Since the emergence of Artificial Intelligence, has been sought, that this science will help to understand and predict the behavior of phenomena that often seem to sobrepasarnos. There are daily events that seem to challenge any analysis of patterns and finance, particularly the stock exchange seems to be impossible to analyze with modern tools.
However, the developments continue and there are now many systems that can analyze patterns, behaviors, companies, and even people, customers, so that they can be assessed using schemes such as the “bots” that can carry on a conversation. Today even some systems already incorporate processes for making decisions or measuring risk.
“In practical terms this means that it will be possible to predict the behaviour of shares on the stock exchange, perform assessments, and financial risk of customers, to mitigate risk factors,” says Gustavo Parés Arce, director of Nearshore Delivery Solutions, where Parés notes: “This technology is a milestone in the financial decision-making”.
It is clear that today there is a lot of work using the “big data”, in addition to work with learning machines, neural networks and all encompassed in what we call the Intelligence Artificial. The idea is therefore to put at the service of companies a tool that allows you to understand complex behaviors and to predict what will happen in the future. This, of course, obliges them to give a follow-up to social networks, government information and banking institutions, with the intention of predicting the behavior of some of the indicators of the stock market.
Obviously, the challenge is interesting and complex, because the decisions taken in the field of the stock exchange can involve gains or losses in the millions. Certain decisions are so fundamental to be able to come to fruition some financial operations. In the page riesgocognitivo.com you have a tool that allows evaluating the financial data about the risks of a business or well, that they can make decisions perhaps better informed.
According to Nearshore Delivery Solutions, up to 30% of the financial decisions could be taken with this tool, which could make predictions of up to 5 days according to different indicators of a business as, for example, the value of the shares.
“The idea is to go put together a digital file of risk that complies with the regulation and have greater sources of information”, he added Parés.
Parés says that this technology already has two years of development in Mexico (by Nearshore Delivery Solutions), and that contrary to the conventional systems that are used in financial institutions, the tool in question can learn, and refine their interpretations over time. We are, therefore, faced with a neural network deep.
But all of this is cross referenced against the reality. How can a system predict the value of the bag of values sufficiently accurate for analysts to follow their instructions and advice? What will be the percentage of success in such predictions? It is not known because the announcement of the company does not say anything about it.
The idea of having tools that can predict what that will be, many times they fall on speculation and a few times in speculation-educated. Nearshore Delivery Systems may have something interesting, but not enough to mention it, but it is essential that you put to match up against reality and see if the proposed model works as expected.