Well - with a title like that I am dating myself. But perhaps if you are humming 'Big In Japan' by Alphaville in your head, I am in good company! But I digress...

I recently returned from a business trip to China and Japan where I had the privilege of meeting several major banks to discuss Big Data and business insights in financial services. I was keen to understand the key business opportunities they believed that investments in big data would support, and also the challenges they faced with implementation.

The key areas of focus resonated well with the business priorities I hear in the US and Europe:

  • Customer and Product Analytics - to understand sentiments and usage to build a stronger lifetime view of a customer.
  • Risk Analytics - to move toward real-time risk analysis and become more interpretive of risk rather than reactive to past events.
  • Financial Performance - to predict impact on the business through a better analysis of costs/revenues and building simulations for the impact of cost cuts.

These core scenarios were equally pervasive in China and Japan, although I did notice an interesting cultural difference. The banks in China were much more open to discussing ideas and concepts with their peers (competitors) than the Japanese banks. Those in Japan viewed the promise of big data as something to be fiercely protected and a means to gain competitive advantage. Although the analysis and insights gained can and should lead to competitive advantage, banks also share some common challenges. The impact of big data - whether the massive amounts of structured data in systems, the explosive growth in new forms of unstructured data, or harnessing data streams from the cloud and social feeds is a huge challenge. What I saw in China was a mutual agreement of the areas that big data would provide value. Breaking that down a little further, where they shared information was in how to move beyond the 'what' and understand the 'how' to solve the problem. It is hard to overstate the volume of data in question in China - even by US banking standards. With a population of 1.35 billion, and a middle class as large as the entire population of the US, China has a massive banking population. One bank I talked to is based in southern China and is considered a tier 2 bank, yet has 50 million credit card customers.

With such large volumes it is almost impossible to start a big data project from the data upwards. One of the new practices I am seeing emerge is to start thinking about the questions banks want to answer, and then look at the data required to answer or interpret those questions. As an example, banks in all countries can learn from the approach taken by RBS Group in the UK. By working with Microsoft's Analytics Platform System the bank is mapping business customers' transactions across the globe to build a correlative view on GDP trends; and therefore a more qualitative view of risk which can be leveraged in multiple ways.

Whether dealing with big data in Japan or any other country, banks that start to ask innovative questions of data will be first to gain the benefits of a data and analytics program.