Mr Calvin Hao Zeng
Partner

Calvin is the National Banking & Capital Markets (BCM) Leader of Deloitte China, overseeing all business functions in the industry across the region. He is a Partner in the Audit & Assurance practice of Deloitte China, where he specialises in serving a diverse cohort of Chinese mainland financial institutions.

With over 20 years of professional experience, Calvin has led numerous audit and assurance engagements for local and international banks and investment management companies. His deep industry knowledge spans an array of financial services, including retail and corporate banking, asset management and capital markets.

Calvin also has a profound understanding of the regulatory and operating environment in the Chinese mainland and is well-versed in accounting standards, regulatory compliance, internal controls and risk management practices. His insights and practical experience enable him to provide clients with high-quality audit services and value-added advice that support their strategic objectives and enhance corporate governance.

Mr Zhong Bin You
Partner

Zhong Bin is a Partner in the Financial Services Integrated Offering of Deloitte China and Co-Managing Partner of the Deloitte AI Institute. With over 17 years of consulting experience, he brings deep expertise in digital transformation, artificial intelligence applications, customer insights and financial technology innovation.

Zhong Bin has led numerous large-scale projects for leading financial institutions, helping clients drive operational efficiency, enhance customer experience and accelerate digital innovation. A leading authority in the industry, he has published numerous articles in prominent financial and technology journals and is frequently invited as a keynote speaker at major industry conferences. In addition, Zhong Bin contributes to academia as a part-time master’s program advisor at the School of Economics of Fudan University, nurturing the next generation of finance professionals.

China’s Banking Industry: Adapting to Margin Pressures and AI Transformation

As China’s banking sector navigates a landscape of low interest rates, narrowing margins, and profitability constraints, institutions are responding with strategic balance sheet adjustments, efficiency gains and digital transformation. Against this backdrop, the rise of Artificial Intelligence (AI)—particularly through China’s homegrown DeepSeek—is reshaping banking operations, risk management and customer engagement.

From asset-liability optimisation and cost reduction to AI-driven risk modelling and operational intelligence, Chinese banks are reimagining their business models to remain competitive. The next few years will decide which institutions can successfully harness technology and market-driven strategies to sustain profitability and navigate the shifting financial landscape.

Managing Margin Pressures: Asset-Liability Adjustments and Non-Interest Income

China’s banking sector is under pressure from prolonged low interest rates and tightening net interest margins (NIMs). With the People’s Bank of China (PBOC) cutting benchmark lending rates multiple times to stimulate economic growth, banks are experiencing compressed interest spreads, forcing them to rethink their balance sheet strategies and funding costs.

To cushion the impact, leading banks have reduced deposit rates, effectively lowering their cost of funds. Simultaneously, banks are shifting their loan books toward higher-yielding sectors, such as retail lending, SME financing and specific corporate segments, to protect profitability.

Beyond interest income, banks are aggressively expanding non-interest revenue streams—wealth management, bancassurance and payments—as part of a broader pivot toward an asset-light model. With regulatory encouragement, the industry is developing fee-based financial advisory services, insurance-linked products and cross-border investment platforms.

Credit Risk Management: Strengthening Resilience Amid Economic Uncertainty

As China’s economy faces structural shifts – particularly in real estate and local government debt – credit risk management has become a top regulatory and commercial priority. Although reported nonperforming loan (NPL) ratios remain stable, banks are bolstering their loan provisioning and risk buffers to safeguard against uncertainties.

To mitigate exposure, banks are deploying enhanced credit monitoring systems, real-time analytics and AI-powered early warning models. Some institutions have introduced automated loan restructuring mechanisms that proactively adjust repayment terms for stressed borrowers, preventing widespread defaults.

Regulators, too, have taken a risk-based approach, encouraging banks to:

• Tighten credit underwriting for high-risk sectors, including property development and local government financing vehicles.
• Increase collateral requirements for vulnerable borrowers.
• Expand scenario-based stress testing to assess macroeconomic shocks.

By combining stronger risk governance with predictive analytics, China’s banks are maintaining financial stability while ensuring continued credit support for the economy.

Operational Efficiency: Cost Control and Digital Transformation

With shrinking margins, banks are doubling down on cost efficiency and process optimisation. Key strategies include branch network rationalisation, automation of routine tasks and digitisation of customer engagement.

