The use of Artificial Intelligence (AI) can transform industries and companies worldwide. There are already amazing applications now available everywhere, especially in the financial services industry.
AI-powered professional search is changing the way investment professionals consume research, and it provides them with major time savings and the ability to find information they would otherwise miss.
Does that mean that AI will eventually replace an analyst?
Unlikely. There are major differences between people and algorithms. Machines are single-dimensional beings. They’re optimized to do one thing very well – and can potentially do that one thing better and faster than people can. However, while machines are capable of learning tasks, they don’t understand why they’re doing what they’re doing.
Machines are very good at massively scalable, repeatable tasks. And, if machines are scaled up with cloud computing capabilities, they will execute tirelessly.
People have broader integrated thinking capabilities that machines do not possess. People possess creativity – the ability to grow and adapt from their past knowledge, experience and context in a way that machines cannot.
The things that machines do well, most people don’t like performing. Repetitive tasks or dull parts of our workflow can be easily mechanized.
The AI-Augmented Analyst
When people partner with machines, they’re able to accomplish something much more powerful.
An AI-augmented analyst is much better than the analyst that existed before. The threat is not that machines will replace us, the threat is being the last to adopt AI technology and finding yourself left behind.
The stock and securities markets are the most competitive with millions of people competing to have the best insights and understanding of the market. For analysts, having a competitive edge is everything.
How can analysts leverage this AI-powered opportunity?
Solving Information Overload with AI-Powered Research
As an analyst, you’ve likely spent many nights manually punching numbers from broker research reports or filings into a spreadsheet, simply because there’s no other way to do it.
This is where tools that apply machine vision, which automatically and algorithmically analyze images, such as tables in research reports, are crucial for analysts. With one click in AlphaSense, users can extract tables from those documents and add them directly into a spreadsheet.
Another issue you face as an analyst that AlphaSense search easily solves is language variance when searching for specific keywords.
For example, when searching for information on sales growth guidance, there are multiple ways that companies refer to those terms. Multiplied together, there are thousands of variations.
One of your worst fears as an analyst is that you’re missing information, and that can negatively impact the quality of your investment recommendations.
With the proprietary Smart Synonyms™ technology in AlphaSense, users can lean on AI-powered search and not worry about missing information. AlphaSense uses natural language processing to automatically expand users’ keyword searches to include related financial and business terms in their results, while excluding false positives. Users don’t have to think about and manually search for each possible keyword variation individually.
AlphaSense also offers a “Smart Synonym for Numbers.” I can search for the keyword phrase: expected EPS number. By including the word, “number” in my search, AlphaSense understands I’m looking for a number and will display the relevant results, so I don’t have to manually review hundreds of documents to find the figures I need.
Users may want to use AlphaSense to search their own content alongside pre-existing content in AlphaSense. AlphaSense automatically tags every document by recognizing companies and disambiguating similar-sounding companies (i.e. “Apple” the company versus “apple” the fruit), and many more complex issues.
AlphaSense AI technology recognizes industries based on text patterns. When users are receiving research from many different sources, it’s invaluable to have a tool that tags all incoming documents. This way, users quickly find the research they’re seeking.
Algorithms can recognize anti-patterns as well. Text that users don’t want to see, such as the legal boiler plate text or any other data that creates noise during analysis, can be eliminated from search results.
What, then, is the vision for the AI-augmented analyst?
AI-powered professional search creates major time savings and provides an insurance policy for buy-side firms, so they can mitigate risk and not worry about missing critical information.
AI and the Future of Asset Management
Will this advancement in technology require everyone to be programmers to be able to understand these tools?
Not at all.
The self-driving car is a great example. It is an invention that contains many algorithms with many challenging technical solutions built in, working together to deliver the end outcome of a vehicle that can safely drive itself. The driver is sitting comfortably in the car without having to know that there’s any kind of AI going on.
The same goes for AI-powered, professional search tools. While it’s beneficial for analysts to be savvy and knowledgeable about AI technology, it’s ultimately up to the technology companies to engineer AI-augmented products that free the user from concern about using the right technology and let their users reap the rewards.
That’s the beauty of AlphaSense. It’s designed for the AI-augmented analyst, is simple to use and can be immediately beneficial to the entire investment management team.