Another interesting article: here. UBank in Australia has put some billion transactions records into public domain, allowing customers to run comparatives on spending patterns etc. (H/T to @moneyscience ).
"Users may input their gender, age range, income range, living situation, post code and whether they rent or own their home. The site uses that data to serve up average spending habits of people in that demographic, including detailed information on restaurants, housing costs and travel destinations. Users may also choose to input more detailed data to perform a “financial health check”, comparing their monthly shopping, utilities, housing and communication costs with “people like you” and the average Australian."
The idea is to make Big Data work for both clients and the bank - reducing the overall costs of risk pricing and in the long run helping the customers to lower their risk profiles and cash flow management. This has to be good for the bank and for its clients.
Next step would be for the bank to capture actual interactions within the database and correlate these to changes in spending patterns of customers (within the sample of those who engage with the system and outside the sample) to see what changes are generated.
This type of 'actioning' big data has been discussed at a recent round table on disruptive innovation in finance that I chaired in Dublin (here).