Big data, artificial intelligence, and machine learning are some of the hottest technologies out there. Well, machine learning has existed since the late 1950s, and big data got first coined in 2005. However, it is only in the last decade, or so that computer engineers, scientists, and corporations have tried widespread implementations of these technologies.
The investment industry is one of the leading users of artificial intelligence and big data in the modern world. But how is technology helping people make smarter investment choices?
Different sources have their explanations and definition of what exactly artificial intelligence is. This is because AI is a field of computer science that is rather hard to explain and harder to understand.
In simple words, artificial intelligence systems are algorithms that consider data that is fed into them and make complex calculations and decisions, just the way a human brain does.
The basic example of an artificial intelligence system would be playing chess against a computer opponent. Whenever you make a move in
the chessboard, the computer opponent evaluates all the steps it can play
against you and picks one that gives the computer the best chance of winning against you.
One important thing to note is that artificial intelligence systems “learn as they go.” This means that no AI programs aren’t perfect initially, they learn as more data is fed into them, and as they go through various use cases. The more times an AI system functions, it iterates itself and learns from its mistakes, just like humans do. Thus, “Artificial Intelligence.”
Well, big data is exactly like what it sounds. Data refers to information, and “Big Data” refers to a massive collection of information that is difficult to store and analyze using traditional methods.
Big data collections are usually in the terabyte size range, if not more. Therefore, there needs to be a useful data storage mechanism that can store these big amounts of data efficiently so that they are easy to analyze and relate to each other.
One easy example of big data would be to consider large businesses, such an eCommerce website. Such websites usually store a lot of data like the individual items purchased by a customer, the combination of items purchased by a single customer, the demand for individual products, and
Depending on the scale of the eCommerce platform, the data can be huge. All these data needs to be stored to each other so that the platform can analyze and understand the products that have the most demand, the
products that are more likely to be bought together, etc. Hence, the use of big data analytics tools.
Now that you know about AI and big data, it is also essential to understand how these two technologies go hand-in-hand.
See, as we mentioned earlier, to enable an artificial intelligence system to make the right decisions and accurate predictions, we need to train the system with lots of data. These data will be used by the AI system to make predictions/calculations. If there are errors in them, the system can mostly rectify itself depending on how it is coded, or the programmer can make changes to the AI system to function correctly.
While training an AI system, it is a tedious and often challenging task to provide it manually with huge amounts of data that mimic all use scenarios. Hence, a well-maintained big data system can help in giving
the AI system with all the types of data it will need to learn, commit
mistakes, and correct itself.
Artificial intelligence and big data are, without a doubt, going to be two of the most prominent technologies in the investment world shortly.
Time and observation are vital when it comes to making investments. In today’s world, everything from a tweet by a world leader, a new law, or a growing epidemic, can all exponentially grow or tumble the stock markets and other investment sectors.
Therefore, it is essential always to stay updated about the current market behavior to predict future returns accurately. However, with human effort, this is very time-consuming, resource-intensive, and contains a high risk of predicting or calculating things wrong.
However, with the help of a well-developed artificial intelligence system that was trained well by a big rich data set, investors will be able to analyze changing market scenarios and make prompt decisions quickly. Thus, such a system helps in making both back-end calculations as well as front-end decisions for investors.
Artificial intelligence systems already exist in the investment industry. And they go through a lot of data including social media posts, geopolitical scenario, market risks, and much more to make real-time predictions which help investors a lot to make swift decisions that safeguard
Not just traditional investment predictions, but AI systems can also help investors to move away from high volatile investments and focus more on investments with the least risk.
Companies such as LearCapital enforces the latest AI and big data techniques to allow people to invest in low-risk precious metals such
as gold and silver. You can check out Lear Capital everything you need to know to find out how it works. As precious metals are less volatile to sudden price drops and have huge demands, more people are nowadays interested in precious metal investments, especially for retirement savings, than ever before.
So to put it, technologies such as AI and big data are allowing investors to conduct high precision analytics of data faster than traditional analytical approaches and thus helps them to create faster and more informed decisions.
Artificial intelligence may sound too flashy and attractive, and as we all have heard many times, AI brains may even rule us one day. However, that day is still not here yet!
As we mentioned before, the efficiency and effectiveness of AI systems are hugely dependent on the data that they were trained on. Therefore, entirely relying on AI systems is not at all a recommended option when huge investments are at stake.
Instead of replacing the human workforce with robots and AI. Investors should focus on developing a team that has specific skills to understand and analyze the predictions/calculations put forward by the AI systems. As well as use their intelligence and experience to make viable investment choices.
Implementing an AI-based system backed with the power of big data unleashes a very significant advantage for investors. However, doing
so is not a small task and is a challenge by itself.
One of the prime concerns of implementing such an advanced IT system is its cost. Apart from high installation costs, there are additional expenses in the form of maintaining the system, finding a large amount of data, and storing them for analytics as well as training the AI.
Even though being an early player in utilizing these cutting edge technologies does bring an advantage, it is not to forget that the technology front is continuously evolving at a rapid pace than ever before.
Therefore, even a latecomer can have an advantage in terms of efficiency and results. So, it is crucial to keep the system evolving and up-to-date.