What is the “data-enabled client” in Banking?
The banks need to pay much more attention to the ability of the clients to be much more self-directed. This is where we get into the discussions of the data-enabled client.
Have you read my last blog post, where I bring up the discussion I had with my neighbour during the height of the COVID-19 pandemic? He, like many others during that time was struggling with the uncertainty that he was facing, and trying to get a clear picture on his financial stability. If not, then you can find it here.
So in my last blog, I made the case for required change in the banking industry. But I have also sparked off a lot of questions from you readers asking – but what is the data-enabled client? So I thought I would do a short post here just before closing-down for a relaxing summer vacation with the family.
So, where to start?
You see, banks today are facing a fundamental transformation of their revenue-generating mechanisms, or in other words – the way they make money. The traditional linear models based on distribution channels of products are facing a severe margin compression, accelerated by the new normal imposed by the central banks (zero to negative rates) and the regulators (transparency on costs and incentives) which has been accelerating in a post-covid world. Extreme digitisation is required by the banks to realign existing costs, but this drives the risk of worsening the cost/income imbalances because digital can force a further squeeze of margins due to the clients inability to understand higher value propositions from the bank outside of a human relationship.
A key fact is that banking revenues generate two type of margins, there are interest rate margins which come from things like deposits, loans and mortgages. Then you have intermediation margins, from things like investment and insurance contracts. The later is the main focus for the banks in general, and are harvested predominantly today by using offer-driven approaches, so in other words the products are pushed towards the customer, instead of a more demand-oriented approach where the products are being pulled by self-directed clients in the way we are used to in a digital world via the internet. Due to the focused shift to digital as the main channel, banks are facing a need to adopt new business models which are forcing them to relax their current product-centricity and embraces a more client-centric focus, and looking at digital as the main relationship channel going forwards for them. Now, this obviously requires the banks to pay much more attention to the ability of the clients to be much more self-directed. This is where we get into the discussions of the data-enabled client.
So, the “Data-Enabled Client” in Banking is an individual who has been enabled to take advantage of and engage with the bank using digital solutions, and as such have been motivated via available and relevant data supplied predominantly by the bank to be self-directed in making well informed decisions in regards to their financial life and actions. But there is also a need for the bank to ensure that the client is making these decisions and actions founded on full transparency in regards to the value and implications of any actions that they are taking. To do this, the banks will need to support a frictionless Online to Offline mechanism, so basically removing the notion of channels. But it then becomes critical for the bank to deliver relevant and contextual information on-demand, using a mix of human and AI capabilities.
This is even more important given a new trend towards Online Merges Offline (eg, Amazon closing the experience circle with owned stores). The transformation required for a bank to reach this new level of client focused engagement will require a fundamental recalibration of their business models and transformation of their operating models along with a new technical and data architecture.
To be successful, the banks will seek to built capabilities to support this transformation on a number of modern architectural principles and technologies such as cloud native, AI technologies and taking advantage of hybrid multi-cloud infrastructures such as IBM’s Open Hybrid Cloud platform and our new Financial Services Ready Public Cloud offering.