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Originally Published on: Quantzig|Top 4 Advantages of Big Data in The Banking Industry

Transformative Shift in Operations and Elevated Service Standards in the Financial Sector

In recent times, the financial sector has undergone a remarkable transformation, reshaping both operations and service delivery within the banking industry. Despite this evolution, a striking revelation emerges – many banks have yet to fully exploit the informational potential within their databases. This narrative is gradually changing as the financial sector prepares to navigate the vast volume of data amassed and generated. Industry experts predict an unprecedented surge in data volume by 2020, positioning big data in banking as a monumental stride toward industry expansion and affluence. Let’s delve into the myriad advantages that big data brings to the financial sector.

Big Data in Banking

Prevention and Detection of Fraud: Big data emerges as a pivotal tool in addressing a primary challenge confronting banks today – fraud. Empowered by analytics and machine learning, banks can discern between fraudulent interactions and legitimate transactions. By defining normal activity based on customer history, big data aids in identifying unusual behavior indicative of fraud. Implementation of big data in banking systems prompts immediate actions, such as blocking irregular transactions, preventing fraud before it occurs, and enhancing overall profitability.

Customer Segmentation: Leveraging big data in banking provides comprehensive insights into customers’ spending patterns, fostering a profound understanding of their needs. Banks can categorize customers based on various parameters, including preferred credit card expenditures, commonly accessed services, and net worth. This customer segmentation empowers banks to target their audience effectively through relevant marketing campaigns.

Personalized Service: Customer segmentation facilitated by big data in banking services allows the creation and delivery of schemes and services designed for specific customers according to their requirements. Past and present expense analyses guide banks on how to elicit a higher response from their customers. Personalized products and services assist banks in establishing more meaningful relationships with their customers.

Risk Management: Early detection of fraud is integral to effective risk management. Big data plays a crucial role in efficiently managing risks by presenting vast data on a single platform, minimizing risks to a manageable number. Big data's pivotal role lies in integrating the requirements of the banking industry into a centralized platform, helping banks reduce fraud and manage risk effectively.

By staying abreast of big data and emerging trends, companies in the financial sector can better understand client requirements, leading to improved financial services. The implementation of big data in banking is evolving and is poised to be fully embraced by the entire industry in the near future.