In the session ‘March of the machines: Getting better execution from automation, cloud and AI,’ Lisa Frazier, chief innovation officer, Wells Fargo, sets out that AI and machine learning are fundamental to the future of banking - just like they are in other industries.

She argues that it’s the catalyst for a new level of human creativity we haven’t seen before and organisations that embrace big data and AI at pace and at scale will outperform and differentiate themselves. “They will be the organisations that are able to systemically combine and exploit these innovations with a real purpose, solve complex problems, identify opportunities before others.”

“Perhaps most importantly these companies will be the companies that posses a newfound agility to adapt to customer needs and the ever-changing business landscape which is certainly playing out through 2020.”

Frazier points out that these aren’t just optional, nice-to-have features any longer. The reality is that these are fundamental given the sheer amount of data being produced every day: “The numbers are truly staggering. At Wells Fargo we sit on 200 petabytes of data, that’s essentially a million digital photos every day of your life.”

The ability to be able to manage and hopefully leverage this data through tech is essential, and is helping improve strategic application of not just fraud protection and prevention tools, but across a raft of business problems such as regulatory technology and climate change requirements.

Robot process automation (RPA), Jason Kingdon, chairman and CEO, Blue Prism believes, is another of these fundamental revolutionary technologies.

Currently, the RPA market is around $2 billion but is facing a $1.3 trillion opportunity. The two ways RPA is currently being approached, continues Kingdon, is the fairly straightforward automation tasks being carried out in a human-centric way, while the other approach describes the more dramatic opportunity of the creation of the ‘digital worker’.

The centrepiece of this movement can be described as ‘digital singularity’, that is, the ability for all systems to interoperate with all other systems whether they’re past present or future.

“The way this takes place is that either technology has a machine-readable format or it has a human readable format. The sophistication of the technology means that the human readable format can be repurposed as a machine-readable format. Everything becomes interoperable.”

While it’s still early days, Kingdon adds that Gartner estimates all organisations will have this technology by 2022, and while the implications of this kind of tech are still being learned what is clear is the ease of deployment and reduced cost these capabilities offer to financial institutions.

“It’s probably one of the least expensive enterprise technologies ever created. The cost of a digital worker is a few thousand dollars (depending on what it does), it can be downloaded for a free trial almost immediately.

“While firms have historically felt boxed in about decisions or choices made five years ago, digital workers are highly promiscuous and have the ability to swap technologies depending on the context in which they’re applied.”

Christin Brown, global financial services lead, Google, concludes that the way that data interacts with people and concepts involved (for example, within a global content management system), means that the future lies in taking these technologies and unlocking these immense data resources.

This means that when digital workers are deployed, they are able to be pumped full of data to enable them to learn, to improve algorithms, to become more accurate and become more effective. “We’re going to see another wave of not just digital transformation, but data transformation. It’s the beginning of the next frontier.”