By Mark Bakker, Regional Lead Benelux, H2O.ai, an AI technology software company.
Artificial Intelligence is now where Business Intelligence was 10 years ago, says machine learning proponent Mark Bakker. The smart move is to take it to the next stage like you did with BI, and make it truly operational.
COVID put unexpected, protracted strain on many enterprises. But while it may be too early to say this, the positive impact of this first 1.5 years of COVID is how organisations, especially in banking and financial services, were forced to look into digital technology to identify first, ways to cut costs and survive, but increasingly how to help customers more (and more intuitively) online.
When I say ‘technology’ there, in one way, I mean everything from Zoom to cloud to chatbots. But really, my focus is on Artificial Intelligence (AI) and its most practical contemporary manifestation, industrial-strength machine learning. And from that perspective—and it pains me a little to say—from what I see AI still has some challenges being taken seriously enough in some parts of European financial services: despite amazing advances in the field in the last couple of years, and some progressive organisations embracing AI—advances that make it a truly mainstream, trusted enterprise option—I do wonder how many companies have dabbled in it just because it’s fashionable, or see it as a ‘shiny new thing’ to kind of play with a little bit.
A compelling, growing list of AI use cases
That’s really not a defensible position any more. It’s a little bit of an old example now, but we used to talk in tech about how only some great ideas ‘cross the chasm’ and escape the lab or bleeding-edge use cases to being accepted/embraced by the majority of the market. And it is my contention that AI is at that very point: that it’s made that jump, and so needs to be fairly and properly looked at by financial services CIOs.
After all, huge short-term potential exists for AI in financial services on the following fronts:
- Open Banking in more and more ‘cashless’ Europe: In 2021 we will see consumers increasingly providing their consent for specific, prescribed and constrained uses of their transaction data across multiple suppliers. That means a lot of data, and a lot of rapidly-changing data, that you will need to be able to cope with as more and more gets spent online: think on-time billing, better fraud detection, real time interaction with customers, and creating interesting, time-sensitive personalised offers.
- Fraud and Anti-Money Laundering (AML): AI is already being used here, but we know from our conversations that usage is about to explode. That’s because the bad guys are only getting more sophisticated here, and our traditional ways of dealing with their schemes are being exposed more and more as plodding and unimaginative.
- Accurate behavioural modelling: We are starting to use AI to use data to derive truly dynamic pricing to understand your customers better so you can help them better (and also help yourself)
- The rise of ‘insuretech’? We have biotech, and we have fintech. Soon, we’ll have ‘insuretech’: financial products in life and motor insurance fully informed by extensive data capture about my real health and my real driving, pumped into fair-minded AI systems that will be able to offer fully-customised, fully-appropriate insurance to the individual out of masses of IoT (Internet of Things) data.
AI can do all this, but it can (and is) also helping your internal workflow and customer service. Ultimately, what AI is there for is to automate processes that were manual before. If you automate, then you can do tasks faster; you can cut costs and you can help customers easier, more intuitively. Indeed, if you implement correctly, you will make less mistake. This does not at all mean you’re just going to replace all your bank tellers with bots; it’s actually going to be much more cooperative than that, much more of a human-software synergy. You want to get to a situation with AI where the customer can ask whatever she wants to ask and she will be helped by a reassuring human, backed up with incredibly accurate, fair and high-speed automated processes in the back office.
Imagine AI-enabled dashboards with deep visibility into how the company really is
The reality is that you are almost there already without knowing it. Think of how Business Intelligence (BI), now a universal tool in banks and credit card and insurance companies, came into operational use; once, it was an exotic piece of wonder only the special people could use, and then, it was democratised, secure, trusted, compliant and opened up for all levels of decision makers.
AI is almost at that tipping point. But what’s really special is that it will work with and complement all your great BI systems, but also do things they can’t. Think of a typical internal reporting process. The divisional manager passes on the command from the board to make more revenue in this particular line of business. To measure your progress against that goal, you need to report on how much revenue was actually made. At the end of the year, the leadership gets that report and with today’s BI it’ll be accurate, but really it’s a few numbers… maybe a three-color pie or bar chart?
So we can all look at this and say, We’re almost there, but we need to do something. Your standard BI pie chart can’t tell you what—it’s a static page, with minimal bandwidth or a dashboard with a few filters. But an AI-enabled dashboard with deep visibility into how the company really is at the moment with real-time data at massive scale will be a lot more useful. It’ll be able to much better tell you deep patterns, what really happened and what will happen next; allow you to do really deep ‘what-if?’ scenario planning; and so much more.
From everything, then, from better ways of promoting a digital economy to improved decision-making, from improved AML to personalised products, from back office automated efficiency to improved customer service, it’s clear that 2021 really is the year AI is set to become the next BI of the European financial services sector. And that’s got to be a good thing for everyone.