Fintech Finance

Our CEO, Diana Paredes, was featured in the the Fintech Finance Magazine Issue 10

Don't be a data dummy

AI isn’t the threat. Doing nothing about it is, says Diana Paredes, CEO and Co-founder of Suade Labs.

FINTECH FINANCE: The financial industry has talked about artificial intelligence (AI) for years. In your opinion, when will it start to fully realise the benefits?

DIANA PAREDES: Banks have always had a lot of data but if it’s not normalised a machine can’t do anything with it. You cannot go the extra mile in the way Facebook and Amazon do. At Suade Labs, we’ve been working with clients to organise their data and we’ve been involved in conversations around good practices, so the first steps are now being taken. However, companies that are a potential threat to financial firms, the likes of Amazon and Google, have a much better understanding of what they should be doing with data and have given a very clear roadmap. The reason Facebook can do what it does is because its data is more structured than that of any financial institution. I think firms have woken up and are understand the things that are possible, but we’re not doing it properly in financial services yet. The likes of Facebook put us to shame. How awesome would it be, from a financial services perspective, if you could know, based on an individual’s transactions, what they are doing – for example, if they’re renovating their house? Regulation, such as the General Data Protection Regulation (GDPR), has helped because it has forced institutions to improve the accessibility of their data. And, because money is being spent on meeting rules on data, companies have realised they should do much more with it.

FF: What do you predict the conversations around AI will be at Sibos this year?

DP: I’m hoping there will be a call for action to really start discussing the issue. It’scommon practice for financial firms to hire a third party to do their strategic thinking, but I think it’s shameful for a bank to outsource core discussions around how the business should be run. I’m hoping people will realise that it’s not a question of ‘if’ for machine learning, it’s ‘when’, and firms need to decide how they prepare. Other industries are embracing AI and working hard to get there. Google is revamping whole departments around AI and machine learning engineers. What are we doing in financial services compared to that?

FF: Should banks build AI capability in-house, or collaborate on shared projects?

DP: It has to be the right kind of collaboration, not just any collaboration. Sadly, collaborations in the financial industry can be inefficient. Staff can be reluctant to get involved with projects because they can be seen as low priority, and things are very meeting-orientated with lots of talking but not much getting done. Compare that to tech departments where things are run as opensource projects done over GitHub, sharing work without much human interaction. It’s a lot more efficient.

FF: What part do you see AI playing in compliance in the future? How can it help?

DP: There are so many things, but a quick win would be the ability to identify outliers quicker. The next stage is thinking about how robots can do work more efficiently. It’s not about machines replacing humans, it’s that machines can enable humans to have a far more pleasant job. Anyone who worked on a trading floor 30 years ago, writing tickets and sending them through a fax, would that agree modern practices are better. Staff should not feel threatened by the evolution of technology, they should educate themselves and be the person who learns how to take decisions on the back of AI and machine learning.

FF: So, how do we get away from fears about AI taking away jobs and seizing control of decisionmaking?

DP: Well, if you don’t educate yourself, AI could become something that is handled by ‘geniuses’, and it’s beyond your understanding. The best way is to empower people is to teach them about it, demystify it. Because innovation isn’t something you can stop, it’s human nature. We need a much larger population than we have now that is educated in machine learning, it should even be taught at school. What you don’t want is innovation overtaking the way people live and they have no idea how it happened.

For the full magazine, click here.