There are many areas of technological innovation that are having a big impact on how the banking industry operates.
Biometrics, for example, could transform how people complete payments and prove their identity when logging in to their online accounts. Contactless and NFC technology is another exciting growth area, not only in payments but also in the self-service channel.
But one field that arguably has more potential than any other to transform retail banking as we know it is artificial intelligence. Its impact is already being felt in the industry – in the form of chatbots for online customer service and machine learning in fraud detection, for example – but the consensus seems to be that AI has much more to offer and will only become more influential in the years to come.
In a recent study, titled ‘The next big wave: How financial institutions can stay ahead of the AI revolution‘, Finextra spoke to a number of industry executives about the growing importance of this field and what it could mean for the future of banking.
One of the key conclusions from the research was that it is now possible to turn “the vision of AI in banking” into a reality, thanks to recent progress in areas such as big data, processing and affordable storage.
The report noted that financial institutions can use AI to gain advantages such as greater efficiency, more effective risk management, better fraud detection and improved customer service.
It also warned that those banks that are slow to get to grips with innovations in this field will run the risk of being left behind.
Roberto Ferrari, managing director of Italian bank CheBanca!, said AI will be the defining technology of the banking and financial services of the future.
However, there was also a recognition of the fact that adopting and implementing these technologies might not be a straightforward process.
Julia Krauwer, AI expert at Dutch bank ABN AMRO, said: “One should keep in mind that AI is not a plug-and-play solution. For most bank-specific purposes, you will need large quantities of data and a great amount of effort to train the models that lead to intelligence.”