software.

“With the web app, they get the fully functional, built application,” said Naidu. “And they can customize it the way they want, operationally. We then work with them to integrate with their back and front offices. We don’t take ownership of assets. We literally connect back to the advisors’ offices so that their workflow does not change.”

“At the heart of our technology is one idea—access,” he said. “In the end, better technology for financial institutions leads to improved access and personalized experiences for investors.”

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