By Hemant Sood
The world has entered an ‘AI era’, and it is becoming more mainstream in different domains and sectors. The finance industry is no exception, and market watchers and players are also positive about the implementation. According to a joint report by PwC and FICCI, 57 per cent of financial organisations agree that AI will give them a competitive edge in the markets.
Furthermore, participants are utilising its power for several functions in the industry, such as automating procedures, making informed decisions, and predicting growth opportunities. In addition to that, AI has been actively considered for algo trading systems, which have already been a boon to the financial markets as a whole for a long period of time.
Algo trading with AI as an enhancer
The increased competition in the market has led traders to change their strategies, and algo trading has emerged as a successful one. SEBI has allowed algorithmic trading since 2008, and its popularity among institutional investors, HNIs, and individual traders has rapidly increased and never looked back since. Unlike before, it is today available at the disposal of individual traders, who are using it to make more efficient and faster trading decisions. As a result, today 50–55% of trades happen under the influence of algorithms. However, the progress does not stop here.
With the advent of AI, algo trading has become more advanced. It is not only aiding in the analysis of bulk data but also helps traders make informed decisions. Furthermore, it analyses trends and patterns that are difficult to observe manually, which instantly provides a competitive advantage. With the capacity to learn and adapt, it can mould itself to changing market conditions, making it lucrative for the trader. Collectively, AI algorithms have become performance enhancers for the participants in the market. Also, some of the realised use cases for AI in algorithmic trading are changing the landscape of the finance industry at a faster pace.
Fulfilling the needs of traders
The proliferation of AI in trading is largely a result of the expansion of data availability and technological advancements. Trading professionals today have an abundance of market information. As a result, AI trading systems can be used efficiently as they are capable of accurately and quickly processing this data, enabling traders to make sound choices in real-time. The industry and its participants have recognised its potential and have been rapidly implementing AI to benefit from a myriad of benefits.
Increases efficiency: The purpose of AI in algo trading is to process enormous amounts of data quickly and precisely. This improves the efficiency of the trading process by enabling traders to execute in less time, which decreases costs and helps traders make informed decisions. According to a Boston Consulting Group report, using AI in trading can reduce operational costs by as much as 25% and increase portfolio returns by approximately 1.5%.
Reduction of human emotion: Human emotions are likely to affect trading decisions, which can have a detrimental effect on profitability. As Artificial intelligence (AI) is not biased and make decisions on data, it can take a call which is devoid of the influence of human emotions.
Dynamic decision-making: AI has the potential to end the conventional algorithmic trading cycle. When using AI-powered algorithms rather than just an Algo-wheel based on benchmarks, decisions are more likely to be intelligent. It uses historical data to recommend specific settings and parameters, which are also dynamic and give traders the best possible results.
Enhanced accuracy: Automation is now a required response to the rising demand for faster and more accurate trading. AI in algorithmic trading entails the creation of intricate rules that gauge market conditions, including volatility, order book depth, latency, and P&L.
Better risk management: In order to help traders manage their portfolios effectively, AI can analyse market data, find anomalies, and spot potential risks while trading. This may result in improved risk management as it reduces error and eliminates human bias, making it more reliable and successful.
Collectively, AI has aided traders in fulfilling their needs for high-frequency trading (HFT), loss reduction, and smart order routing.
Reduced barriers to entry
The use of algos is primarily driven by several factors, including improved trader productivity, diminished market impact, consistent execution performance, ease of use, and more. As AI technology becomes more widely available, a wider range of traders and investors are likely to adopt algorithmic trading. According to a report by Mordor Intelligence, the consolidated algo trading market is anticipated to grow at a CAGR of 10.5% during the forecast period of 2023–2028.
Furthermore, brokers also have access to more sophisticated platforms that employ transparent AI algorithms that were created in response to the demands of the traders. It has democratised learning thanks to their assistance in educating traders about these platforms. Because of the lowered barriers for individual traders, market participation and liquidity have increased as well.
New avenues for employment
The financial sector has greatly benefited from AI, but there are also some concerns about the job market. It’s expected that AI will replace a number of job profiles. However, not everything is doom and gloom. We can observe how the use of AI has spawned fresh job opportunities in industries like data science, AI development, and algorithmic trading. Furthermore, strong proficiency in programming languages, ML/AI, and big data analytics is consequently becoming essential for new employment opportunities. As a result, there is a burgeoning need for qualified professionals in India’s finance industry. As AI still requires human input, there will be a requirement for individuals who can combine human expertise with AI’s accuracy. Collectively, some jobs will be automated; however, they will be balanced out with new opportunities. According to a PwC AI study, any job losses brought on by automation are likely to be more than offset in the long run by new jobs produced as a result of the greater and wealthier economy these new technologies have enabled.
The era of the AI
Artificial intelligence in Indian algo trading markets is still in its nascent stage. However, its trading future is promising and has a lot of potential for the financial sector. Brokerages are concentrating on utilising AI technology to lower latencies and make their platforms fail-safe from outages and crash threats, which can result in significant losses. To remain competitive and offer cutting-edge trading solutions, they are also investing in building AI recommendation and analysis models on their own platforms.
The growth of the AI-based algo trading market in India is anticipated to be fueled by the rising demand for market analysis, which is enhanced by lower transaction costs. As AI algorithmic trading solutions frequently enable simpler and quicker order execution, this makes them more appealing to traders. These solutions have turned out to be advantageous as they aid in instantaneous and accurate trade timing, automated checks on multiple market conditions, and simultaneous automated checks. Hence, as the AI market matures in the Indian financial markets, several new use cases, strategies, and employment opportunities are expected to arise.
The author is founder, FinDoc
