Experts at Sibos 2023 recognise the benefits of new transformative technologies but caution that companies should have a plan in place to mitigate potential risks.
As a leading provider of secure financial messaging services, Swift is aware of new technologies as they sweep across the industry at a rapid pace. The advancement of data intelligence will help businesses improve their operations and become more competitive, but which technologies will win out in the race?
Jerome Piens, Chief Product Officer at Swift, explains the relevance of this debate:
“Since the release of Chat GPT, Artificial Intelligence has been a daily topic. AI has the power to be a transformational development across society – bolstering creativity and productivity – particularly in financial services.”
But while many are experimenting with new technologies, racing to improve efficiencies and enhance the customer experience, Piens cautions that we need to “recognise the risks and the trade-offs.” Only once AI is effectively governed can the industry fully realise the potential of these technologies.
“Transforming the customer experience means going back to basics, rather than getting caught up in the latest shiny new toy,” says Katrina Stuart, General Manager, Australian Payments Plus.
“The challenge of striking the right balance between automation and the human touch is crucial to avoiding the trap of overreliance on AI,” explains Bruno Campenon, Head of Bank, Brokers and Corporates, BNP Paribas. We also need to be conscious of the risk of over trust. “A bank’s biggest asset is customer trust”, he says. And when you play with data you run the risk of compromising that trust.
The devil’s in the data
Fraud is an emerging trend in the development of new technologies. “Fraudsters are early adopters of new technologies,” cautions Stuart. The ‘network effect’ is important, leveraging intelligence across the entire ecosystem and working together to maximise protection. However, Cathinka Wahlstrom, Chief Commercial Officer, BNY Melon, argues that AI can help us to identify fraudulent patterns.
Generating code and creating predictive models are among the most valuable benefits of AI. Businesses will reap the rewards because research will be much simpler and faster, and operations will be easier and more efficient. “But we need to trust the data,” emphasises Campenon. “The results you get out will only be as good as the data you put in,” he explains.
Validating your data is key. “Ensuring data quality means we can understand why customers are making certain decisions and help them along the way,” says Mark Gould, Chief Payments Executive, Federal Reserve, Financial Services.
Evolution and education
Gould explains that companies need to evolve their infrastructure, transitioning from siloed to harmonised structures. “Integrating data is one of the biggest challenges,” he says. “We need to find a way out of those verticals and into an integrated data enterprise. It’s a journey rather than a quick trip,” he adds.
Businesses need to examine and unlock all their data pools across the organisation, not just from insights, but fraud detection and prevention too. “There’s an enormous opportunity to streamline within the B2B industry, but how do you change a whole industry?” asks Stuart.
Our positive relationship with AI will depend on education. The Federal Reserve is focusing on teamwide knowledge, and learning in real time through an incubatory process. “Technology changes fast, so we need to learn fast,” says Gould.
Communication with the industry on both a practical and theoretical basis is key. “We learn by doing, by knowing what works and what doesn’t. First you educate and execute, then you experiment and evolve,” he explains.
Predictions for the future
In what’s hailed as the fourth industrial revolution, task automation and automated personalised content will be high on the agenda. Stuart takes the example of the airport experience: “I hope that one day predictive AI will be able to alert me – accurately – when my bag is ready to be picked up at baggage reclaim.”
Meanwhile Wahlstrom explores whether “machines going to take over our jobs.” Low-skilled tasks are likeliest to become automated, but mid- and high-skilled jobs could also be driven by AI, she explains.
Data intelligence will improve productivity. “One study said engineers are going to be happy, because they’re going to be able to focus on the more strategic things they enjoy,” says Wahlstrom. And at the same time, AI might create jobs we can’t even imagine right now.
If you have a Sibos digital pass, you can watch the full debate here
The views expressed on these pages are those of the authors and/or the institution they represent, and not necessarly those of Swift.
