From Wall Street to AI Street: How AI is revolutionizing Fintech


    • Generative AI Chatbots have taken the internet by storm.
    • Read on to find out how they're set to revolutionize Fintech too.


Read to find out!



A recent study titled ‘State Of Enterprise AI In India 2019’, published by Analytics India Magazine in association with BRIDGEi2i, suggests that the Indian enterprise market for AI applications is estimated to be valued at $100 Mn, growing at 200-250% CAGR.

Another report by Accenture shows AI has the potential to add $957 Bn, or 15% of India’s current GDP to the economy by 2035. The combination of the technology, data and talent that make intelligent systems possible has reached critical mass, driving extraordinary growth in AI investment.

Goes without saying, the rise of AI can change how we deal with finance forever.


What are the use cases for AI in Fintech?

Angel Investing and AI?


So, can an algorithm outperform the average angel investor? And if it can, does that also mean it will make less biased investments? 


Many large venture capital funds use artificial intelligence (AI) to support their investment decisions. Bill Maris, former managing partner at Google Ventures, once said that when you “have access to the world’s largest data sets … it would be foolish to just go out and make gut investments.”

Most startup investors, however, do not have access to Google-esque resources and still do things the old-fashioned way. Angel investors, for instance, rely heavily on gut feeling to make investments. But as technology advances and the cost of building powerful algorithms through machine learning decreases, these investors will need to decide whether to incorporate AI. Can it outperform human judgment in making early stage investment decisions? And how should angel investors use it?

A group of researchers from Harvard built an investing algorithm and put it head to head with 255 angel investors in a simulation, asking it to select the most promising investment opportunities among 623 deals from one of the largest European angel networks.

The results? The algorithm significantly outperformed the average novice investor and even experienced investors who fell prey to cognitive biases, but was bested by the top tier of experienced investors, who could control for their own biases. While the algorithm may have made less biased choices when it came to the race and gender of the founders it picked, it also reflected systemic inequalities, and illustrated the limits of how algorithmic investing can be used to address deep social inequalities. 

The Bottomline

The research underscores the advantages of using AI in early stage investing. It can process large amounts of data, correct individual investment biases, and, on average, outperform its human counterpart. At the same time, the most successful individuals — experienced investors able to correct for their cognitive biases — outperform the algorithm in terms of both efficiency and fairness.