US Investing Champion 2020
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As retail trading and investment enthusiasts, the co-founders found a significant gap in technology available to retail traders and investors vs. institutional ones when it comes to the availability of Financial Market Intelligence software. Also, institutional software is costly.
The 2020 pandemic caused a phenomenal growth in retail trading and DIY investing interest, especially in the Millennials and Gen-Z age group. But not many of them could trade consistently or successfully.
We spoke to several successful retail traders during our market research. We found that almost all of these expert traders spent several years and sometimes decades learning the market the hard way, making expensive mistakes, and blowing up their accounts several times before they could trade consistently and successfully. They have to manually scan the market, study thousands of charts and data points, and visually look for patterns and correlations daily. This we felt is too difficult for most people. Also, the stats that almost 80-90% of retail traders fail confirms that.
When you ask an institutional trader or fund manager what software they use, you are most likely going to hear a single answer which would be the likes of Bloomberg Terminal or Refinitiv Eikon et al. But, if you ask a retail trader, the answer will be a mixed bag because there is no equivalent software for the retail trading and DIY investing market. Each software available here solves a small part of the trader's workflow. As such, productivity is lost in hopping between different software, making decision-making sluggish. Also, multiple software licenses weigh heavily on the retail trader's wallet.
We wanted to solve this two-part problem by creating an AI-powered Financial Market Intelligence Platform for retail traders and investors. Firstly, we provide all the necessary data and tools required in the trader's workflow available in one place. Secondly, we use AI to reduce the time to master the market by providing automated analysis starting points to learn how to trade or invest like an expert fast. And the AI also increases productivity by automating mundane and repetitive time-consuming parts of the workflow. Our goal is to inverse the percentage of retail traders who fail to the percentage of retail traders who succeed.
The team at Researchfin.ai comes from a diverse background of AI/ML/Data Science and large scale products from companies like Yahoo, IBM, Wipro, Naspers Group, Progress Software, and DataRPM, as well as the financial domain from working with the New York Stock Exchange, London Stock Exchange, JP Morgan, Charles Schwab, and Aditya Birla Sunlife Mutual Fund. Our advisory board comprises professional traders and CMTs. We have also partnered with several educators who teach trading and investing across stocks, forex, and crypto-asset classes to help new traders and investors get to trading and investing with consistency and profitably.