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Machine Learning and Automation are the Future of Social Investing

By Apac CIO Outlook | Monday, February 11, 2019

Big data and machine learning have changed the way people and organizations process information. Social media mammoths use the data of their users for commercial and political purposes. By applying machine learning tools, these social media platforms can read a user’s profile and identify the user’s needs and wants accurately. Artificial intelligence (AI) is making its way into people’s daily lives, and it could be applied to trading and investing. Some hedge funds and quantitative funds have developed AI-driven trading bots.

The automation of idea generation, idea validation, and trade execution can solve multiple issues. AI can help automate these processes with bots. Implementation of bots can help investors analyze the information accurately and precisely. Automation is also needed to remove the emotion factor especially when the investor is eyeing a position closely for long periods. AI bots will play an important role to help investors to be more reliant on automation and scalability.

There are a few challenges that AI will face before being commoditized. Firstly, AI has to understand a user’s request correctly. For trading, AI bots need to understand the demands of the trader and this idea is still farfetched. Sophisticated virtual assistants of today still struggle when something is requested. The second challenge is the quality of data. If the source of data is not right or the data sets are corrupted, then the outcome would not be reliable.

Market participants are eager to run the data individually to get their hands on the better set of data. However, raw information should not be the focus. The focus should be the knowledge extraction from the data. The last challenge is the user interface that currently exists. Chatbots are being used in customer relationship management but not in the financial industry. They are still dependent on outdated interfaces such as watch-lists, spreadsheets, and chart reading skills to identify signals.

Today’s generation grew up using smart devices with touch screen interfaces and notifications. In this social media age, a more straightforward user interface that encourages idea generation, validation, and sharing is essential. Once these challenges are solved, the next step should be used to increase the complexity of the bots by using machine learning. Investors can help build a community with the help of automation and machine learning.