Big Data in retail banking – the opportunities and challenges
There’s a lot of buzz about big data in the retail banking sector right now as all the major banks work out how best to bring new unstructured data sets (such as social data and mobile data) together with transactional data in order to improve customer experience, become more competitive and drive growth.
I recently discovered this great debate from September 2012 that provides a clear understanding of where banks are today in their use of big data. The video includes panelists from HSBC, Barclays and RBS; the full debate lasts for more than an hour.
For those of you without the time to spare to watch it all, here is my summary of the main points:
1. What are the pain points that banks are grappling with?
- Customer retention, cross-selling, up-selling, developing new products that customers actually want, and minimising fraud
2. Where are the biggest opportunities with Big Data?
- Improving insight and understanding of the customer in order to deliver a better customer experience through highly personalised communications (‘the segment of one’)
- Using social media analytics to find out what your customers think of your competitors and their products
- Identifying and reducing fraud. Part of this is showing fraudsters that you are looking for them. Most banks are doing real-time detection already and this is where Big Data, combined with social data, can come into its own
3. What are the challenges with Big Data?
- Gaining permission to use and process some of the new data sets such as mobile and social media data. The panel all admit that financial services is behind the curve in this because of compliance issues, and that a lot could be learned from some of the new technologies and techniques that companies like Google, Facebook and Amazon have developed
- The ultimate goal of Big Data should be about delivering a better customer experience for customers. Not easy when the user journey is now dynamic when it used to be confined to in-branch interactions
- Finding the right balance between giving the right access to data across the company, and making sure adequate controls are in place. This is because the further away from source it gets, the harder it is to ensure compliance is maintained
4. Where should retail banks start in Big Data?
- Think about who owns the customer and therefore the data relating to the customer. This will require a rethink in organisational and governance structures, and a real need to get the C-Suite bought in
- Focus on your strategy in order to frame the right questions and therefore data that you need. There are infinite possibilities with Big Data. That said, the business and the data analysts need to work collaboratively. Once you start to visualise data, it can raise new questions or reveal that the original question wasn’t right in the first place
- The Holy Grail is to get the single view of the customer first, and then enrich this later with newer data sets such as social data. Take things step-by-step – unlike Facebook, banks cannot afford to get their communications to customers wrong! They are already governed by a set of regulations to use data responsibly
- The emphasis should be on quality and not necessarily speed of communications. The next best action for the customer may not be a cross-sell – that won’t drive loyalty or build trust
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