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The AI-Augmented Investment Analyst
March 18, 2019
3 min read
Augmented Intelligence is changing the way investment professionals consume research by streamlining data aggregation and eliminating repetitive processes.
But does that mean that AI will eventually replace an analyst?
There are major differences between people and algorithms. AI is very good at automating repeatable tasks at scale — and when lifted with cloud computing capabilities, they will execute tirelessly.
But AI tools are also single-dimensional. Machine learning algorithms are typically optimized to do one thing very well, and when trained effectively, do that one thing better and faster than people can. But even though machines are capable of learning tasks, they don’t understand why they’re doing what they’re doing.
Humans, on the other hand, are more creative and have a more dynamic approach to knowledge processing — which can bring richer context, deeper analysis, and more nuanced insights to research in a way that AI can’t.
The AI-augmented investment analyst
The stock and securities markets are competitive, with all players fighting to discover the best insights and understanding of the market. For analysts, having a competitive edge is everything.
What is the vision for the AI-augmented analyst?
Extracting relevant data
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 machine learning tools that analyze images like tables, charts, and research reports are crucial for analysts.
Natural Language Processing, a subset of AI, can also help identify and aggregate nuances in language, eliminating the need to perform multiple, often-complex searches to cover all variances in language used to discuss a particular topic.
Leveraging alternative data
AI-powered search engines can analyze millions of documents in seconds, delivering data back to the user in an organized fashion. By outsourcing data mining, analysts save hours of research time, allowing them to spend more time on analysis and generating alpha.
Risk management and compliance
Using an intelligent research management solution allows firms to organize, analyze, and share the research and data needed to make important investment decisions. A good system will enhance an investment manager’s research by centralizing information, fostering collaboration, and increasing productivity.
AI and the future of asset management
When people partner with machines, they’re able to accomplish something much more powerful. The threat is not that machines will replace us; the threat is being the last to adopt AI technology and finding yourself left behind.
Want to learn more about maximizing your investment research strategy with augmented intelligence? Download our best practices guide.
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