Is hyperautomation in banking truly achievable?

For the second year in a row, hyperautomation has been listed as one of Gartner’s strategic technology trends for the next 12 months. Defined as “the combination of multiple machine learning, packaged software and automation tools to deliver work”, hyperautomation creates a backbone of automation tools that work together to transform business processes, delivering reliable, scalable outcomes.

Not only has the technology been heralded as a sure-fire way to minimise cost and risk while maximising revenue, the added benefit of hyperautomation is that people are involved in the process. Not only does it augment workers to improve productivity, but it also enables employees to get involved with training other automation tools to quickly meet business goals. 

The benefits of hyperautomation

There are huge benefits to be gained by deploying hyperautomation in the banking industry. From monitoring transactions for fraudulent activity and improving compliance management, to automating manual tasks in call centres so employees can work on customer queries where their soft skills are more valuable, the list goes on. But how close is the financial services sector to achieving true hyperautomation, and is the technology a realistic prospect for banks?

Two unknowns are proving problematic in the race to realise hyperautomation:

• How much automation banking customers are actually comfortable with
• Whether banks are opening themselves up to greater compliance risk as hyperautomation increases

In terms of customer service, hyperautomation will never be achievable on its own. To implement the technology to generate a customer-friendly outcome, it must be combined with hyper-personalisation. Only then will banks be able to strike the right balance between the elements of the customer journey that should be automated and those that should not.

What are the risks?

Before banks embarks on a hyperautomation project, they must consider the potential compliance risk. As with any type of AI, there is a chance an unexpected error could occur or that bias could unknowingly creep into the model, which could result, for example, in the wrong lending decision being made. If there are layers upon layers of automation all interwoven through hyperautomation, it will be incredibly difficult to pinpoint any issue, unless the AI in use is as transparent as possible and tracking and audit checks are easy to complete.

As more financial institutions dip their toes into the hyperautomation water, there must be more regulatory scrutiny over this technology. Of course, the downside of that that is there will be additional hoops for banks to jump through. However, because of the ongoing pandemic and increase in economically vulnerable customers, it is vital banks demonstrate to the regulator what additional processes and training are in place for hyperautomation to be used safely and responsibly.

Don’t run before you can walk

Although hyperautomation offers a lot of promise, banks should not get ahead of themselves and automate for the sake of automation. There needs to be careful consideration about where best to divert investment in this technology where budgets need to be prioritised.  

That is not to say banks should steer clear of automation altogether. Initially, financial organisations need to think at a more granular level to work out which type of AI and automation is most appropriate for a specific task, whether that be intelligent automation, RPA, or an intelligent business process management tool. In the immediate term, intelligent automation is the more appropriate solution for implementing more customer-centric sales practices and streamlining processes to boost customer service and organisational efficiencies. Only once that initial groundwork has been done can hyperautomation serve as a toolkit of powerful intelligent automation capabilities for banks.