Big Data is defined as data that comes from a wide variety of sources, arriving in increasingly large volumes and at increasing speeds. As data is continuously collected and analyzed, highly valuable information can be extracted to help guide business decision-making. This is where its great potential lies.
The term refers to the recurring collection, analysis, and accumulation of large amounts of data, including personal data, subjected to automated processing through computer algorithms, using both stored and transmitted data to generate certain correlations, trends, and patterns (large-scale data analysis). The growth, speed, and complexity of data are driven by the deployment of billions of smart sensors and devices that are transmitting data (popularly known as the Internet of Things).
Although it is recognized that converting data into information constitutes a major advantage, the veracity of different data sources and the lack of financial budget and technological capacity in most cases are undoubtedly barriers that slow down the implementation of Big Data projects. Nevertheless, many companies have been handling large volumes of data for some time. What distinguishes analytical and management applications from new Big Data concepts are four reference words for pioneering companies in this field: Volume, Velocity, Variety, and Value.
Opportunities and Applications for the Financial Sector
In financial services, especially in banking and insurance, there are significant opportunities to obtain benefits through the application of Big Data and Analytics technologies and methodologies. The main area of application for Big Data and Analytics is advanced customer segmentation. Incorporating new data sources into traditional segmentations makes it possible to obtain a more complete vision and understanding of customer needs, which leads to the definition of value propositions better adapted to different demand profiles. Better knowledge of customers enables more precise targeting, and this translates into greater efficiency and performance of commercial actions. Furthermore, Big Data allows for the definition of appropriate customer actions to achieve greater customer loyalty.
Other applications of Big Data include the management of “omnichannel”—so important in a context where new technologies provide customers with a greater number of improved communication channels and high transaction capacity with companies—and the definition of dynamic pricing strategies by customer segment, in a context approaching real time.
