BigDataScalability.com – Big data is getting more popular today. In the modern digital world, big data is used actively in various industries, including the financial industry. Now, you’re about to see big data in banking, its benefits, and the application of big data. Everything is packed below.
Big data has a lot of benefits for the financial industry. This is going to ensure cyber security while increasing the loyalty of customers. Data science, especially in the financial industry allows someone to continuously store and analyze all information from digital and traditional sources.
The data scientist will also help create an electronic trail of every single client. Technologies like big data are going to help those organizations in financial industries. What is the importance of big data, particularly in the financial industry and in banking? Find the details below.
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The Importance of Big Data in Banking
A major way to provide top-quality banking services to clients is by providing the excellent services that each customer needs instantly. Big data is going to be more valuable especially in the upcoming years because it enables customer behavior analysis.
By 2022, global big data revenue and also business analytics solutions are expected to reach USD260 billion. No wonder the banking industry is going to be the largest contributor to the massive growth. Customers of banks today have a different attitude towards financial industries than before.
In past, customers needed to contact the bank’s physical branch to solve any issue. But today, customers can get answers to any question they have online. The bank branches’ role is changing now. Clients can use mobile apps to get online access to their bank accounts.
Benefits of Big Data in Banking
The banking industry is an engine that is now powering organizations, nations, and economies. This industry also produces data in massive amounts every second. Each transaction in the banking industry will leave a trace and also generate data.
However, the use of big data in many other sectors, like healthcare, start showing its true potential. Then, big data started to be used in the banking industry. The goal is to see the financial insights’ true potential that can be used for various purposes. Here are some advantages of big data in banking.
1. Customers can get personalized banking solutions
When the banking industry is combining big data with effective technologies and tools, the bank will get a much better understanding of each customer based on the inputs that are received by the bank. Some details the bank will get include the customers’ investment habits and shopping habits.
Some other details also include the financial or personal backgrounds of customers and their investment motivation. With those complete data and customer profiles, the bank will be able to prevent and predict churn. The bank will also be able to find the right way to solve the existing issues.
Big data in banking industry will help the bank to know each customer. With this knowledge, the bank will be able to create services, products, and many offerings based on the existing profiles of each customer. The bank can tailor its offers to meet the specific needs of customers.
2. Big data in banking eases customers segmentations
Customer segmentation will let the bank target the client in a better way. The bank can target the client by using more appropriate marketing campaigns. Those campaigns will be tailored so that they can meet the client’s needs in a much more meaningful way.
Banks can combine artificial intelligence and machine learning with big data in banking to get valuable insights into customers’ behavior. This will also let the bank optimize the customer experience. Next, the bank can use various parameters to categorize customers.
For example, the bank can track and also trace each transaction of each customer to categorize customers based on their net worth or preferred credit card expenditures.
3. More effective in analyzing customer feedback
The tools of big data in banking are going to use feedback to provide some customer comments, concerns, and questions to the bank. The feedback is going to assist the bank in responding to their customers promptly.
As a result, customers are going to remain loyal to the bank since they believe that the banks value the feedback they share and are willing to communicate with the customers immediately.
4. Detecting and preventing fraud
Among so many challenges the bank should face, the most difficult one is detecting fraud and also preventing questionable transactions. But big data in banking allows the bank to ensure that there is no unofficial transaction happening.
Big data will also make sure the overall security and safety of the financial industry. Banks are allowed to use big data in preventing fraud and making customers feel secure. To do it, the bank should monitor the spending patterns of each customer and identify any unusual behavior.
5. A clear and wide view of business
Easy to reach and instantly updated data will increase the insight and collaboration sharing between various departments. This is going to allow the employees to see the big picture. Big data in banking will provide valuable insights into customer behavior patterns and broad market trends.
Big data will even provide insights into internal process efficiency so that the bank can make more accurate strategic decisions.
Applications of The Financial Industry’s Big Data
In the financial industry, especially in banking, big data can be used in various ways. Big data has a lot of advantages when it is applied in the right way. Below are some examples of big data applications in the banking industry and how big data can help the banking industry.
