The role of AI in bridging gaps in Indian retail

Hindustan Times

14-05-2025

Since we are entering a new age of investing, one that is not led by emotions but Artificial Intelligence (AI), financial markets are also changing. AI is changing the way investors engage with financial markets from real-time insights to predictive analysis. Now, there are applications and software like robo-advisors and natural language processing creating customised portfolios and sentiment analysis that were earlier available only to institutional buyers. Today, these are accessible to retail investors. This technology-driven revolution is the third major wave of tech disruption in investing, following dematerialisation and mobile-first platforms. Each wave has democratised investing more and more, and AI will further make markets more inclusive, smart, and intuitive for the retail investor.
The late 1990s and early 2000s saw the revolution in India's capital markets because of dematerialisation. The shift from physical share certificates to electronic holdings erased cumbersome documentation, fraud, and settlement lags. This was the foundation of retail investing in contemporary times—a safer and more efficient mechanism that facilitated mass participation.
The introduction of smartphones and tablet computers were another moment for the evolution of trading platforms. With the evolving mobile technology and its growing ubiquity, investors began demanding to have access to trade anywhere. Brokerages answered with mobile-optimized platforms and standalone investing apps, which enabled users to look at markets, place trades, and monitor portfolios anytime from anywhere. This transition from desktop-based systems to mobile applications radically changed the trading experience adding speed, convenience, and flexibility to retail investors. More importantly, it further democratised access to financial markets by removing the limitations of time and place, ushering in a new generation of technology-enabled investors.
The second wave included the introduction of fintech apps that started offering not just equity trading but also mutual funds, SIPs, gold, insurance, and even loans under one roof. Democratisation of investing will increase through the assistance of additional fintech innovation. Demographic shifts and consumer behavior have contributed significantly towards propelling this trend, as millennials and Genz are comfortable with technology and are leaning strongly toward digital-first investment options.
Fintech platforms have considerably lowered the costs of entry since they offer easy-to-use systems through which an individual can start investing with minimal amounts of money, making financial markets accessible to a much broader population. Fractional investing has also seen an impact enabling people to invest in pieces of expensive items like stocks or real estate rather than having to come up with lots of money in order to afford entire units.
Additionally, the advent of social trading features has brought investing more into a social focus. Users can now share ideas, exchange strategies, and learn from each other, making knowledge accessible to all and providing investors with access to the community's collective knowledge. All these put together are changing the face of investing to more inclusive, educational, and accessible than ever before. While access improved, many retail investors continue to struggle with decision-making and that is where AI played a role.
AI is a paradigm shift and not just a feature. It has the capability to scan millions of points of data in real-time, identify patterns, predict trends, and recommend actions with an increased level of accuracy. For individual investors, this means brighter portfolio allocations, risk management on autopilot, and customized investment plans.
Individual investors have been left confused with information overload, time pressures, emotional biases, and low financial literacy. AI is bridging those gaps. Technology like robo-advisors, AI stock screeners, and rebalancing software is bringing advanced strategies to the masses. AI is also reducing the costs by reducing human intervention, eliminating manual research, and speeding up execution. AI is making investing not just easier but more efficient.
While AI brings considerable innovation to finance, it also generates several issues of significant concern. One such issue is transparency where AI algorithms make decisions can be quite difficult to ascertain, which presents difficulties for regulators, customers, and even the institutions themselves. Accountability is a problem too, as the intelligence of AI-based decision-making makes it difficult to pinpoint responsibility in cases of error. Apart from that, there is also the risk of misplaced trust. AI can be utilised only as a decision-making tool, not to replace human decision completely. Excessive reliance on AI with insufficient checks and balances can lead to bad decisions, customer grievances, and even regulatory penalties.
Existing AI regulations within financial institutions are more focused on ensuring transparency, accountability, and data privacy. Regulators require financial institutions to implement solid governance structures that promote ethical usage of AI, for example, documentation of decision-making processes, regular audits, and transparency in AI-based outcomes. Compliance requires transparent explanations of AI model decisions, strong data protection measures, and safeguards against biases and discriminatory behaviour. When regulations evolve, financial institutions must remain ahead of the curve by revising their AI strategies to tackle new compliance requirements and promote responsible innovation.
This article is authored by Ajay Lakhotia, founder & CEO, StockGro.