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? ›

With big data, businesses can optimize processes, allocate resources efficiently, and streamline workflows to minimize costs. Big data is transforming the banking and financial sector in many ways, helping banks make informed decisions, improve the customer experience, and much more.

How does big data affect the banking industry? ›

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 does data science affect the banking sector? ›

Mitigating Risks:

Banks are more capable to recognize and manage risks thanks to analytics. Banks can safeguard businesses and their clients by spotting any fraud, money laundering, or credit issues early on through the analysis of patterns and deviations in financial data.

What is the role of data in the banking sector? ›

The importance of data analytics in banking:

Data analytics enables banks to assess and mitigate these risks by analyzing historical data, identifying patterns, and predicting future trends. This helps in making informed decisions, reducing potential losses, and ensuring regulatory compliance.

How big data has changed finance? ›

Big data has completely transformed the finance industry. The sophisticated analytical methods and machine learning algorithms help companies uncover hidden trends and patterns that facilitate quick and accurate decision-making.

What is big data strategy for banks? ›

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 used in improving customer experience in the banking sector? ›

Improves risk management: Big data empowers banks with the tools to proactively identify, assess, and mitigate risks across various dimensions, including fraud, credit, operational, and market risks. For instance, it promotes better credit risk management by providing a more holistic view of borrower behavior.

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 does data analytics help a bank? ›

Data analytics can analyze historical market data, news sentiment, and other relevant information to predict market trends, helping banks make informed investment decisions.

What is the importance of data and database into banking? ›

Efficient database administration provides valuable insights into customer behavior, market trends, and business analytics. By leveraging data analytics, banks can make informed decisions, develop effective marketing strategies, and identify potential areas for growth.

What are the major applications of big data in banking, retail, and communication? ›

The Role of Banking Analytics
  • Track customer spending patterns.
  • Segment customers based on their profiles.
  • Implement risk management processes.
  • Personalize product offerings.
  • Proactively address customer needs.
  • Incorporate retention strategies.
  • Collect, analyze, and respond to customer feedback.

Why is data quality important in banking? ›

High-quality data is pivotal for robust risk management in financial organizations. Accurate data feeds into models that predict credit risk, market volatility, and potential fraud. These models guide everything from loan approval to investment strategies.

How are banks leveraging data? ›

By harnessing the power of data to understand consumer behavior, preferences, and financial needs in depth, financial institutions can unlock the potential of personalized marketing, transforming the way they engage with customers and members and setting new standards for account holder satisfaction in the digital age.

Why is big data important in finance? ›

There is a valuable saying in the finance industry — numbers don't lie. Big data can reveal real-time performances and developments within the stock markets. The data analysts use machine learning to create algorithms that monitor the prices, trades, fluctuations and trends.

What is the impact of big data in accounting and finance? ›

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 impact Fintech? ›

Big Data is currently revolutionizing the Fintech sector in terms of data security, for example, as well as in fraud detection. AI, coupled with data analysis, allows for the creation of more detailed customer profiles and the prevention of suspicious activities.

How does big data affect the industry? ›

The use of Big data assists in operational optimization, customer experience enhancement, fraud reduction, and inventory management. Retailers can dive deep into consumer shopping patterns and preferences, as well as market trends, to create targeted marketing campaigns and personalized offers or discounts.

What is the role of big data in finance? ›

There is a valuable saying in the finance industry — numbers don't lie. Big data can reveal real-time performances and developments within the stock markets. The data analysts use machine learning to create algorithms that monitor the prices, trades, fluctuations and trends.

Why is data analytics important in banking? ›

Analytics can be used to identify and rate individual customers who are at risk of fraud and then apply different levels of monitoring and verification to those accounts. Analyzing the risk of the accounts allows banks and financial institutions to know what to prioritize in their fraud detection efforts.

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