In my last two posts, I’ve defined what composable banking is and its potential scope.
In both these posts, I’ve highlighted BIAN as a way of defining the composable modules. One thing I’d like to add though is that BIAN represents the business model of banking first and then how it can be supported by technology. It’s not about the modularisation of software components that can be easily interchanged, it is very much about creating flexibility and agility in banking by creating a canonical representation of the business of banking.
The biggest challenge for any bank is how do they reach such a vision of composable banking when over decades of investment in technology automation they have hundreds or thousands of systems, with some sharing data through extraction, some integrated through technical bridges and maybe a few more modern solutions through APIs? Integration is one of the biggest headaches a bank has, so the idea of composable banking would be simpler if every system had APIs, but that just isn’t the real world.
In addition to this, not every process is based around system-to-system interaction. There are processes that require human intervention, often managed by business process automation software. Sometimes these processes are necessary because systems integration may not be possible without them: the swivel chair problem of keying data from one system into another (robotic process automation, or RPA, is especially handy here).
In the last few years, artificial intelligence (AI) has been added to the mix to make the routing of flows smarter. As always, technologists are great at solving individual processes, but business tends to be more complex, and it is only much later we start to see a bigger picture. For example, what if a process involves system-to-system integration, workflow systems and robotic process automation? On top of this, what if you need to measure, monitor and manage these processes so they can be further optimised?
In one of the banks where I was responsible for IT architecture and strategy, I found six different workflow systems being used. And this wasn’t across the entire bank, it was just one business area. This was the classic spaghetti architecture issue driven mostly by silo implementations for individual business requirements or processes. I’m sure most of you recognise the issues above, but it seems there is now an emerging solution for this problem.
This is something research and advisory firm Forrester highlights as a new space called ‘deep process automation’. In simple terms, it is a layer that sits above IT systems, workflow systems and RPA solutions and combines orchestration and execution of the whole complex process. Applied to multiple complex processes, this layer can act as an enterprise operating system. There are solutions like Luther Systems that already claim to be able to handle the most complex scenarios banks have to deal with.
The key thing here is that often we hear that digital transformation is hard, slow and expensive. Quite often I find banks still looking at transformation from an individual process-by-process approach within specific business areas. A siloed approach within a big programme. Instead, it is key to take a step back and look at the overall picture today (current landscape), define the desired state (future landscape) and then work out how to get there and with what technologies.
This is definitely harder than it sounds, but it is achievable. It requires a strong combination of business and technology vision and leadership, but it is business led. However, if a bank’s vision is simply to digitise what they have, i.e., automate how they sell and service products they have today, then this is probably something they can get away with without creating a composable bank.
Right now, there are many new technologies available with more on the horizon and regulators are pushing for change to create more competitive services. There is arguably more innovation happening now than at any other time in banking history.
Therefore, I’m just saying that time spent creating flexibility in banking is not just time well spent, but critical. Flexibility, agility and innovation are core competencies that will keep banks competitive through the next decade. By 2030, the banking landscape will be a very different scene. The winners and losers will be defined by how well they have architected their technology led by a strong business vision.
About the author
Dharmesh Mistry has been in banking for 30 years and has been at the forefront of banking technology and innovation. From the very first internet and mobile banking apps to artificial intelligence (AI) and virtual reality (VR).
He has been on both sides of the fence and he’s not afraid to share his opinions.
He is CEO of AskHomey, which focuses on the experience for households, and an investor and mentor in proptech and fintech.
Follow Dharmesh on Twitter @dharmeshmistry and LinkedIn.
Read all his “I’m just saying” musings here.
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