Cognitive computing: The future is now

tall building in city

AI and cognitive computing will become a core part of how financial service organisations operate.

Everything from customer experience through to sales generation.

Let’s examine what’s fuelling this technical revolution. And explore how can you take advantage for your own business.

It starts at the cognitive level

You’ve seen AI in the movies – often trying to destroy its creators, the human race. You may have heard of Google’s Alpha-Go, which recently defeated the world’s best human player of the notoriously difficult game. Perhaps you have regular conversations with Siri or Alexa.

Within the financial services industry, things are similarly disruptive – and game-changing. According to Gartner:

“The industry that is the most excited about AI implementation is the financial services sector. CDOs in this industry are dealing with a very large amount of data in the form of financial transactions that must be analysed for fraud, or customer behaviours that provide insight into what type of financial advice would be most beneficial.”

UBS, a Digital Reasoning client, is reportedly using AI for optimising trading strategies. Machine learning is used to scan vast volumes of data, and identify patterns and predict volatility. What’s more, tasks that would normally take 45 minutes now take just two minutes.

Understanding the total data landscape

Of course, none of this is possible without data. Over the past few years there’s been a massive expansion in data types (3.3 Zettabytes per month by 2021).

We’ve seen growth in real-time data, big data and even alternative data. All are providing us with revolutionary information, but at such velocity, volume and variety that we need something as powerful as machine learning to make sense of it all.

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Global IP traffic will increase nearly threefold over the next 5 years (source: Cisco)

Send for the machines

While machine learning enables understanding of markets, this needs to be transform those view into insights. That’s where natural language processing (NLP) comes in.

Human speech and the hierarchical structure of language present a challenge for computer science, but when NLP is powered with machine learning it unlocks the technology’s full potential. Along with other AI capabilities such as computer vision and pattern recognition, it provides context.

Empowering users to be smarter

When these capabilities combine, the result is cognitive computing. But how can this empower users to be smarter and make use of the vast amount of information that comes into banks and financial service institutions?

Kim Prado, Managing Director, Head of Client, Banking and Digital for Royal Bank of Canada (RBC) describes the process she used to gain understanding and get go ahead with this type of technology.

“We needed to empower our users to be smarter. There was too much information coming into the bank and you can’t possibly look at all of it.” Said Prado, describing the key drivers behind the implementation of the technology at RBC.

“The first step is to lay the plumbing. Collect all the information in a standard way and apply a standard identifier to it so in the end you can tie it together.”

Secondly, Prado and her team realised that they were throwing a lot of valuable information on the ground.

“For example, Bloomberg chats, when you’re chatting so much business gets done through different types of chat systems and client interactions are happening all day long.”

RBC realised that they needed to gather information from their unstructured data and turn it into structured data, finding a smart way to display this information back to the end user.

unstructured data
Unstructured data is one of the biggest challenges to companies’ digital transformation strategies

“Your end user is not going to tell you what the spec is to deliver this piece of software to them. So you need to figure out with your data scientist how to actually relate the information in a way that will then in turn tell your end user what their next move is.”

The big data challenge

Making sense of communications and voice data offer great potential for the financial services industry. The challenge is to take existing legacy systems, mass data, unstructured data – all commonly found within many banks, insurers and other well-established companies.

“Everybody should take a minute and think this through because you have all this information already in your compliance databases. Why not leverage it for your end user?” says Prado.

“Why not bring it into their daily workflow and use it to help them make decisions and by the way you kill two birds with one stone. You kill a regulation compliance issue and you now make your end user smarter”

A necessary change

Cognitive computing isn’t limited to improving customer insight and experience. The technology can also be applied to areas such as surveillance and tackling financial crime.

According to a recent survey 36% of banks and 31% of insurance companies have already adopted artificial intelligence, a move that Prado sees as a necessity over an advantage.

“I think it is definitely giving us a competitive edge now” Prado said of RBC’s adoption of cognitive computing “but it is a necessity to move forward. If you don’t start adopting these technologies you will fall behind. It needs to have already happened, I would catch up.”