Open Banking and Analytics Intelligence

Open banking is catching the imagination of consultants, analysts, commentators and general public. One reads about the benefits from data sharing with third parties, concerns over data privacy and on the technology front-information and electronic security. I thought it best to ask a friend of mine in London, what her views are on open banking and will she sign up willingly.
What truly interests her is that she will have processed information that will help her take learned decisions. Right now she only has her transaction information and some elementary product and pricing knowledge; the relationship manager at her Bank sells her products for which he gets higher sales commission. That is not a big help. In her own interest she did try once to prepare a comparison chart of products and pricing across banks, it was so complicated, she gave it up mid-way. She knows for sure that she can get better deals. However she did not have the required information. Her expectation is that the Third Party Provider (TPP) will have the capability to analyse per her requirement. Going a step ahead the TPP must give her a simple, meaningful information on a user friendly front end. She gave me two examples as illustrations. The first, it must tell her if she is getting the best returns on her investments and cheapest price on her overdrafts. The second, she should be in a position to define her goals, short and long term, the resultant outcome must be suggested spending and saving pattern over the period.
The onus now is on the TPP to meet the requirements of a typical customer who consents sharing of account information. A look at the data assets that a TPP will have must help in understanding if such expectations can be met. In simple terms there are three different data sets, Firstly the most essential, transaction data from a customer. This is genuine and accurate. The second, financial products and services and finally pricing information. This in itself is a strong base for analytics. The customer user will have to add related personal information and select an appropriate demographic profile, set goals. A predictive ‘what if’ scenarios contingent on the data assets and customer information completes the requirement. All these mirror a PFM tool.
If this is the expectation from an open banking customer, a TPP must have a robust analytics solution, with sophisticated algorithms and price it as a service. In short analytics-as-a-service.