BIG DATA SOLUTIONS FOR BFSI
The Banking and Financial Services Industry (BFSI) in the past few years has had a lot of change. Almost all businesses in BFSI sector have been facing more challenging problems as a result of increased regulatory scrutiny and higher customer expectations. To cope with challenge and difficulty, the businesses have to save processing customer information time, improve efficiencies, detect errors and frauds, control risk, etc.
In order to achieve this, banking and financial services organizations are using big data technology to provide better services. These businesses gather a lot of information from social media, customer transactions, account records, and market feeds. Utilizing the insights generated from these massive volumes of data, businesses can learn more about their customers and use this information for getting a competitive edge over other business in BFSI sector.
Before learning about the role and benefits of big data in the banking and financial sectors (BFSI), let’s start by talking about what exactly big data means and its elements.
Big Data Explained
Big data consists of structured, unstructured, and semi-structured data, gathered by organizations, that can be utilized for advanced analytics applications, predictive modeling, etc.
Systems for handling and storing large amounts of data, together with tools to enable big data analytics applications, have become a common component of data management infrastructures in businesses. The five Vs are frequently used to describe big data:
- Volume: massive amount of data
- Velocity: speed at which big data is generated
- Variety: various data types (structured, unstructured, and semi-structured data)
- Veracity: the degree of data that can be trusted
- Value: disease detection, better treatment, reduced costs, …
Big data solutions provide the tools, methods, and technologies used to capture, store, search, and analyze data in seconds to find relationships and insights for improvements and get a competitive edge that have not existed before.
The Value of Big Data in Banking and Finance
Providing the assistance that the customer may need immediately is the primary way to improve the quality of financial services. This is just one piece of evidence that shows how useful big data will become as it enables the research of consumer behavior in the upcoming years.
According to the International Data Corporation (IDC) predicts that, by 2022, big data and business analytics solutions will reach $260 billion global revenue. That isn’t too surprising that the banking industry will contribute the most to this massive growth.
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Benefits and Advantages of Big Data in Banking and Financial
A Comprehensive View of Business: Employees can see the full picture thanks to data that is constantly updated and easy to reach data, help enhancing different departments cooperation and insight sharing. Big data will give insightful information on board market trends, internal process efficiency and consumer behavior patterns. Sosene certainly that you will make much more accurate strategic decisions thanks to these bases
Personalized Product: Big data allows for the tracking of a customer’s expenditures and previous transactions. With this insight, it is possible to forecast customer needs and interest rate of highlight products and services that will attract them. Thus, the bank’s revenue grows while ensuring maximum customer satisfaction
These insights will give banks numerous chances to cross-sell and up-sell to increase profit margins in the market. A lot of banks in the world are 60–70% more likely to sell to potential customers than current ones.
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Risk and Fraud Detection: Nowadays, banks are able to research detailed behaviors and patterns of the customer thanks to big data’s open source and access to information. This makes sure that any possible fraudulent transaction risks in investment banking will be identified, controlled, and their repeats avoided.
Moreover, the use of big data also enables banks to make sure that no unauthorized trades or transactions occur. By doing this, a crucial security measure that protects all exchanges is established, ensuring that financial crises are avoided before they even occur.
Real-time analytics and marketing: Instead of waiting for data to be processed and made available, data science now allows for real-time data analysis. As a result, BFSI sector will be able to catch the trend quickly and make decisions that put them ahead of the competition. Geotargeting, geofencing, and beaconing are several examples of real-time analytics.
In an ultra-competitive market, the banking and financial sectors (BFSI) need to understand what customers want and need, as well as when they need it. This enables organizations to create marketing campaigns that meet customers’ demands and win market share.
Analytics Prediction and Future Planning: Big data enables the immediate analysis of data sets from the past and present. This makes it easier to predict the directions in which the market will go, and which investments will be more or less viable based on those trends. This simplifies decision-making for financial institutions.
To summarize, increasing customer demands and restrictions have created a highly challenging for BFSI sector
Sosene has complete solutions for the development of products. Along with software development, we also provide business consulting, design, marketing, and business analysis. So, if you’re looking for a software company to solve your business challenges, please feel free to get in touch with us. We will assist you in finding solutions that match your requirements.
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