A strong majority, 84%, of Singaporean Gen Z consumers, those aged 18 to 23, are aware of the potential of generative artificial intelligence (AI), significantly higher than the 76% awareness among the city-state’s general population, according to a recent survey.

Overall, nearly 60% of Singaporeans across all age groups expressed an interest in using AI for banking services, finds the Visa Consumer Payment Attitudes study. The top perceived benefits of the technology include reducing fraud risk, speeding up transaction processing and improving customer service efficiency.

Gen Z consumers show the strongest interest in applying generative AI to enhance their banking experiences, particularly in areas such as fraud detection (68%) and customer service (61%).

As well, there is a high interest by Singaporean consumers to use Generative AI for money management, the study notes. Close to seven in 10 consumers were interested most in using this technology to plan for their retirement, pay their bills on time, and track and analyse their spending. 

In addition to banking services, AI is also making inroads in retail where a quarter of Singaporeans have used AI-powered shopping tools, with Gen Z leading at 43%. Interest in AI personal shoppers is also high, the study finds, especially for personalized recommendations and finding deals.

Underscoring the potential of generative AI to innovate the banking sector, Adeline Kim, Visa’s country manager for Singapore and Brunei, predicts the technology could generate up to US$320 billion in value, adding that her company has launched a US$100 million initiative to support AI-driven innovations in commerce and payments.

“There are interesting use cases in banking that could emerge that include using generative AI to create more efficient and automated customer service and drive hyper-personalized content and product customization,” Kim adds. “For a long time, AI has been used by financial institutions to create some of these services for consumers, but generative AI will further refine and make these customizations more precise due to enhanced machine learning capabilities.”