Large banks are progressively shifting customers toward mobile banking and AI-driven self-service platforms, reducing reliance on expensive physical branches. Robotic Process Automation (RPA) is streamlining back-office functions, accelerating processes such as regulatory reporting, transaction verification and compliance monitoring.

Additionally, banks are refining their marketing and customer acquisition strategies using big data analytics and AI-powered personalisation. Instead of broad mass-market campaigns, financial institutions are using data-driven insights to deliver hyper-personalised product recommendations.

The Implications of DeepSeek: A New AI Paradigm

The emergence of DeepSeek is reshaping the AI landscape in China’s banking industry, setting new standards for efficiency, cost optimisation and application across financial services.

Redefining AI Model Development

Traditionally, large AI models relied on massive computational power to achieve performance gains. DeepSeek challenges this approach by prioritising algorithmic innovation over sheer processing power, proving that AI models can reach high performance without excessive hardware dependency. This shift has substantial implications for China’s financial sector, allowing banks to adopt AI solutions without incurring prohibitive costs.

Moreover, as hardware demand moves from model training to inference, DeepSeek’s efficiency in processing complex tasks with minimal computing resources presents an opportunity for banks to implement AI-driven decision-making in real-time operations, enhancing service delivery, fraud detection and credit risk assessment.

Expanding AI Adoption Across Industries

DeepSeek’s influence extends beyond core AI development—it is accelerating the integration of AI as a financial infrastructure tool. This has profound implications for China’s banks, as AI capabilities become more accessible to institutions of varying sizes. Where global AI advancements initially fueled foreign enterprises’ digital transformation, DeepSeek is now driving a wave of AI adoption among domestic banks and financial institutions, particularly state-owned entities.

As AI-powered automation shifts from information retrieval-based applications to decision-making engines, banks can embed AI into core functions like loan approvals, wealth advisory and market analytics, raising financial intelligence to an entirely new level. Additionally, DeepSeek’s open-source strategy allows institutions to fine-tune models with proprietary data, ensuring AI applications are customised for industry-specific requirements.

The Evolution of AI-Driven Banking

The accessibility of AI technology is shifting traditional banking models. DeepSeek’s emphasis on low-cost, high-performance AI is making it possible for banks to deploy AI on devices in real-time, bringing intelligence closer to decision-making processes. This paves the way for a centralised, AI-powered banking brain, augmented by distributed intelligent decision-making at various customer touchpoints.

Moreover, as China’s AI ecosystem becomes more self-sufficient, the reliance on western technology is decreasing. With AI models tailored specifically for Chinese financial markets, regulatory frameworks and customer behaviour, the domestic financial ecosystem is becoming increasingly independent. The shift toward open-source AI ecosystems further democratises innovation, allowing more banks and fintech firms to develop tailored AI solutions.

Impact on Competition and Market Strategy

The rise of DeepSeek is also reshaping market competition. By making AI adoption more cost-effective, it is closing the gap between large financial institutions and smaller banks, allowing a broader range of players to implement AI-driven efficiencies. As AI models become more effective at predicting credit risk, optimising liquidity management and personalising financial services, competitive edge will be sharpest among those that integrate AI most seamlessly into their operations.

From a hardware perspective, DeepSeek’s push toward efficient inference over raw computational power challenges the dominance of traditional hardware providers. Chinese chipmakers are gaining traction in AI applications, signalling a new phase in China’s technological self-reliance and positioning the country as a leader in AI-driven banking solutions.

Conclusion: A New Era for China’s Banking Industry

As China’s banking industry adapts to a low-margin, high-tech environment, the institutions that thrive will be those that seamlessly integrate AI with traditional banking models. The combination of balance sheet optimisation, cost efficiency and AI-driven intelligence will define the next generation of banking leaders.

DeepSeek and other AI platforms are paving the way for a new era of digital finance, transforming risk management, lending, and asset allocation. China’s banking sector is embracing AI to enhance profitability, resilience and competitive strength.

Success will be decided by how well banks balance innovation with regulatory compliance, efficiency with service excellence, and automation with strategic agility. In an era where technology is reshaping finance, the winners will be those that move swiftly, adapt intelligently and leverage AI as a core pillar of their strategy.