How Big Data Sector Changed the Banking Sector (2024)

K Benjamin / 3 min read.

How Big Data Sector Changed the Banking Sector (1)

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How Big Data Sector Changed the Banking Sector (2)

Unlike the early days when everything was done manually, these days the evolution of technology has changed how different sectors perform. One of those industries that have been impacted by the growth in technology is the banking industry. During the early days, the sector handled communication manually which greatly limited the sector. It was difficult for the financial institutions to efficiently transfer data from one point to the other and hence holding an account those days was ridiculously expensive.

As time went by, growth in technology hit the data sector and everything started to change. The banks could now use technology in gathering and saving clients data, a move that improved the efficiency in which the sector operates. As growth in technology continues to grow, the banking sector is offering their services online, hence making it easy for anyone to access their services from wherever. Explained below are some major changes we are experiencing in the banking sector.

Delivering Services in the Sector has improved

Data in the banking sector is very substantial such that it is difficult to handle it manually. Just think of this, what could happen if an account number has to be searched manually in files? We could have unending long lines in banks. But this has been digitized as the data is now stored in computers that an entry of the account number shows all the details of an account holder in few seconds. This has made it easier for the customers to get the services efficiently. Opening a bank account has also been made cheaper and available to everybody in the world. One can even use a mobile phone to access banking services, and this has spurred development of financial institutions.

Management of Arising Risks

Detection of frauds in banking institutions has been made easier and quicker. Early detection of frauds is a risk management tactic as it is easier to make a follow up hence reducing the number of risks faced. The significant data sector finds and brings into display information on frauds. Some banking institutions have come up with their apps that help customers to monitor activities on their cell phones such as transfer of funds, tracking their transactions and receiving notifications. This has built trust with the customers hence the recent development in the banking sector.

Global Reach

Online technology has changed the way banks operate entirely by introducing critical players in the sector. Banks now offer their services across the world. Information on the cloud has made it easier to access information at any time anywhere in the world. The growth of businesses and firms has led to the growth of IT thus increasing the amount of data shared.

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Enhanced reporting by customers

Banks can now receive numerous customer requests and needs, and by using the significant data available, the banks can now efficiently serve them. This has reduced the cost and increased revenue generation by more significant amounts. The banks are also able to fulfill the customer’s exact needs thus they are more helpful than before.

Segmentation of customers

Big data has brought into light customer spending habits and thus simplifying the task of fulfilling their requirements. The banking sector is also able to group clients based on preferences and choices of services accessed, and therefore it is easy in advertising as the banks know the target groups of specific advertisem*nts.

Concerns about data security

Technological development has put banks at risk of hackers. Phishing is one way used by hackers to steal money from banks something that almost impossible back then. The banking sector is also working tirelessly to improve their cybersecurity measure to ensure that the client’s data and funds are safe.

All in all, the data sector has increased business transactions across countries and as well as continents. This has led to the development of foreign trade which has hence helped in the event of third world countries through foreign investments.

How Big Data Sector Changed the Banking Sector (3)

About K Benjamin

K Benjamin is a professional accountant and Business writer at Weaccountax.He loves to write about hot topics on like Big data, Accountancy, and finance. Visit this page for more details about him.

How Big Data Sector Changed the Banking Sector (2024)

FAQs

How Big Data Sector Changed the Banking Sector? ›

Big data in financial industry provides banks and financial institutions with in-depth insights on such things as customer behavior, state of internal processes, and external risks. As for the IoT, this technology can significantly improve security by alerting about fraudulent behavior in real-time.

How does big data affect the banking industry? ›

A: Big data enables banks to gain valuable insights into customer behavior, improve risk management practices, enhance operational efficiency, drive innovation, and maintain a competitive advantage in the market.

How big data is changing the finance industry? ›

The use of unstructured data

Unstructured data, such as text, images, and videos, are becoming increasingly valuable in the finance industry. With the competition for Alpha intensifying, investors are turning to the analysis of unstructured financial data using sophisticated models.

