A new chapter for AI

Understanding a story and telling one are very different challenges for a robot. Seán Jevens, Chief Digital Officer at Irish bank AIB, and Pierre-Louis Durel, Head of Customer Success for AI specialist Yseop, compare notes

The Irish government has just given itself the mission of making the country a global leader in the use of artificial intelligence (AI).

Its eight-strand policy, announced in July 2021, has a particular emphasis on AI education, promoting the adoption of AI tools by Irish enterprise, as well as building a strong ecosystem to benefit the economy and wider society with a ‘people-centred, ethical approach to AI developments, adoption and use’.

The strategy builds on the fact that the country’s capital, Dublin, hosts one of the EU’s 30 Digital Innovation Hubs, and that Ireland has long been an important centre for the European operations of AI trailblazing technology giants Google, Apple and Facebook.

They, in turn, have helped to create a thriving network of fintech firms, mainly sited in Dublin’s docklands, which is now inevitably known as Silicon Docks. That ecosystem has also fed the country’s major banks, which have collectively invested more than €3billion in their digital services in the last five years. Irish firms have made up a third of the 100 fintech partnerships forged in the process, according to figures compiled by the Banking and Payments Federation Ireland (BPFI). “That comes down to integrating machine learning into delivery mechanisms. But at AIB we are able to spot propensity triggers and now we’re getting to a point where we’re able to deliver them in a timely way, too, to customers and staff, so that they can act on them.“

While, for banks like AIB, the big focus up until now has been using AI to translate human experience into code, equally important for their back-office processes is translating code into something intelligible for humans. It’s another area in which AI can potentially help to reduce the significant costs of meeting regulatory and reporting requirements.

To quantify that, French AI software specialist Yseop, says it has reduced analysts’ time spent writing and updating reports from 48 per cent of their working day to just nine per cent, by applying its pioneering natural language generation (NLG) tech to translating structured financial data into a clearly-written narrative over its Augmented Financial Analyst platform. Pierre-Louis Durel, Yseop’s head of customer success, says it’s suitable for profit and loss analysis, risk and compliance, as well as fund and portfolio reports. And he claims it offers a potentially big return on investment.

An example of one of those deals involved Ireland’s largest retail bank, AIB, and the Dublin-based data analytics company Boxever, whose technology the bank leveraged in order to better engage with its customers.

AIB has so far used AI in biometric onboarding, to interrogate datasets to find cohorts of customers who might be interested in its services, to retain existing customers, and machine learning in payment tracking and reconciliation.

AIB’s chief digital officer, Seán Jevens, says it has been thoughtful about where it applies the technology. “As with all great technologies, there is always the risk of tech hijack where something has no real, productive use,” he says.

AI on its own is of limited value, he points out, unless you have a way of interpreting and delivering the insights it reveals when they are needed – such as in customer relationship management (CRM).

“A lot of the failure I’ve seen around AI and CRM wasn’t because the insights weren’t good and clever, it was due to companies’ inability to deliver those insights to the right people, at the right time,” says Jevens.

Story-telling AI:

A balance between deterministic and probablistic

“There are a lot of controllers spending Back at AIB, despite the significant insisting a lot on operational excellence a lot of time just consolidating data to do a investment it has so far made in its digital – we talk even more about operational first analysis. It’s a big advantage to be able services, Jevens is candid that it still has a excellence than cost reduction. It enables to free up this time for them to exploit the long way to go in its AI journey. Its chatbot them to standardise and speed up their analysis rather than just write it down,” is, for example, still taking ‘baby steps’, he processes, standardise the documents they he explains. “We have more than 50,000 says. But the bank is hesitant for a reason. are producing to avoid any error, any risk. users live in Europe, the Middle East and “There are lots of bad examples [of It’s clearly a big benefit. Africa (EMEA) and the US – it’s our daily robotic chat services]. Customers have “The second important thing for them is obsession to make data real for banks, been burned by that, provoking comments the internal satisfaction of analysts. AI is insurers and others; to make AI like ‘I can’t talk to anyone. They’re putting clearly a must-have for providing more accessible to all.” this ridiculous capability on a daily basis. I think it could

Hot on the heels of the chatbot in front of also be a way to retain talent in a bank or release of Augmented me that can’t other organisation, too.” Financial Analyst, Yseop understand Jevens agrees that the future adoption also developed an anything I say’. So of AI in banking will impact on many levels application called ALIX, how we stitch that – not just cost reduction. which quickly assesses if natural language “I think AI will help us standardise and a report is suitable for into our core API improve our data and service quality across interpretation by the the board,” he says. platform – a kind of AI “A lot of our digital investment so far has triaging. The Analyst been in the priority use cases, the platform and ALIX, as high-volume customers. Where we really well as the development need to stretch digital now is the more of a no-code studio so that it can embed complex cases – the joint customers, the some pre-packaged analysis and text to multi-party SMEs – and when dealing with ease report creation, are just the latest fraud cases, to get to customers more in a long line of investments made by quickly whenever we suspect some activity Yseop since it was founded in 2007 by a on their account so that we’re not relying mathematician and a linguist. on an agent who’s spotted something, to

It’s much harder for a robot to write a pick up the phone and narrative from code than it is for code ring them. We’ll be much to be written from narrative. It has to take more interactive, in terms into account all the randomness of human of how we do that. nature in the interpretation. service is, for me, the “The other place we

“But at Yseop, we have the option to real challenge.” see it really helping combine machine learning with Nevertheless, as AIB customers is preventing deterministic AI, to be able to generate shifts towards having them falling into debt, error-proof text, and, at the same time, more of its products by being more proactive adapt the text to user preferences,” explains and services available as as a bank in spotting early Durel. “I think we’ve found the right balance APIs, Jevens sees huge signals of vulnerability. between deterministic AI and probabilistic potential in using natural “Australian banks have AI to have the best of the two worlds.” language processing to make its core done some good work in this space,

One among several of the large European services available within key Big Tech apps suggesting the customer, for instance, uses banks with which Yseop is working on such as Facebook’s WhatsApp and spare funds to pay down their credit card. intelligent automation roadmaps recently Messenger, Google’s Alexa and Apple’s Siri. It’s maybe counter-intuitive for a bank, but, approached it with a request to make its That’s especially so as customer demand in the long term, it’s the right thing to do reports more readable. for point-of-sale credit increases and the for everybody.

“It was a manual internal report, with appetite for having multiple apps stored “In Canada, banks have done work in the a lot of tedious graphs, and it was pretty on devices like smartphones almost opposite space, in helping people save, complex to understand,” says Durel. certainly wanes. again using AI to identify signals and saying “The bank decided to use our technology “We’ve already adapted for that, ‘well, actually Pierre’s got spare cash at the to revamp it with more dynamic text and and will continue to do so,” Jevens says. end of the month, let’s help him save that’ a focus on the important insights. As a result, Durel also sees AI propelling banks in an intuitive and natural way. I think that’s this internal report, because it’s so much to ever-higher levels of efficiency and where AI will come more to the fore, as we easier to read, is widely shared today and customer experience. become more comfortable with it.” we are extending the parameter for analysis “It’s very clear that our AI has enabled And, as it gets more comfortable with us so that the bank can have more and more banks to cut costs, but it’s not the only – as adapt at telling as it is understanding people using it on a monthly basis.” benefit,” he says. “Our customers are human stories.

Our customers are insisting a lot on operational excellence – we talk even more about operational excellence than cost reduction

Pierre-Louis Durel, Yseop

Working smart: AI can help banks step in AI will help earlier to help customers us standardise and improve our data and service quality, across the board

Seán Jevens AIB