Use of Unstructured Data Might Give AI-Driven Financial Advice an Edge

The use of artificial intelligence to provide financial advice has far to go, at least partly for reasons of human trust in the quality of the advice. But there are some potential advantages for AI-generated algorithms that underpin the advice, when compared to current human-devised algorithms. 

It is relatively hard for human algorithms to quantify and make sense of unstructured data. That should be increasingly possible for AI, which will have the advantage of many more data points. On the other hand, AI systems might not be as well-equipped as human advisors when it comes to factoring in human emotions (fear versus greed). 

The same arguably holds true for unexpected events such as pandemics, wars or political upheavals. As a general rule, then, AI-generated advice might be more useful during times of relative market stability, while human decision-making might be more important at times of market turbulence. 

On the other hand, since AI can process so many more sources of data, faster than the human algorithms, it is possible AI also could be better at detecting shifts of trend. 

Also, to the extent that the AI algorithms can evolve organically over time, as the systems learn, AI could have an advantage over human-created algorithms that must be manually revised. For instance, “generally accepted accounting practices” and financial metrics of performance are relatively static measures. 

AI can take advantage of social media sentiment, easy measurement of cars parked in company parking lots and other non-traditional indicators that are similar to “channel checks.”

The point is that we might ultimately be surprised at how much "advice" businesses and functions will eventually be displaced by AI mechanisms. Much expert advice is driven by rules of thumb; general rules and experience or precedent.

AI is going to be pretty good at summarizing and applying such knowledge or precedent for financial guidance. Algorithms already have been driving buy-sell actions in equtiy markets, for example.

In the same way, the ability to process unstructured data might give AI systems an edge over human advice, or at least become a required part of humans giving advice.