Few industries in the UK have been as quick as the financial services sector to embrace AI, machine learning, Robotic Process Automation (RPA) and data analytics. Highlighting progress in machine learning alone, a recent Bank of England report found that two-thirds of UK financial services firms are already using it within their organisation.
While established banks have been quick to embrace these emerging technologies, they are often held back from going all-in by their size, IT systems and processes. Consequently, it is the disruptive, challenger brands that are currently setting the pace for innovation.
And it is quite a pace they set – consider Monzo, for example. Many banks have introduced chatbots as a means to communicate with their customers, but Monzo has used AI to take this a step further. Through using machine learning, Monzo implemented a system that makes recommendations to customer service agents on how they should respond to different customer queries. This naturally leads to a speeding up of the resolution process and enhances the customer experience. Not only do customers get the answers they need quickly, but they also avoid listening to automated responses that might not specifically address their questions.
In business lending, Iwoca is putting AI and data analytics to good use. The small business lender has deployed AI to allow customers to access financing in seconds. In getting this to market, Iwoca, like Monzo, benefits from its newer, nimbler IT infrastructure to develop and launch new services.
These are just two examples of challenger banks deploying machine learning and data analytics. As smaller organisations with newer IT infrastructure, it’s easier for challengers to move nimbly.
The challenge for established banks, therefore, is how to respond. One option is to set up their own fintech disruptor, as RBS has done with Bo. Launched a few weeks ago, Bo is an app-only bank targeting younger, tech-savvy consumers. While only time will tell how successful it will be, we are now entering an exciting second phase of fintech disruption.
Even so, established banks still need to decide what to do with their existing operations On this question, conventional wisdom offers three main options. One is to put up with the limitations of existing systems and soldier bravely on. A second is to tinker around the edges to fix part of the problem, perhaps by investing in some software that will improve one aspect. The third option is to bet the farm on a huge new platform.
The problem with the first is that customer expectations and competitors continue evolving while the bank’s operations and capabilities don’t. This isn’t really a long term solution. The second will at best deliver moderate benefits, as the root causes are deeper and more structural than any point software solution can fix. The third takes years and years, will cost tens if not hundreds of millions and creates a vast amount of risk.
There’s a fourth option, and it involves the following components:
Those are the strengths of the business process management (BPM) sector, and here is an example of this approach in practice for an asset finance company: read the case study.
The future belongs to financial service companies that embrace RPA, machine learning and AI, and apply all these to improve customer experience. So far, disruptive challenger banks have been quicker out of the blocks. I expect established banks to fight back, and their scale and brand awareness will make them a force to be reckoned with.
Written by Siddharth Parashar, Chief Revenue Officer, Customer Management at Firstsource.