RPA and AI in banking and finance: A five year predictionAdd bookmark
Artificial intelligence is now a key competitive advantage in banking, insurance and financial institutions
Photo by Freddie Collins on Unsplash
BBVA, the 2nd largest bank in Spain has proven to be an innovative bank quick to embrace new technologies. Their most recent project is a global deployment of a new platform for internal and external developers.
In this interview, Pedro Suja, head of artificial intelligence technologies BBVA & expert speaker at the RPA & Intelligent Automation Banking Financial Services & Insurance World Summit, shares his insights from the company's intelligent automation journey so far, and discusses how its playing a key role in their IT infrastructure.
How do you see the role of artificial intelligence (AI) evolving in the automation landscape?
All companies want to automate as much as possible. For many years we have been automating simple tasks, and now we are facing much more complex tasks automation. This is the new frontier. In the past we have used scripts and robotic process automation (RPA), and now the challenge is to automate human capabilities to keep on this track.
Why do you think it’s so important to go one step further into AI?
Using AI gives us three benefits. Firstly cutting costs: the more tasks can be automated; the better will be our position to reduce costs. The second benefit is to give a better user experience. Sometimes, we as humans have limitations: the time it takes to get information and to understand the problem. So we need help from AI. The third benefit is increased sales, because using technologies we can give the best and most tailored and relevant offer to our clients.
How is your BBVA planning to set themselves apart from the competition?
All the banks have a similar problem. We have a cost problem because we have huge legacy systems. We are very expensive, not only in terms of hardware maintenance or software licences, but also in integration costs. The amount of money we spend every year in integration costs, precisely in people working on integration issues, is incredible.
We need to create a new platform, with web scale features: scalable, elastic and in a paid per use base. We are all trying to get rid of legacy infrastructure and create a new scalable platform. We all have core banking, databases, infrastructure services, etc. What we are now doing is including a set of cognitive and artificial intelligence services, to be used by programmers in their new applications. Are we going to perform better than other players? I hope so.
Would you say 2017 is the breakthrough year for RPA and AI in banking and financial services?
We started this adventure in May 2015, so I wouldn’t call it the breakthrough year. For us, 2017 is the AI moment because we have three things. Firstly, cheap storage which allows us to house vast amounts of data, and now we can get information out of this data. Secondly, we have immense processing power at a very reasonable cost and third the availability of published machine learning algorithms.
Can you predict the role of RPA and AI in five years time in the banking and financial services sector?
The future of artificial intelligence will be everywhere.
It’s a way of automating everything, not only our relationship with clients, but also we can think in others tasks as for example data centre capacity planning or maintenance.
The second idea is that artificial intelligence and RPA can be used in two ways. On one hand, they can replace human beings when the task is very simple and can be automated – it could be the case of RPA, or very simple applications for artificial intelligence.
On the other hand, AI can be used to help human agents or executives. Imagine an expert system helping an executive in a branch. I see the future with automatons helping him with not only with simple servicing tasks, but also with more complex tasks such as commercials issues. In the future AI will help human beings.
What value-add is AI bringing your organization?
The added value is when there’s the ability to help humans taking difficult decisions, or decisions needing to process a lot of information. When we want to make very personalized offers to our clients, humans cannot process all relevant data.
The value is the ability to turn this big data we have in the banks into valuable information from our clients.
This is a real value because we can do things we couldn’t do in the past. We can divide our clients into different sets (clusters). We can investigate each set and give the best offer to each client. If we have tools like AI we can think of each client as a one person market, and we can think in millions of such Markets.
What’s the number-one tip that you would share with your peers?
Don’t wait. Go forth, make these techniques actionable. Companies are either waiting and seeing, or working on proof of concepts. But these technologies are ready. All the banks and big corporations have very complex processes, but in BBVA we are simplifying and automating them. And we are getting results because we are not waiting, we are running and we are delivering.