“Big Data” collects and analyzes large and complex sets of data. According to IBM, in 2015, 90% of data has been created in the last two years. The financial services industry utilizes the most data in the global economy. This data comes from banks entering large amounts of consumer data daily, including general transactions, ATM transactions, and more.
In the last decade, the financial services industry has heavily invested in data and processing technologies. Banks and other financial services companies need to utilize new and existing data to understand their consumers and have a competitive advantage. The goal of Big Data is to gain real-time insight to push the business forward and to keep advancing with analytics and predictive analytics.
Trends of Big Data in 2020
Sales and Marketing
Big Data improves acquisition by using the information to attract new customers, create effective campaigns, segment prospects based on information Big Data provides, and determine the best messages and channels. Additionally, businesses can determine which products customers will most likely take an interest in.
Enhancing loyalty and trust with customers can be expanded upon through Big Data. Loyalty is enhanced by targeting customers with offers, loyalty programs, customized interactions, and retention management.
Change in customer behavior
Now more than ever, customers interact with banks or other businesses virtually for their financial needs. Virtual interaction means more data is collected, such as browsing history and geo-location. This collection also means social media activity is being gathered where companies can get a more in-depth insight on how to interact with their consumers via different channels to create a more personalized experience for the consumer.
Quality of data
As many different channels are available to each consumer, real-time analytics provide Big Data with precision and speed for companies to see valuable insights and introduce new services and offerings to consumers.
According to Aeris, the Internet of Things (IoT) refers to internet-connected objects that collect and transfer data over a wireless network without human control. IoT will highly increase continuous consumer data. Authentication techniques will also increase the amount of data processed.
Fraud is increasing drastically. Banks and financial institutions need to protect their trust and data. Businesses can also utilize fraud-detection engines to identify irregular consumer behavior.
This portion of Big Data refers to the size of data that needs to be analyzed. Data sets are too large to process on a laptop, so volume is expressed in zettabytes (ZB) or yottabytes (YB) for generating explosive data.
Velocity refers to the speed of data that is processed. According to Devs_Data, with about 18.9 billion network connections, there are about 2.5 links per person.
Organizing data can be challenging for variety, as there are many different data types.
Businesses must make sure their data has value after analyzing volume, velocity, and variety.
Financial institutions have an enormous amount of data about their business and customers. The financial services industry is always increasing in competition, so companies must stay driven with insights and information. Big Data is an excellent opportunity for financial institutions to be a differentiator between the competition and be valuable for consumers.