Every action, such as a purchase, an indebtedness or even a like, is registered on databases. Big data is that maelstrom of information, the storage of data in real-time that never stops growing.

Companies from different economic sectors use big data to create knowledge and fine-tune their strategies. While retail companies know precisely the preferences of their clients, insurance companies can determine who is more likely to cause a car accident. Likewise, a person will be able to decide if it is the right moment to switch jobs and if the company that they are applying to projects growth.

At FIT, we have a panoramic view of a wide variety of scenarios.

We discern in a sea of data to find patterns, which lead us to create knowledge with the aim of improving people’s lives. We make these conclusions by use of predictive analysis and high-precision algorithms.

Target® predicts pregnancies of clients to promote products such as diapers, baby wipes and vitamins; Netflix® interprets our behavior to suggest shows and movies.

At FIT, we foresee financial, economic and social behavior.

We anticipate trends in the different sectors that make up the economy to provide an accurate view of where we are going and what drives us in that direction.

Predictive analytics, according to Eric Siegel, a specialist in big data, is a discipline based on informatics and statistics, a tool that allows us to make decisions based on data. It is as useful in the decision making of companies as it is for people. We analyze it by use of analytical mathematics.

Through analytical mathematics —whose input is big data— we analyze sections of data that were previously isolated from reality. On the other hand, predictive mathematics are algorithms that allow us to make predictions. Through predictive mathematics, we transform data into valuable information to support correct decision making.

At FIT, we create statistical models to obtain a 360° view of the user in order to predict events and discover patterns in behavior.

Its function is to anticipate the consumer’s desires by collecting and analyzing data. For this, we consider their record of consumption, preferences, styles, income, culture and social segmentation. If we have a deep knowledge of the users, it is possible to predict their future purchases. For example, an important jewelry store knows who to offer the most expensive products to and to whom they shouldn’t. Therefore, the clients with greater purchasing power will not feel that they are wasting their time looking at low-value jewelry, and those with less purchasing power will not feel disappointed.

At FIT, we use these predictions to anticipate consumers’ activities, support them in their decision-making and transform daily processes through an efficient and digital experience.

Its purpose is to reduce risks in the decision-making process; for example, in the adoption of a mortgage loan or the purchase of a company’s shares. Nowadays, commerce and industries base their models on risks prediction. They make predictions based on record data that allows them to achieve a better chance of success by using analytic and statistics mathematics.

At FIT, we use high-technology and huge quantities of data. Big data allows us to identify patterns that give us insights on future events.

We discern a variety of levels of risk, which is reflected in our personalized and flexible products for our users. For that reason, our core and technological infrastructure let us offer a lower cost of money than the average of the banking sector.

The correct and technological analysis of behavior on social networks is one of the factors that feeds the knowledge of FIT every day.

This translates into useful projections for the user, such as looking up a potential tenant through our Kalifika product or connecting with someone who represents an excellent business opportunity. All the information that we look up, share or qualify on social networks like Linkedin, Facebook, Spotify, Instagram, Twitter, among other sites, is registered and feeds big data. 81% of six-month-old babies already have a presence on the internet, Linkedin has 300 million members and politicians campaign on Twitter and Facebook.

With the consent of our users, we use information from social networks to better serve them.