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HomeTechAI seeks to analyze trader behaviour, but experts urge caution

AI seeks to analyze trader behaviour, but experts urge caution


NEW DELHI : The use of artificial intelligence (AI) is not new to stock-broking, but the emergence of robo-advisory services is fast changing the landscape. While traders are excited about the prospects of advisory services using data analytics, experts have sounded caution.


Bengaluru-based Anastrat, for instance, uses AI to analyse historical data and trading patterns to help traders make investment decisions. While Anastrat offers suggestions on ‘hold‘ or ‘buy‘ stocks and diversify portfolios, others such as Sharekhan Neo, Angel Broking ARQ or 5Paise Auto Investor, use algorithms to generate automated investment plans using preset market strategies and trends to suggest ways to invest in the stock market.

Mohit Golecha, founder and chief technical officer, AnaStrat, said within two months of launching its “one-of-a-kind service” it has 110,000 clients with 35,000 daily active users. It has partnered with four brokerages in India—Zerodha, Fyers, IIFL and Dhan—to offer its services.

Bhumik Gada, a trader and financial advisor, who works as a sub-broker for many brokerages and handles portfolios of over 100 clients, said if the platforms can offer reliable analysis, it could be a valuable tool. “It is often difficult to follow trading patterns of each client, which is what drives traders like me to analytics tools,” he added.

However, experts said the efficacy of behaviour analytics platforms are yet to be tested.

“One, there are no laws in India that tell customers what would happen if the platforms give wrong investment advice. More importantly, these advisory firms are not regulated by the Securities and Exchange Board of India and therefore do not provide binding investment advice to investors,” said Mathew Chacko, founding partner and head, technology, media and telecom practice, Spice Route Legal.

Chacko said AI tools analysing trading behaviour to offer market suggestions fall under the robo advisory segment and must be regulated. “Analysing data to predict future outcome in a volatile equity market is a risky, something that may not be particularly valuable for individual traders. Many factors influence markets everyday, each of which fluctuates. Using AI tools requires traders to be veterans, and have a sound understanding of the market risks. Otherwise, they may face losses,” he added.

Moin Ladha, partner, corporate and commercial practices, Khaitan & Co, said lack of regulatory definitions for AI and automated tools in India might prompt Sebi to eventually bring such services under its ambit. “The way investment advisories and research analysts are defined by Sebi are too wide, and if you are offering any form of financial advisory you might easily come under Sebi regulations.”

Though robo-advisors in India are still at a nascent stage, globally such tools are gaining traction. For example, Polish firm Sigmoidal‘s deep-learning-driven investment strategy tool, or Chicago, US-based Neurensic’s trade pattern analysis platform, and Seattle-headquartered Kavout’s K-Score are using data analytics and predictive AI to rank stocks on the basis of the investment patterns of users.



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