Not only does it improve efficiency, but research shows that financial institutions also see AI as a key driver of strategic transformation

On March 17, PwC released the report “AI Accelerates Innovation and Upgrades in China’s Mainland and Hong Kong Financial Services Industry” (hereinafter referred to as “the report”), which states that artificial intelligence has moved from experimental pilots to large-scale applications. According to the survey in the report, 76% of financial institutions plan to use AI to achieve business strategic transformation and help develop new revenue streams.

The report shows that the surveyed institutions have already achieved an initial return of 11%-15% through AI investments. Seventy-six percent of respondents are willing to accept a return below 10% to accelerate AI strategic initiatives. For these organizations, while focusing on short-term gains, they place greater emphasis on AI’s long-term value in enhancing market position, expanding strategic development space, and creating new growth opportunities.

Respondents indicated that the investment returns from their AI projects mainly manifest in reducing risk losses, improving compliance efficiency, increasing revenue, and lowering costs. PwC shared specific case examples, noting that some banks have transitioned from sampling checks in workflow processes to comprehensive inspections using AI technology, significantly reducing risk losses.

Five major application scenarios—customer service/chatbots, investment and asset management, fraud detection, predictive analytics and modeling, and back-office automation—are delivering measurable investment returns and rapidly becoming key development areas in enterprise AI applications. As one senior executive from a Hong Kong bank put it, “It’s not just about improving efficiency through AI; we also hope AI will help create new value propositions and business models in the market.”

Currently, different industries focus on different AI deployment applications. Ni Qing, Partner in charge of Asset and Wealth Management at PwC China, stated, “The banking sector concentrates on risk control, anti-money laundering, and compliance tasks, while the insurance industry focuses on enhancing agent capabilities, customer service, and claims processing. In asset and wealth management, AI is applied to investment and portfolio management, data and market analysis.”

However, investment in AI technology remains a core issue. The report shows that 61% of financial institutions allocate less than 10% of their technology budgets to AI, with a 30% to 40% gap between AI investment and actual needs within the industry. Among them, 68%, 48%, and 60% of surveyed banks, insurance companies, and asset management firms, respectively, admit that their AI investments do not exceed 10% of their technology budgets.

The large-scale promotion of AI still faces multiple constraints. Respondents identified three major barriers to increasing AI investment: data availability, regulatory pressure, and the need to prioritize maintaining existing core systems. Additionally, talent shortages and rigid organizational structures are core obstacles hindering large-scale AI deployment, with impacts far exceeding budget or technical issues.

Looking ahead, the report predicts four major changes in the financial industry over the next five years: first, ultra-personalized services shifting from standardized products to AI-driven dynamic real-time service models; second, highly automated and optimized decision-making, with AI taking on more decision authority to become a “super collaborator” for humans; third, proactive intelligent compliance shifting from passive response to embedded, real-time, preemptive compliance; and fourth, real-time predictive risk management.