What are the main steps to becoming a lean, agile, collaborative bank?
The first and most important step is getting a common understanding what “Agility” really means. It is very commonly misunderstood as a methodology only, and then everyone follows the famous “Spotify model” – which did work well for the company at certain period of their evolution, but is definitely not a blueprint everyone shall follow (btw, even Spotify doesn’t use it anymore). Agility is an important enterprise capability: to learn fast from own mistakes, and to use these learnings to quickly change and adapt certain elements of, or even the whole business model – not just deliver a code in sprints. Therefore, Agility is not a methodology or a way of working (and certainly not one methodology, like Scrum). It’s a combination of skills and attitudes of all employees (sometimes referred to as mindset), and basic principles everyone should follow. So, it’s corporate culture and capability. This first step requires a lot of learning from everyone in the organisation, deep retrospectives and, above all, top-down commitment and support from the management. Based on these learnings and introspective, company needs to define own goals and steps it will follow to achieve them. There is no blueprint of an “agile organisation”, nor is the agility a destination – and therefore there are no prescribed steps to reach it.
How can cloud technologies and AI help banks deal with changes posed by the Back Office transformational process?
Once I heard a great definition of “a computer”, which says that computers are machines that help us solve problems we wouldn’t have without them. The same is with all new technologies – they offer (just) additional possibilities, but whether these possibilities will offer more help than headache – can be debated. For example, I saw attempts to implement AI for helping colleagues in Back Office to read and extract data from lending contracts and inserting these data into booking systems – which looks as a very advanced, modern solution (and it is). But, I’m wondering why would you use advanced and complex AI to extract data from a contract – when that same data you probably already have in the previous step in the sales process – structured and ready for further processing. In other words, before thinking how advanced technology could replace a person doing a step in a process, we should look wider and consider improving the entire process or even the entire business model. In the spirit of business Agility, we should not look how technology could help improving an existing business function, like Back Office, but start thinking how could we do banking differently. Since 2010 I am speaking on conferences that focus on different, isolated aspects of banking business (like Back Office) and I’m wondering whether we should stop focusing on separate aspects of Banking and start talking about improving Banking in general. And that’s where both AI and cloud could help more than just in Back Office. Cloud opens possibility to horizontally slice the entire value chain of banking operations, from front to back, and consider whether some of these layers are really necessary for a banks’ competitive advantage or not. And based on that, reconsider the entire business model and either: a) further utilize some of these layers (maybe even turn them from cost, into profit centers by scaling), or b) outsource those that are pure commodity. And, in those layers which a bank decides to further utilize, AI can help getting the most out of data processed in/through that layer.
How do new regulations influence the back office to transform?
I believe that the biggest regulatory push already happened with GDPR and related data and privacy protection regulations. Back Office is a funnel through which practically all client data passes through. And as long as some of these data are manually processed (and everything that is in documents is manually processed – no matter if a document is “digital” like pdf) is under threat to be leaked. So, these regulations will, and should, motivate transformation of internal processes to truly digitalize and automate them, to avoid a need for any manual processing.