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Banks and other financial institutions already see value in implementing data-driven analytics and increasing levels of automation and intelligence. Recently, adoption in financial trading has seen a significant uptick. Wealth managers are using AI to help serve more clients. Traders are implementing bots for stock market prediction using AI to gain slight market advantages.
While a predictable formula that could be used to guess tomorrow's stock prices might not truly be possible, traders and market makers are voracious consumers of data. Any tip, trick or tool at their disposal can help gain even the slightest advantages against their peers -- and AI is slowly becoming one of these tools.
Cracking the market with AI
One of the biggest ways that AI is being used on the trading floor is to model changes in the stock market, global finances or in risk levels. This can help banks and other institutions plan for potential problems. AI is able to compare organizations and analyze markets at profound detail and combine this with other information to help gauge possible outcomes, provide advice on investments and inform trades.
To be competitive in the stock market, you must read the news regularly and check stocks constantly. As a result, companies are building tools that use AI to provide investment advice and news for the stock market. Some of these tools allow users to tune metrics such as specific stocks, specific types of deals, prices and then the bot monitors the stock market and factors that influence the market and provides real-time announcements to the user. This speed is incredibly valuable when milliseconds matter and getting something just slightly faster than a competitor can potentially make a huge difference. Other AI tools are looking at the stock market in real time to track complex patterns in the market and analyze the patterns, allowing for real-time risk assessment to ensure compliance. Many companies such as EquBot or AlphaSense have built tools to watch the stock market for slight changes.
Augmenting human stock-traders
Humans are not particularly good at combing through very large volumes of data at high speeds, but machines are great at this. Recently developed tools use natural language processing (NLP) to allow users to talk to the system to filter out things such as financial data, stock statuses, current trends and conversions. Some systems -- like GreenKey Technologies -- go one step further and allow users to search through their own personal financial notes with the bot.
Another augmented intelligence feature popular in stock market tools allows AI systems to provide daily stock recommendations to users along with stock rankings. AI uses pattern recognition and price forecasting to provide the best information possible. The system provides recommendations, but it's up to the human to make the final decision on what to do.
AI is also helping with the back end of financial trading. Companies are using AI to help facilitate communications and back-end actions. This can include IT-related issues, financial data processing and reducing the labor associated with compliance, audit and regulations. AI systems can provide automatic documentation when certain activities happen, and record paper and voice-based transactions when necessary. This is especially critical for heavily regulated industries, which finance, trading and banking all fall under.
Robo-advisors changing wealth management
One of the most popular uses of AI in the financial world today are robo-advisors. Falling into the goal-driven systems pattern of AI, these advisors use little to no human intervention to provide advice on the current financial world and act as a financial advisor to many clients. Many wealth management companies have robo-advisors as part of their offerings because they allow customers a less expensive alternative to traditional wealth managers.
Robo-advisors see popularity because of their lower cost to the user, allowing a company to gain customers they may not otherwise have attracted. Primarily, users with little-to-no stock experience can seek out advice for potential investments or get guidance on how to save for certain goals such as college, retirement or a wedding. Using machine learning, the system is able to run through hundreds of thousands of scenarios to be tested in a very short amount of time and come up with suggested plans.
The stock market is a great place to see the increasing adoption of technologies like AI as it is a complex environment that can add significant insight, provide better pattern identification and simplify back-end processes. In the next few years we expect to see more AI role out and hope that tools become accessible to the general public so that everyone can get access to these powerful tools.