NEW DELHI : Stock markets and investment advisors have taken a slow approach towards adopting artificial intelligence (AI) in everyday operations even as AI leads the digital transformation of multiple legacy industries. For brokerages, market advisors and traders alike, AI continues to play a bit-part role in most operations, despite the heavy dependence on data and analytics in investment and market analysis sectors.
Industry experts said while there is some market interest in using AI in analytics and end-user features, most of it is still in the nascent stage.
Tejas Khoday, co-founder and chief executive at brokerage Fyers, said these include fundamental issues that continue to plague numerous brokerages.
“Brokerages are still focusing on using technology to reduce latencies, and make their platforms fail-safe from downtimes and threats of crashing — incidents that can lead to massive losses. It’s not improbable for brokerages to invest in creating AI recommendation and analysis models on their own platforms akin to the available charts and data, but this would be a factor of when the market generates demand for tech-driven advisories,” he said.
Sonam Srivastava, founder of Wright Research, an equities research and advisory firm, concurred, and said, “While we have a clear reliance on using AI to analyze data and create trends that we then feed to our machine learning system, our market is still not ready for AI to become a standalone factor for which investors would flock to a platform,” she said.
Both officials highlighted key factors of how the stock market operates, due to which AI upstarts haven’t seen their growth surge. For most funds, tech expenses are centred around fundamental infrastructure, or in using the data to draw statistical analysis that is then delivered to clients through human brokers and advisors. As Srivastava said, nearly 90% of her clients approach her to gain from her nearly two decades of experience as a market researcher and advisor —and not for the AI or tech component of her offering.
As a result, firms are keeping away from investing in AI to boost customer offerings, since customers themselves are wary of simply trusting AI for making investments.
This, according to market traders, originates from how the market functions, too. Abhay Bhatia, a Mumbai-based trader and investor, said one of the key reasons why AI may not be an instant hit in the stock market is due to how market trends work.
“In a market environment where there are clear trends, it is easier to use AI to project how a stock might work, and invest accordingly. However, in a sideways market, where there are major out of turn crashes, or irregularities due to external factors, AI cannot be a factor that is solely depended on, and human intervention is always required,” he said.
Bhatia added there has been an increase in the use of AI in the stock market, with algorithmic trading taking up around 10% of the market’s overall volume at the moment. However, both Srivastava and Bhatia affirm that the addressable market size for investors interested in using AI is a tentatively smaller one, which automatically translates to a smaller opportunity for drawing returns on investments (RoI) in AI technologies for brokerages and advisory firms.
Despite this, startups have continued to play the field, addressing a small market size in India currently. Sumit Chanda, chief executive at Mumbai-based AI-based investment advisory firm Jarvis Invest, said the company’s machine learning tool seeks to create price projections based on 12 million parameters, a factor that has seen the company grow in the past one year. Jarvis grew to 4,900 users, from 1,820 users in March last year, marking a 2.7 times increase. The company presently has ₹110 crore of total investment portfolio under its management.
However, Bengaluru-based AnaStrat, which uses AI to offer post-trading analysis of investment decisions made by users, hasn’t seen such steep growth, and is looking to diversify. Mohit Golecha, co-founder of AnaStrat, said the overall growth has been slow, “but this has largely been a factor fuelled by the consolidation of the stock market over the past one year.” As a result, the firm has used its AI platform to create a virtual investment learning environment — a simulation where users can use AI analytics, learn how to use them, and make virtual investment decisions before actually trading in the market.
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