One of the sectors that can benefit the most from the implementation of Big Data is financial, where figures and quantitative information allow the optimization of services, product customization, and reliability.
The value of a company is measured by the data it manages, but only when it is capable of interpreting it more than storing it, that is where Big Data comes in, allowing it to analyze large amounts in an agile way and in real-time.
In the digital age, everything leaves a trail of information, however, one of the giants that have most wasted this gold mine is the banks.
With the appearance of FinTech companies, it was shown that the correct analysis of Big Data allows providing new functionalities to clients in a closer, more personalized, and empathetic way.
Financial entities have one of the most valuable data with a competitive advantage over other companies, as they are holders of thousands of data on their clients.
It can be inferred that the financial sector must reinforce its strategy to extract as much as possible the hidden knowledge in these volumes of information.
" The application of Big Data allows financial success by allowing them to base their decisions on the findings found when applying analytics to big data," explained engineer John Boza Araya, who works in the Technological Transformation Management of ICE.
Big Data reduces the time that must be invested in the analysis and processing of big data, transforming months into hours, facilitating decision-making more efficiently.
"Through analytics, you can discover customer segments, predict income, costs, develop prediction algorithms on money laundering or fraud," Boza told us.
Also, the development of predictive methods can provide guidelines for automating processes, simplifying procedures, optimizing resources, and improving products for your customers.
In the same way, it is possible to use the Robo-advisor that function as financial advisers and online managers, allowing the financial institution to save costs.
Big Data Analytics offers the possibility of carrying out a more precise and complete segmentation, which will make it easier to improve the loyalty of your customers, becoming a more competitive company in this so-called digital transformation.
It is essential to incorporate technological innovation that puts the customer at the center of everything, creating a detailed profile of each user, their consumption habits, interests, and needs.
“ From there, the strategy of some FinTechs turned more towards alliances with traditional banks, providing them with digital functionalities but using their Data”, commented the Director of Digital Transformation and Business Strategy Bac & Asociados, Fernán Gallegos
Consequently, “ Big Analytics” will allow the bank to offer products and services that are truly adapted to the needs of users, improving its image as an entity and achieving greater customer satisfaction by offering what they need.
Using a predictive model to achieve through Big Data Analytic offer personalized products in advance.
Big Data allows the financial institution to better understand the behavior of its clients, their tastes, interests, and needs, which will translate into the possibility of offering solutions tailored to their financial needs.
When we use Big Data, we can even calculate behavioral variables, information about the area where your customers make their purchases.
Big Data offers greater precision in risk assessment when managing sensitive data, preventing fraud with rapid and early detection through predictive models.
Besides, through the processing of thousands of data from various sources, potentially suspicious activities and behaviors can be identified before fraud occurs.
In this way, an intensive analysis of the data facilitates the detection of criminal or potentially fraudulent behavior.
The benefits of advanced analytics include automating decisions, detecting unusual patterns, and reducing the time it takes to make business decisions.
Antit as a software development company specialized in FinTech has highly qualified IT professionals, with advanced skills in managing Big Data and cloud engineering.