In today’s data-driven world, data is a powerful tool in the development of several big industries. With the proper implementation of data analytics, tons of vital information can be used to improve, enhance, and grow several important industries of the country, ultimately leading to the growth of the economy. One such industry that drives the economy and is largely dependent on voluminous data is the banking and finance industry. It generates, records, and handles a huge amount of data daily that with the help of data analytics has contributed to its growth and development in the past decade. There is an enormous amount of data and information within their database that they are utilizing to improve operations and service delivery.
Big data analytics in banking and finance is an emerging trend and this analytics technology is expected to help the banking industry grow by leaps and bounds. With the integration of big data applications, banks are taking the big step towards the future. They are prepared to process huge volumes of data created and collected for the future growth of the banking and finance industry, as well as many other businesses. Every transaction you make, every SMS you send, every visit you make to the bank, call logs, app use, and more, builds into a gargantuan amount of data that has the ability to open up new avenues and opportunities for economic growth.
Since digital banking is one of the primary ways of carrying out banking activities, just imagine the amount of data we are creating daily. It is enough to understand consumer behavior and expectations, improve operations, customer experience, and become more efficient and profitable. With the start of the big data revolution, the banking and finance industry has realized the immense opportunities it can provide. Let’s dig deeper into the subject that is transforming the world.
What is Big Data?
With the advent of the modern internet, banking and finance institutions began wondering what to do with the huge amount of information stored in their database. Big Data provided the ultimate solution and opened new avenues by converting the data into meaningful information that they can use to benefit themselves and their customers.
It is important to understand that Big Data has got nothing to do with the volume or size of the data collected and created. Instead, it is a reference to large amounts of data that is generated from various data sources in different formats. It is the field of study that includes methods to analyze, extract information, and tackle huge data sets that are too large and complicated to be studied by traditional data processing applications.
Big data has some key elements associated with it. It includes volume, variety, velocity, veracity, and value.
1. Volume: The primary concern of big data analytics is the volume of data. It enables to process high volumes of low-density, unstructured data. There is no value attached to this data. For some organizations, it could be small and for others, it could be really large.
2. Velocity: It is the rate at which data flows in and processes.
3. Variety: This refers to many types and formats of data available. This is important because big data is dealing with unstructured and semi-structured data.
Value and veracity are the two V’s that were linked with big data recently.
4. Value: This is a reference to the intrinsic value of data which makes it more meaningful.
5. Veracity: The data will hold any value only if it is truthful and one can rely on the information provided.
History of Big Data
Big data is relatively a new concept, and most of the available data big data uses was created only a few years ago. However, the attempts to study and understand the large and complex volume of data has been there for a very long time. The earliest instance of using data to track something dates to 7000 years ago during the time of the Mesopotamian civilization.
It was in 2005 when the term Big Data came into existence. It was coined by Roger Mougalas from O’Reilly Media. It was used to refer to the huge amount of data that was not only difficult to deal with but also process, using traditional channels. The same year, Hadoop created Yahoo! in an attempt to index the entire World Wide Web. However, now, Hadoop is an open-source platform for reliable and scalable processing.
With more and more technological innovations and the emergence of social networks, greater amounts of data were created. However, no one had a clue what to do with this data. The Indian government’s Aadhar card aims to store iris scans, fingerprints, and photographs of each one of its citizens. So far, this is the largest biometric database in the world.
In 2010, an American businessman and software engineer named Eric Schmidt informed the world that we create 5 exabytes of data every two days, now. This is the amount of data that is equivalent to data created from the beginning of civilization up to 2003. This is the reason for the rise of innumerable big data startups that help businesses, industries, and governments to make meaning of this information and grow further.
Advantages of Big Data
Big data can benefit us in many ways, such as:
Big data can be used for cost reduction. Several big data applications enable the users to not only store but also analyze and identify ways to perform the business right.
A large amount of data can help in analyzing data and learn how to be more efficient.
The findings can provide answers to make quick decisions and be more efficient.
By learning more about customer behavior and expectations, one can use this tool to create new, improved products and services that will match the needs of your customers.
Its usefulness in understanding market conditions and trends contributes to its popularity. With the help of in-depth analysis, companies can learn what products are liked by their customers and products disliked by them.
Businesses can even track feedback about their brands. They can track what the customers are complaining about and what they like. This can help organizations in maintaining their reputation.
It allows companies to make predictive analyses that will help them stay ahead in the competition.
And by analyzing the market, it can help companies channelize their efforts towards profitable avenues.
Importance of Big Data in Banking and Finance
1. Fraud Prevention and Detection:
The biggest concern of the banking and finance industry is the prevention of fraud and cybercrimes. Using all the information available, big data implements knowledge to understand unauthorized and unexpected behavior, and prevents and detects fraudulent activities. This makes the role of big data in the banking industry even more significant and makes banking space a safe zone.
2. Better Regulatory Compliance:
For smooth functioning of banks, it is essential for them to meet the criteria set by government regulatory authorities. However, it gets difficult because they have thousands of customers to deal with daily and maintain their records. With the help of cloud-based big data analytics, this process has become simpler and even more cost-effective.
3. Understanding Customer Expectations:
Big data application empowers banks with the information they require to improve their services and meet customer expectations. This is important to stay ahead of the curve and strengthen their customer base. Better analysis of customer’s transaction history also enables banks to create segments and categories of their customers based on various criteria. Accordingly, they can create tailor-made marketing campaigns keeping in mind their target audience.
4. Creating Personalized Products:
Customer categorization can be further used to offer personalized products to their customers, meeting their specific needs and requirements. This not only helps them create a niche of personalized products but also creates a loyal customer base with meaningful client relationships.
5. Risk Management:
As mentioned above, fraudulent activities are the biggest concern of this industry. However, big data helps measure and analyze risk involved in loan lending processes. This helps them in reducing risks to a significant number. With the help of centralized networking, Big data applications reduce the chances of losing sensitive data.
6. Overall Performance:
Big data is a great technological addition not only to banking but also to other top world industries. It is incredibly effective in enhancing employee performance and efficiency. Data analytics help them streamline their efforts to products that are more profitable and will scale better in the market. It’s easy to keep up with what works and what doesn’t.
7. Customer Service:
With all the information about every individual customer available at just one click, it simplifies decision making and several tasks. It helps in streamlining processes and saves time and money. All of this positively impacts banks’ methods of service delivery and help them cater to their clients better. Support and help centers receive a huge amount of data every day, particularly feedback. This allows them to perform effective customer feedback analysis and deliver services that will benefit their customers.
The Role of big data in banking is significant. It is one of the greatest technological innovations that made banking easy and simplified banking services. Big data gives a comprehensive analysis of the entire business, which includes customer behavior and internal process. Meanwhile, with all the knowledge and integration of other technological trends like machine learning and artificial intelligence, banks and businesses can streamline their internal activities and processes for improved efficiency. Additionally, it eliminates the chances of human error from critical processes. It provides an enhanced ability to solve problems and make better decisions.
Big data has been in use for a while. However, the banking and finance industry has barely scratched the surface. It is yet to explore its maximum potential. With all that said, it is assured that big data in the banking industry can help several big and small businesses to grow and expand in the future.