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  2. > Big Data Opportunities in Retail Banking

Big Data Opportunities in Retail Banking

  • October 2013
  • -
  • GlobalData
  • -
  • 24 pages


Table of Contents

Big Data analytics can uncover hidden patterns, correlations, and other useful information. The insights that can be drawn from Big Data analytics can help financial services providers tackle mission-critical issues, such as improving customer understanding, customer profitability, and managing risk more effectively.

- Discover how to make the most of the opportunities offered by Big Data.
- Sculpt future strategies by harnessing lessons from best practice examples.
- Keep ahead of the curve by learning the potential challenges of applying Big Data.

Reasons To Buy
- How can financial services providers seize the opportunities in using Big Data?
- What is the untapped potential of Big Data analytics in financial services?
- Which providers are being innovative and pioneering the use of Big Data in financial services?
- What is the future of Big Data usage in financial services?
- What are the key obstacles to utilizing Big Data?

Key Highlights
Big Data analytics can provide valuable insights that can be used to improve existing products and create new ones. It can reveal if there is strong demand for a product that a bank is not currently offering or if it is losing customers due to a flaw in its offering.

Big Data analytics can help banks understand their customers at a more granular level and more quickly deliver targeted personalized offers. This enables higher offer and cross-sell acceptance rates that improve customer profitability.

The management of risk has become a key priority for banks. One of the exciting applications of Big Data is improving banks' credit risk management as well as their ability to detect and prevent fraud, financial crime, and security breaches.

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