How to Leverage Big Data in Financial Services

Leveraging Big Data in Financial Services: Real-World Use Cases

How to Leverage Big Data in the Financial Services Industry.

The financial services industry, like many others, is being inundated with data. Finding ways to take advantage of new, unstructured data is the key to making sure financial services providers can gain competitive advantages by improving consumer insight, dealing with risk, meeting regulatory challenges and improving operational efficiency. As a result, the financial services sector is one of the major contributors to the big data market.

In order to get the very most from Big Data, financial services firms are realizing the benefits of carrying out Big Data analysis much faster in an industry where speed is important in gaining a competitive advantage. For those financial institutions that adopt the most up-to-date, timely Big Data analytics tools, what are the benefits?

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  • Gain consumer insight — Personal finance providers and banks of all sizes are starting to use the Big Data they gather from consumer activity to deliver more personalized products and services. Today’s consumers are insisting on a higher level of customer service and favor banks that can offer them services that others cannot. Big Data analytics can help provide this through the creation of a “recommendation engine” such as those offered to shoppers on Amazon.com.
  • Respond to greater regulatory pressures – Legislation has been brought in to try to create a more transparent environment and financial institutions are more accountable for their actions in terms of governance and reporting. Big Data analytics enable financial businesses to present audit trails and demonstrate enterprise transparency.
  • Analyze risk – The analysis of Big Data is helping banks and other institutions manage their risk more effectively. Payment platforms can now use Big Data to detect fraudulent transactions and behavior, while Big Data analytics that look at historical behavior can be used in the design of credit risk models.
  • Operational efficiencies – Financial enterprises are increasingly using Big Data to help inform their IT system reviews. Adopting Big Data analytics helps them to establish how their IT systems are performing and can also help businesses to make decisions about innovations they wish to invest in.

The message is clear – adopting Big Data solutions is essential to ensure your business is in the right position to make growing data a valuable asset rather than a liability.

Look for future blog posts that drill into the details of each of these use cases.