The rapid pace of technological advancement and adoption, driven by an increasingly influential and digitally savvy customer, is having a transformative effect on banking in China – from payments and retail banking to wealth management and corporate banking, an industry expert said.

Many banks, from big names to city banks, are embracing this trend and devising a strategy for collaborating – or competing – with the growing number of fintech firms and leading technology companies starting to enter the financial services space, said Tony Cheung, head of advisory for financial service at KPMG China.

"We have seen some banks developing their own fintech solutions, while an increasing number of financial institutions are entering into strategic partnerships and alliances with fintech firms," he said at the firm's exhibition area during the second China International Import Expo held in Shanghai from Nov 5 to 10.

Cheung stressed that the development of fintech, digital and open banking and the proliferation of emerging technologies including artificial intelligence, blockchain, cloud computing and natural language processing continue to disrupt the banking industry.

As multiple approaches are being tested for the launch of the first digital currency of the People's Bank of China in the country, Cheung said the digital currency can become a tool that could allow policymakers to monitor and steer market activities and the economy.

"Digital currency has the ability to track money electronically as it changes hands, and it would be useful in anti-money laundering and fighting other illegal activities in the financial services industry," he said, adding China is one of the leading markets when it comes to implementing advanced technologies in the financial services sector.

To prevent risks, he noted banks must improve their controls and governance to ensure AI and its associated risks are properly managed. Banks should seek to develop a purpose-built risk and control framework that can help mitigate data privacy, security and regulatory risks across the entire lifecycle of the model.