1. Customers profiling
Big data helps the banking industry in profiling its customers. This way, the bank can serve an individual customer based on each customer’s transactional patterns and history over time the customers have been with a bank.
This is also going to let the bank create tailored solutions and plans for clients. Big data in banking will boost the experience of the customer and will help the bank to differentiate itself from the other banks and to retain its customers.
With big data, the bank can also target various products to various types of customers by using the customers’ demographics.
2. Fraud detection
The bank is now able to detect fraud before the fraud happens. To do this, the bank will analyze the data and use statistical computing. With unique algorithms that can detect fraud, the bank can track and also compute customers’ spending and behavioral patterns.
Furthermore, the bank will be able to identify and also gauge if the customer is on financial ruin verge and may be willing to defraud a banking institution. Investment banks, retail banks, and private equity firms have a specific risk management department that is dedicated and relies on big data.
3. Making lending decisions
Lending is an important decision in the financial industry. It is critical for the bank to choose only the right clients who are financially sound and creditworthy so that they can pay off the debt. Besides, the banks will also rely on the agencies’ credit ratings when assessing the creditworthiness of a customer.
Because of the big data in banking, the bank can get new insights that help the bank consider some other factors like the spending habits of each customer, the volume and nature of transactions, and the other details when deciding whether the bank will lend to the customer or not.
Big data in the financial industry has broadened the horizon both for financial institutions and bankers. Big data will provide financial institutions and bankers with more knowledge and data.
4. Compliance with regulations
With big data analytics, the bank can now keep records and comply with the regulations much more efficiently and effectively. The bank can also effectively track and manage all regulatory procedures and also keep records with the central banks.
5. Cybersecurity
Online financial frauds and cyber-attacks become more common today. Besides, embezzlement becomes a problem that should be faced by many organizations around the globe. So many big organizations, especially banks, becomes victim of cyber-attacks.
Cyber-attacks are now not only targeting the money of the banks but even the information of each customer. But banks can now set up robust internal control systems. They can use artificial intelligence and big data.
With artificial intelligence and big data, the customer will be able to use advanced algorithms to track the behavior of their customer. And if financial terrorism happens, the bank can collaborate actively and share the insights they got from Business Intelligence tools and big data in banking.
Challenges of The Banking Industry’s Big Data
The banking industry is also facing some challenges when implementing big data. The bank industry needs to know the challenges that it will face when trying to implement big data technology and tools. Some challenges that the banking industry should face include:
1. The legacy systems can’t keep up easily
The banking industry is slow to innovate. This makes the adoption of financial technology becomes so high. Many traditional financial institutions don’t have a chance against startups that are agile and customer-centric.
Big data is something new for traditional systems. Many legacy systems aren’t able to handle the increasing workload of big data. When the legacy systems are trying to collect, analyze, and store the data in required amounts, the outdated infrastructure may jeopardize the stability of the overall system.
As a result, financial organizations must completely rebuild the systems or increase the processing capacity so they can meet the challenge.
2. More data causes the bigger risk
When there is more data, the risk will increase, especially when the banking industry is still using the legacy system. Banking providers need to ensure that the data of users they process and collect is secure at all times. Furthermore, the regulations of data security become more stringent.
3. Big data in banking becomes unmanageable
The combined volume of data in various types may cause the business to struggle just to keep up. This challenge becomes clearer when the business is going to separate the useless data from the useful one. The potentially useful data’s proportion may increase.
But there is still a lot of irrelevant data that the banking industry should sort out. This means the business should prepare some methods and strengthen the, to analyze more data and find some data applications that have been deemed irrelevant.
Despite the entire challenges above, the big data benefits for the banking industry can outweigh the risks easily. Data becomes a valuable resource for the banking industry because of the money it saves, the resources it frees up, also the insights it provides.
The application of big data in banking industry is now dramatically progressing. The banks that collaborate with big data can now provide much better and more improved services and offers promptly. The bank can also reduce its operational costs because of the big data.
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