Big Data represents a huge opportunity for Banks and Financial Services organizations. The ones who will manage to get the best insights out of the huge amount of structured and unstructured data they already have will be able to better serve their customers and comply to new regulations without putting too much hurdle on their employees.
But how to start? First step is to define the right Big data strategy and it all starts with identifying what do you want to achieve with Big Data. In this blog and in Part 2, we suggest what we think are the top 5 Use cases for Banks and Financial Services.
While fraud isn’t a new problem for banking and financial services companies, many are struggling to find solutions that can prevent and identify fraud, while maintaining a positive, customized, and seamless customer experience.
The key to accurate and non-disruptive fraud detection is to implement emerging technology that allows banks to gain a holistic view of customers. Moving forward, technology will continue to evolve and offer new strategies for optimizing fraud detection.
Use case #2: Compliance reporting
With a new provision of the Dodd Frank Act, financial services firms need to document all the information related to each swap trade, and within less than three days, give regulators access to it. To get to this point, they need to implement a system to monitor traders and collect all the required data.
Big Data can help them to comply to these regulatory requirements by:
- Tracking what goes into each swap deal
- Preventing accidental trades
- Identifying and stopping rogue traders
As these types of tools become common with the big firms, the smaller firms are expected to gradually adopt them at a lower cost.
Make sure to check out Part 2 of this blog to see what are the other Use Cases.
Check out the 5 Big Data Use Cases for Banking and Financial Services.
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