Big Data: Uses & Challenges For Financial Services

[CharlieTriangle]

Financial Services organizations are increasingly turning to and leveraging big data.

There are a number of reasons why they do this. Regulatory compliance, fraud detection and prevention are examples, but it is also used in more of a retail format to map their customers buy behavior, and gain a greater visibility into a customer's buying journey.

This can have a positive impact on improving customer conversion rates, avoiding costly churn and lowering customer acquisition costs. Plus it allows them to develop new data-driven personalised marketing campaigns and products to increase sales.

Big Data Today
In today's fast-paced instrumented and integrated technological landscape, customers have an increasing amount of interaction points. The problem for organizations is that this increases dramatically the complexity and variety of data types they will need to blend with more traditional CRM and mainframe data to analyze.

The Value Of Big Data
The real value of Big Data comes when you are able to analyze all of these data types together – The insights and value you can yield will have an incredibly positive impact on your business. Based on the blended data and technology like Streams you can start to spot patterns realize who your high-value customers are  and what motivates them to buy more.

You can get a sense of their behavior patterns, and how and when it is best to try and reach them to improve customer sales and loyalty. Instead of leaving customer buying journey's to chance you can now design specific customer-centric  campaigns to improve your product conversion rates. This approach gives the customer: what they want, when they want it, how they want it, at a price they will pay.

The other benefit of this is to analyze why sales do not convert? You can identify points of failure in the acquisition path and act upon it to make your sales more successful. The big draw of big data for financial services is the ability to gather all of the data, blend it together, and analyze it all at once regardless of its source, type, size, or format.



What's The Catch?

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