What exactly is Big Data and Benefits of Big Data for Banking Industry?
Big data was born out of the necessity of data sets growing so large and complex that traditional tools are no longer sufficient to process this data. By aggregating large amounts of data from many different sources by leverage cloud computing, business intelligence (BI) makes big data very powerful for business decision-making, revealing insights and behaviors faster and better than otherwise possible with traditional BI.
The financial and banking industry has evolved by leaps and bounds over the past decade, when it comes to operations and service delivery. Surprisingly though, most banks still ‘conservatively’ practice traditional way and have failed to utilize the information within their own databases. Either the data is keep in traditional silo database or no put the effort in linkage each of the transaction, customer behavior and use for aggregate pattern and next banking need prediction and so on. Those are valuable business intelligence is us wisely that can help the banker ahead of their competition and create truly what the market needed product. However, that’s all about to change as the banking sector gears up to process immense volumes of data created and collected. Some industry experts expect a seven fold increase in the volume of data, before 2020. Big Data is huge step towards the development of banking industries, and will propel it into the 21st century. Let’s take a look at big data’s benefits for the banking industry:
1) Fraud Detection & Prevention
Banks and financial services firms use analytics to differentiate fraudulent interactions from legitimate business transactions. By applying analytics and machine learning, they are able to define normal activity based on a customer’s history and distinguish it from unusual behavior indicating fraud. The analysis systems suggest immediate actions, such as blocking irregular transactions, which stops fraud before it occurs and improves profitability.
2) Enhanced Compliance Reporting
Banks now have access millions or even billions of customers’ needs, and they can now use Big Data to cater to them in a more meaningful way. Cloud based analytics packages can sync in real time with your big data systems, creating actionable insight dynamically. Big Data will expand the banking industry in a way that will allow them to earn mores revenue through cost reduction. And by cutting down on unnecessary costs, the banking industry can provide customers with exactly what they’re looking for, instead of irrelevant information.
3) Customer Segmentation
Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments.
4) Personalized Marketing
Customer segmentation can further be used to create and deliver new schemes and plans, aimed directly at the specific requirements of their customers. By analyzing past and present expenses and transactions, a bank can get a clear understanding of how to get the highest response rate from their clients. Creation of personalized product offerings will cater to an untapped niche of personalized services that gives banks the ability to create more meaningful client relationships.
5) Customer next banking need prediction
The focus in on quality insight and relevancy. By consolidate or linkage all the customer previous purchase data across all the silo database and records from different kind of account, transaction history records and and pattern into Big Data. Banker are capable to perform the business intelligence (BI) and to use it for customer next banking need prediction, as such better work out the product for the customer proactively, and ahead of the competition.
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