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Big data technology is at the centre of everything financial services organizations do and will continue to drive innovation well into the future. Financial services firms today can leverage big data to address the challenge of new revenue streams through data-driven offers, provide better services to customers, retain existing customers, acquire new ones and maintain their competitive edge in a technology landscape that is constantly altered with new business models based on digital transformation.

Big data can help financial services firms in the following ways:

  • Digitally transform the operations as they are challenged to improve business processes and develop new capabilities and business models.
  • Personalized recommendations can be made as a part of data-driven offers and this can be a great source of revenue generation through emerging digital streams
  • Getting equipped with digitally desperate technologies to compete with FinTech companies, which use cutting-edge technology to provide customers with banking and financial services

It comes as no surprise that the banking and financial sector generate enormous volumes of data and when it comes to handling them it is a daunting task. Customer interactions with the banks have largely become online leaving few areas like submitting forms or withdrawing cash from ATM’s, thanks for digital transformation.

Big data analytics have been helping banks in a way that was not possible before, partly due to increase in the number of electronic records. Financial services are capitalizing on the digitally disruptive technologies to store data, derive actionable insights and improve scalability.

Harnessing the technology in the design and delivery of financial services and products gave birth to FinTech services. FinTech applications empower businesses to disrupt by providing online transactions. More organizations are discovering how big data enables them to tackle the challenge of data-driven disruption by delivering solutions that make investment management effortless.

Reduce errors and fraudulent with robust risk management

Managing money lending process has always been complex and difficult but Business Intelligence tools enable banks and financial services to accurately identify risks. Leveraging big data analytics, banks can gain insights into the ongoing market trends and zero in on reducing on increasing interest rates for a variety of targeted segments.

The best way to reduce the cost of correcting data entry errors is to find and fix it before it enters the systems. Exactly this can be achieved by leveraging big data that can accurately find anomalies in customer data. Fraud has evolved. Conventional processes are unable to detect fraudulent practices but with fraud detection algorithms it is possible to gain deep insights about the customer’s credit score which in turn makes it easy for banks to approve their loans.

The promise of personalization that big data analytics offers to customers

Data offers businesses endless opportunities, but they must figure out how to best discover access and analyze it. That’s intelligence and that’s where big data analytics helps banks in gaining deep insights into understanding customer’s thinking patterns based on the inputs gathered from their shopping trends and most importantly financial details. If you’re betting your future on personalized banking solutions to increase the loyalty of a changing customer base, don’t overlook the state of your customer data. It comes as no surprise that for banks and financial services, properly engaging customers is a great way to differentiate and distinguish themselves from the crowd. Lead generation is a top focus across all financial and banking organizations, with personalized banking solutions, your team is able to meet your mission.

Ensures compliance with regulatory filings

Meeting all the compliance requirements set by regulatory can be difficult and complex for all financial organizations. But managing them wisely is what differentiates successful organizations from those that are less successful. Meeting regulatory compliance can be intensively arduous if they choose narrowly focused tools for specific use-cases. With business intelligence and big data, you’re able to meet most compliance goals.

Banking and financial organizations can drive real business value by capitalizing on the advantages of big data analytics. When you’re migrating more and more data to big data analytics, it’s crucial that you do it right. Time and time again, we see companies spend heavy investments in big data projects without leveraging its capabilities.

Find out how these successful big data analytics projects are structured, what policies they have in place, and what strategies they do—and don’t—follow to accelerate the efforts.

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