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How Big Data Analytics are Used in the Banking Industry



How Big Data Analytics are Used in the Banking Industry

Image by Gerd Altmann from Pixabay

The banking and finance industry seems to have gained a wide range of traction, all thanks to the ever-emerging technology. And speaking of disruptive technology, I am talking about none other than Big data. 2023 is about to begin and to be precise, Big data or conducting evidence-based decision-making is no longer a buzzing term but also seems to have become a sure-shot norm to grow your business in the shortest span of time. Have you ever wondered how much data we create every day through these financial transactions? Yes, you read it right! With each and every message you send, any debit or credit card transaction taking place, any website or any form you fill that creates your data. According to several sources, more than 2.5 quintillion bytes of data are created a day in and day out. Due to this several endless opportunities are created as well which brings us to this post, how big data is used in the banking industry.

The use of Big Data in the Banking industry

Now, this is something we all know, digital banking technology is used by more than half of the entire world’s population. And that is why more and more financial and banking service providers are found leveraging the power of big data technology and becoming more efficient and well-optimized in regard to their services. Now you must be wondering what is so fascinating about big data technology. To be precise, the financial technology(fintech) allows organizations to gather as well as analyze large sets of data just to check out customer behavior and their preferences. Whether you want demographic-related information or how much does the customer spend, what is the product service usage, any events of that customer’s life which are worth considering, is the relation between the banks and the customers strong, any service preferences, all these can be well taken care of by making the most of the big data technology. In addition to all these,

  • Get a thorough insight by simply tracking customers spending patterns
  • Fraud detection
  • Managing risks
  • Offering a well-tailored experience for every individual
  • Collecting, analyzing and responding to the feedback given by customers
  • Offering personalized products
  • Creating more and more opportunities for upselling and cross-selling
  • Implementing relevant risk procedures

Further below, I would like to mention how big data analytics is used in the banking industry.

The usage of Big Data in the Banking industry

#1 Offering a personalized experience

One of the best ways to make use of big data technology, especially in the banking and finance industry is by offering a personalized experience to the end users. Now imagine you are planning to host a family dinner at your place. Do you think everyone will like one type of meal? Of course not, some might prefer Indian, some might choose Japanese cuisine, and some might like Italian, So instead of cooking one particular meal, what if you try to cater for everyone by offering their favorite meals? I am pretty sure they will be pretty much pleased and have an amazing time, right? Similarly, what if the banking tends to offer different services for different individuals by analyzing their previous purchase history or transaction history? I am sure everyone will be so pleased that they wouldn’t think of switching to your competitors. Fortunately, the banking culture is transforming to a great extent. Profiling is pretty much in vogue but most of the time among the online version of the banking industry. Though there are traditionalists or conventionals who tend to prefer the old concepts and methodologies. In the present scenario, whether it’s about transferring money or depositing checks, or paying bills, everything can be taken care of by using smartphone devices. By the use of big data technology, the banking industry can create a complete picture of what exactly their customers prefer, some type of a generic point of view but an effective one.

#2 The use of Artificial Intelligence

Another important method to consider is artificial intelligence in the banking industry. After the hype of Pokemon Go’, artificial intelligence is no longer limited to a specific industry, in fact it has been growing by leaps and bounds across the globe and banking or finance is not an exception. You see there are times when customer service agents are preoccupied and unable to respond right then and there, here’s the time when artificial intelligence technology can step in. By using chatbots, customers can have their immediate answers and a sense of peace that someone is there to listen to their issue and ready to solve it. With the help of customer profile information and behavioral patterns, personalized responses can be offered. In fact, these kinds of disruptive technologies can also recognize relevant emotions and respond sensitively by not hurting their valued customers’ feelings.

#3 Fraud Prevention

Another crucial method or approach to consider is fraud prevention. One of the fastest-growing thefts is fraud and detecting them is pretty much crucial within a given time. Back in 2017, 16 million identity theft cases were determined and the numbers haven’t lowered down since then. Big data analytics offers great help in securing customer information to a great extent. Several business intelligence tools and big data analytics are used to evaluate risks and prevent fraud. Several interest rates for individuals can be determined, credit scores, pinpoints fraudulent behaviour, and personal and industry-wide financial decisions can be made.

And that’s all for now!

The banking and finance industry will be growing by leaps and bounds, and big data analytics will improve at a fanatic pace. In case, if you fall behind, you may have a lot to lose. In case, if you have any doubts and queries, feel free to mention them in the comment section below.

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