There is no specific definition for Big Data. However, experts often call it a collective term that defines the technology used to process, analyze, group, and gather significant and complex data. According to the research, approx 90% of the data has originated in the past 2-3 years [1]. This suggests how Big Data has grown in recent years. Considering the current technology, it isn’t wrong to say that Big Data will soon be embraced by all sizes and types of businesses.
Big Data is no longer optional in the financial industry. Financial sectors such as banks have a significant amount of customer’s data. However, banks are not good at using customer data efficiently. Considering the current competition in the financial industry and the rising customer’s expectations, banks cannot afford to miss out on these rich data sets [2]. They should rather implement strategies and adopt the Big Data technology to use this data to their advantage. While many financial sectors have embraced Big Data to gain a competitive advantage over their rivals, others are still struggling to embrace this change.
Big Data Applications in Financial Service Industry
Financial industries can leverage Big Data to offer personalized experiences to their customers, ensure smoother management of their data, and provide them with data-driven offers. As mentioned above, many companies have already used Big Data. They are doing it the right way and getting instant results. Let’s see the major applications of Big Data in the finance industry.
An Easy Interaction through Social Media
Earlier, social media was confined to being a platform where people could interact with friends, colleagues, and social media users. Today, social networking sites are mainly used for brand promotions and business growth. Companies interact with their prospects on social sites and gain valuable insights. They plan their marketing strategies accordingly. Likewise, insurance companies, banks, and financial institutions can leverage social media to interact with their customers.
Low Operational Costs
We have seen how low-interest rates and increased competition in the financial sector have resulted in low-profit margins for banks and insurance providers [3]. It has become necessary for the financial sectors to reduce operational costs for efficient management.
Big Data automates many manual jobs. Analyzing the data, gaining insights, processing large and complex data, generating reports, and maintaining records are the common functions of Big Data management tools. This ensures efficient management of the financial business with low operational costs. With customer data growing exponentially, it’s nearly impossible for employees and traditional management tools to handle these complex data sets efficiently and at a low cost. Fortunately, the latest data management technologies have proven a great way to utilize and process this data accurately. For example, NoSQL Databases, Event Streaming, Machine learning, Artificial Intelligence, Internet of Things, Cloud Solutions, Distributed Processing, and Data Visualization tools promote efficient management and with low costs in financial sectors.
Analyze Your Company’s Financial Growth
Financial industries handle multiple assignments annually. It is nearly impossible for banks to analyze the financial performance of the entire unit (including different branches and employee’s performance) accurately. Big Data integration has indeed helped many financial companies in generating precise financial reports. This helps businesses to access and process important insights accurately.
Compensate the Loss of Personal Interaction
The growth in digital mediums has affected personal interaction. People choose online banking and insurance apps rather than paying a visit to the branch. However, it doesn’t affect the personal interaction as banks can gather customer’s data, analyze and process it with the Big Data integration. Their browsing history, time of interactions, and geo-locations can easily be tracked using the Big Data [4]. The financial industries can leverage this information to offer personalized services to the customers.
Data Security
With the growth in digital technology, we have witnessed the increased cases of cybercrimes and online frauds. People trust financial organizations. They deposit their money and carry out online interactions with banks and insurance companies. This increases the responsibility of the financial institutions to protect customer’s data and provide the users with a secure interaction medium for smoother and safer communication.
Big Data tools mitigate security risks. The authentication system is one such advanced tool that maximizes customer’s security by detecting any suspicious activities in customer’s behavior.
So, these were the major applications of Big Data in the financial service industry. The sooner the banks and insurance companies embrace this technology, the faster they will grow.
- Pearlman, Shana, “Big Data in Finance: Use Cases, Examples, Challenges, and Getting Started” Talend, 8th August, 2019, https://www.talend.com/resources/big-data-finance/,
- “Big Data in the Financial Services Industry – From data to insights” Finextra, 9th September 2019 https://www.finextra.com/blogposting/17847/big-data-in-the-financial-services-industry—from-data-to-insights,
- Chen, Mary, “How the Financial Services Industry Is Winning with Big Data/” Mapr https://mapr.com/blog/how-financial-services-industry-is-winning-with-big-data/,
- Ewen, James, “How Big Data Is Changing The Finance Industry/” Tamoco, March 9th 2019 https://www.tamoco.com/blog/big-data-finance-industry-analytics/,
