ARTIFICIAL INTELLIGENCE: NLP
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).
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.
“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.
Story-telling AI: A balance between deterministic and probablistic
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Issue 21 | TheFintechMagazine
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