We are probably still more than a few decades away from seeing an end to bricks-and-mortar branches, but the tide is certainly turning in that direction. We have both the general trend towards convenience-led habits among customers and the technology to serve that need in the fintech world. Currently, the biggest limiting factor is the strategy You do not have to think that far back into the past to recall a time when the majority of our worlds were analogue. Smartphones only started becoming noticeably widespread around 2010. Before that, iPods and other mp3 players were still considered cutting edge. Most millennials can still remember buying their music on CDs - when was the last time you even saw one?
The point here is that household technology has come a long way very quickly, and our habits have evolved in line with that development. When you wake up in the morning, you are now more likely to get weather and traffic updates from a digital voice assistant than the morning radio show, you’re more likely to listen to a curated playlist on Spotify or a podcast or two than read a newspaper on the way to work, and you’re vastly more likely to deal with your banking via an app or website that waste your lunch hour going into a bricks-and-mortar branch.
It has reached the point now that customers expect simple digital solutions, often specifically personalised to their individual needs, rather than labour-intensive, one-size-fits-all analogue solutions. If there’s not an app for it, people don’t want to know. And yet there are still some business practices that missed the memo (probably because they were still relying on memos).
Banking, in particular, has a lot of room for further development. To be fair, their apps are constantly improving and even some of Thailand’s top banks have apps that enable access to simple and secure services for day-to-day needs. But there is still room for a lot of improvement.
McKinsey & Company Financial Services suggest that banks need to adopt an “AI-first” approach to remain relevant, putting all their eggs in the basket labelled ‘artificial intelligence’. It’s hard to disagree, especially as challenger banks around the world that have been adapting to technological evolutions continue to carve their growing market share out of dissatisfied customers leaving the well-established old guard. We’ve discussed how AI is already helping to improve and accelerate fraud detection, but what other advances could be a determining factor in the future of banking?
Speed is key in tech developments - especially fintech. While it’s not accurate to say that the first player in a particular space will always dominate it, they do get a significant advantage and often brand the space in their own name. Of course, innovation within an established space can radically shift things, but it’s a much harder route to take.
Ok, that was a lot of buzzwords - what does that actually mean for banking?
Put simply, programming takes time. Coding a secure, stable, simple and efficient banking app, even with an army of coders on staff, isn’t something you can knock out in a weekend. And it only takes a single innovation from a competitor to completely undermine you, effectively wasting a significant amount of time and money.
However, platforms that allow you to build sophisticated systems with little or no coding allow easier experimentation and rapid deployment and scaling. This means that the big banks can minimise the disruption caused by fintech firms by simply matching their services within a comparatively short time. Being drag-and-drop in nature, the availability of low/no-code tools also means that banks no longer require a huge staff of highly skilled coders as impressively complex systems can be built by those with surprisingly little training.
Unsurprisingly, this is an area that banks are keen to capitalise on, so a lot of money is expected to be sunk into perfecting such systems. According to MarketsAndMarkets.com, it could be as much as $45.5 billion by 2025.
The digital age is an age driven on data. The whole convenience aspect of our habits these days is driven by systems being able to predict our needs and preferences based on past experience. It’s like a friend remembering how you like your coffee, only vastly more comprehensive and accurate.
The same technology can be used for far more than curating your Spotify and YouTube feeds, though. With the right sources of data, it can be used to identify inefficiencies in workflows, minimising delays for consumers. In the analogue era, that could only be achieved with a performance review every six months - a time-consuming and unreliable process. With process intelligence, obstacles can be highlighted in real time.
Again, data is the key for this. Volume and diversity are particularly important - lots of data from lots of different sources. When properly analysed, patterns quickly become apparent and insights can naturally be drawn from those patterns. Act on those insights and you improve the customer experience, which means you keep that customer. It can also be used to improve overall efficiency, meaning you can be both cutting costs and increasing income at the same time.
Content intelligence is the technology that helps a bank to process documents accurately and quickly. Previously, communications from customers would have to be read and manually entered into the bank’s digital systems, which inevitably created the risk of human error. A simple typo - something as simple as a misplaced decimal - could ruin either the bank or the customer’s life, so removing that risk is an extremely important step.
Fortunately, the technology that allows computers to “read” written documents has developed to a very impressive point. If you live in Thailand (and especially if you can’t read Thai), you’ve probably used it yourself in the form of Google Translate’s camera mode, which can take even stylised text and turn it into readable text in a language you can understand. One important point you will have noticed about this process is how fast it is - effectively instantaneous. That translates into customers getting their problems solved, loans approved and business dealt with in a fraction of the time it used to take.
As you can see from the systems we’ve highlighted here, there are a lot of different elements that go into improving the customer experience. Each works in a distinct but important way to contribute towards the same end goal, meaning that they cannot work independently of each other. For example content intelligence systems may help the computer to read a document, but machine learning (ML), natural language processing (NLP) will help the computer to understand what it says and an AI will be needed to determine the appropriate output.
Once again, the key to this development is the removal of manual steps. Each takes valuable time and introduces more risk of error, so any technology that can automate such steps will pay for itself in satisfied customers. What’s more, it removes dull, repetitive and comparatively menial tasks from the workload of employees, allowing them to focus on those tasks with a far greater value to both the bank and the customer, such as service, protection and risk mitigation.
banks adopt to apply that technology. Those that get it right will likely triumph while those that get it wrong will go the way of their branches; the same place that CDs have gone - obsolescence.