Finance sector AI oversight encouraged

Financial sector experts have called for stronger oversight of artificial intelligence in the industry and enhanced international regulatory cooperation to ensure that risks associated with AI can be effectively mitigated, while at the same time, harnessing the opportunities it offers for development.

Zhang Wencai, managing director and chief administrative officer of the World Bank Group, said at the 2026 Bund Summit in Shanghai last week that the world had reached a critical juncture in both the use and governance of AI. Zhang called for greater global cooperation and coordination, particularly in developing AI governance standards.

According to a World Bank survey of 27 financial sector authorities in emerging markets and developing economies, only 11 percent of survey respondents reported adoption of AI to support core supervisory functions. At the same time, nearly half of the surveyed authorities said they lack adequate systems, resources and processes to monitor AI developments and assess the fast-evolving technology's impact on financial institutions and consumers.

Zhang said enabling regulators to use AI to supervise the technology would require better-connected data and a workforce with the necessary expertise. He added that financial institutions must remain accountable for AI-driven decisions, even when they rely on technology developed by external providers, and also called for closer coordination among agencies overseeing cybersecurity, data protection and other related areas, as well as greater cross-border sharing of supervisory tools, test results and early-warning information.

Sheila Bair, a member of the International Advisory Council of China's National Financial Regulatory Administration, urged financial institutions to take a cautious approach to adopting AI until regulators develop a better understanding of its risks and how to contain them.

AI is equipping banks with more powerful tools to defend against cyberattacks, but it is also giving hackers new opportunities for foul play, Bair said on the sidelines of the Annual Conference of Financial Street Forum 2026, which concluded in Beijing on Oct 22.

Other emerging risks include a lack of transparency and algorithmic biases, particularly involving credit-granting decisions, AI-enabled fraud and concentration risk arising from reliance on a small number of AI providers, she said.

"It is absolutely essential that any use of AI be accompanied with clear governance, accountability and risk management," said Bair.

She also stressed the urgent need for information sharing protocols to help identify and counter malicious actors' use of AI, warning of its potential to disrupt financial transactions and infrastructure.

Andrew Sheng, another member of the NFRA's International Advisory Council, said regulators must keep pace with technological advances and strengthen their ability to nip emerging risks in the bud.

Regulatory failures could occur if authorities lack a thorough understanding of the architectures, risks and development trajectories of large language models, distributed ledger technology and privacy-enhancing computing, Sheng said.

He called on regulators to strengthen their expertise and develop and deploy intelligent, real-time supervisory tools capable of detecting opaque algorithms, market anomalies and hidden connections, adding that regulators should also clearly define data ownership, access rights and security boundaries while balancing the protection of personal privacy and national security with the need to unlock data's economic value.

Sheng urged regulators to deepen international cooperation to address emerging divergences in standards, protocols and algorithms. Stronger bilateral and multilateral information sharing — coupled with coordinated crisis-response protocols — are essential to containing risks across jurisdictions.

Xiao Yuanqi, vice-minister of the NFRA, said during the forum that the integration of AI and finance is a systemic transformation encompassing strategy, business operations, business models, organizational processes and corporate culture. Financial institutions need to strengthen their in-house research and development capabilities and shore up three core capabilities — data, models and engineering.

Efforts should be made to foster ecosystems through collaboration between industry and finance, promote the sharing of results through cooperation among financial institutions and advance governance through international cooperation, Xiao said.

jiangxueqing@chinadaily.com.cn