How does data science affect the banking sector? ›

Data science and analytics significantly streamline banking operations, leading to substantial cost savings and efficiency gains. For example, automated data processing and predictive maintenance can reduce operational costs by up to 30%.

How big data is used in improving customer experience in the banking sector? ›

The use of big data in banking makes it possible to improve service quality and stimulate customer flow. This leads to the emergence of new products that better meet current requirements, which in turn drives demand, sales, and retention.

What is the impact of use of big data in decision making in banking sector of Saudi Arabia? ›

This study reveals that the big data analytics helps in targeted marketing, which, in turn, helps in better decision making in the banking sector in the Kingdom of Saudi Arabia.

Why is data important in the banking sector? ›

The banking sector needs to utilize its data for analysis and better decision-making. When you analyze data, you will be able to determine how you can maximize your profits and improve business relationships and customer service. That's where you need data analytics.

Which banks use big data? ›

7 Well-known Case Studies of Big Data Analytics in Banking Sector
  • JPMorgan. JPMorgan is one of the largest investment banks in the world and one of the early adopters of big data in financial services and banking. ...
  • BNP Paribas. ...
  • Citibank. ...
  • Bank of America. ...
  • Wells Fargo & Co. ...
  • Capital One. ...
  • Deutsche Bank.

How big data is transforming industries in big ways? ›

As big data is mined and analyzed, businesses are able to gain a more comprehensive view into their processes and gain valuable insights about their customers' interests and behaviors. In sum, big data can streamline business intelligence processes and help businesses better address the needs of their consumers.

How will big data influence the future of accounting and finance? ›

But, what does big data mean for accountants? Analysing big data allows accountants to gain a deeper insight of the clients' businesses to make more informed decisions ultimately leading to improved financial forecasting, enhanced risk management and more accurate financial reporting.

How does big data help investment banking? ›

The investment management company uses big data in finance to analyze vast amounts of financial data, economic indicators, and market trends. This helps them gain insights into potential investment opportunities and risks.

How is data science changing the finance industry? ›

Data science techniques are transforming finance by converting raw data into actionable insights: These techniques provide tools for risk management, pattern recognition, and risk prediction. Machine learning algorithms are key in detecting fraud by flagging suspicious activities.

How can data analytics be used in banking? ›

Data analytics is used in banking for credit scoring, fraud detection, customer segmentation, personalized marketing, forecasting financial trends, and optimizing branch locations, among many other applications.

How does big data analytics impact the banking sector? ›

Big data and statistical computing empower banks to detect potential fraud before it even occurs. Specialized algorithms track and analyze spending and behavioral patterns, allowing banks to identify individuals who may be at risk of committing fraud.

How do central banks use big data and machine learning? ›

A majority of central banks use structured and unstructured big data to support their economic analyses and policy decisions, including in the areas of economic research, financial stability and monetary policy.

How are banks leveraging data? ›

Historical data lays the foundation for banks to analyze each of their customers' financial habits individually and make predictive insights and recommendations on how they can save more money, make better investment decisions and reach their financial goals.

What challenges were the banks facing that big data could help solve? ›

Fraud detection.

Banks can use AI and machine learning algorithms to flag suspicious activity before it occurs. Big Data analytics in financial services can be used to detect fraudulent activities such as money laundering or identity theft by analyzing patterns in transactions across multiple accounts.

What banks use big data? ›

Fraud prevention was only the beginning. JPMorgan is also actively using big data for deciding the creditworthiness of people applying for loans. To do that, the bank's system analyzes internal financial reports, as well as various unstructured information: emails, social media posts, and even phone calls.

What is the impact of big data in IT industry? ›

Big data can reveal opportunities previously unknown to organizations by enabling comprehensive analysis of large data sets. With big data sets, businesses can map complex patterns, identify emerging trends, and create new products- opening up new horizons of possibility in the competitive landscape.

How does big data impact financial accounting? ›

Big data analytics in accounting allows for the collection and analysis of vast amounts of financial data from various sources. This enables accountants to gain deeper insights into a company's financial performance. They can identify trends, patterns, and anomalies that might go unnoticed with traditional methods.

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