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Next Revolution: AI & ML in Investments Space

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Next Revolution: AI & ML in Investments Space

Pranit Arora, Co-founder & CEO, Univest, 0

Experienced business professional with a demonstrated history of working in the FMCG, disruptive Technology, Hospitality, Automotive after sales and Logistics environment. Skilled in Fast-Moving Consumer Goods (FMCG) Sales, Business Development, Trade marketing and Strategy. He is responsible for leading and overseeing all aspects of the company's operations, including setting the overall strategy, making key decisions, and ensuring that the team is aligned with their goals and values.

Like many of the fields, the world of investments has also seen a paradigm shift due to advancement of technology and the use of AI and ML tools in investment decision making.The shift in the investment space is primarily because, till the turn of the century, only those who had access to information could make informed investment decisions. All this changed with access to information becoming far more accessible, where today real time stock quotes are available easily on your smartphones.

This combined with the ability to compute hundreds of data points across different parameters and present investors concise information have completely changed the way data as well as actionable insights are presented to investors.

The use of AI in investment decision-making offers a significant advantage as it can quickly analyze vast amounts of data that may be overlooked by human analysts. With the capability to identify patterns and trends, AI algorithms can analyze various types of data, such as social media sentiment, news articles, and financial statements, to identify signals and make predictions about a company's future performance.

Combining ‘Human and Machine’ for Optimal Solutions
Though AI can present numerous insights, one must remember that at the end of the day, any machine will give results based on inputs by a human. Any AI based results are ultimately the results of algorithms written by human. Where the machine scores over a human is the ability to compute vast amounts of data in split seconds and present them in a categorized or structured manner. So, it is a complimentary skill of human analysis plus the processing speed of a machine to help better decision making skills.

Why Speed Matters
One of the biggest advantages of AI and ML in
investment analysis is the speed at which data sets can be presented. For example, if were to track the stocks that gained the highest in value over the last month, it just takes the click of a button. Similarly, I can shortlist stocks that gave highest returns in the previous month and the month prior to that. Furthermore, additional conditions can be applied to these selected sets and the system can generate a shortlist of stocks that may meet the multiple criteria for an investor. This whole exercise can be done in a few clicks and the result is available within minutes. The logic and conditions can have any number, but the result of processing multiple data points and producing actionable insights happens in a few minutes.

The use of AI in investment decision-making offers a significant advantage as it can quickly analyze vast amounts of data that may be overlooked by human analysts.



Application Across the Spheres of Investments
AI can also enhance the execution of large orders and optimize order flow, improving efficiency in the financial markets. Advancements in AI technology are transforming the peer-to-peer (P2P) lending industry, streamlining data processing for more efficient creditworthiness evaluations of potential borrowers, optimizing underwriting processes, and enabling more effective management of lending portfolios.

The integration of AI technology in investment decision-making processes has the potential to bring about a significant transformation in the finance industry. AI can improve investment outcomes while also minimizing risks for investors. This means that by using AI, investors can make more informed and data-driven decisions about their investments, leading to better returns on their investments.

Conclusion:
AI can help in analyzing vast amounts of financial data and identify patterns that might be difficult for humans to recognize. This could potentially result in more accurate predictions about market trends, which could aid investors in making more informed decisions. AI can also provide real-time insights and recommendations that can help investors react quickly to market changes.

Moreover, AI can help in reducing human errors and biases, which can result in better investment decisions. AI can analyze data objectively, without being influenced by emotions, opinions, or personal biases. This can result in a more reliable and consistent investment strategy. Further improving the accuracy of investment decisions using AI and ML is probably the next level of things that we can anticipate in coming days.