China’s retail banking market is facing its fourth consecutive year of market downturn, mainly influenced by a shrinking real estate market. Slowing property sales and construction have reduced the need for mortgage lending and associated financial services, which weigh heavily on the retail banking segment.

Retail sales of consumer goods in China touched an all-time low this year, dropping from 18.4% in April 2023 to 2.3% in April 2024. Despite a 34% increase in domestic travel during the Lunar New Year holiday compared to 2023, consumer spending in China has not yet significantly recovered. China continues to experience deflation, with the National Bureau of Statistics reporting an increase in the consumer price index of only 0.2%, far below its target of 3%.

Retail banking revenues for the top 50 largest banks in China—about 80% of assets—have declined since 2019. In 2020, retail banking revenue growth was at 12% but dropped to 1.4% in 2023, representing a marked slowdown in a key revenue stream for Chinese banks.

Despite Chinese banks’ effective expense management, retail banking profitability decreased by 0.2% since 2019, from 1.1% to 0.9%. The key challenge for banks is anaemic top-line growth driven by weak demand for financial services. Recent regulations further curtail retail fee income generation and the margins of banks from retail operations.

Net interest margins have narrowed, reaching a record low of 1.7% in 4Q 2023, with return on assets decreasing from 1.7% in 2019 to 0.9% in 2023. Joint-stock banks saw a bigger decline in retail revenue in 2023, being half as profitable as the big four mega banks, namely Industrial and Commercial Bank of China (ICBC), Bank of China (BoC), China Construction Bank (CCB), and Agricultural Bank of China (ABC).

Retail loan growth has reached a five-year low of 4.9% across the top 50 banks. Growth for the big four banks dropped from 10.4% between 2019 and 2022 to 5.1% in 2023. Mortgage loan defaults continue to increase, with foreclosed homes rising by 43% year-on-year in 2023 to 389,000, according to the China Index Academy.

Facing uncertainties in the macro-economic landscape, Chinese authorities have increased measures to support businesses and stimulate the economy. For instance, more than 50 cities have relaxed previous restrictions on housing purchases to boost sales. In 2023, the government began investing in businesses to boost productivity levels through upgrading initiatives, tax rebates, and interest rate subsidies, with the expectation of contributing approximately 0.5% to GDP annually. These investments are expected to continue into 2027.

Additional policies have been implemented to support the development of new consumption opportunities such as smart homes, sports events, domestic products, and Chinese homegrown goods. Urbanisation efforts are being made to grant urban residency to more rural migrants, which is expected to further increase consumption by 30%.

Lastly, the government has announced more measures to boost consumption in various sectors, such as automobiles, real estate, electronics, tourism, and services. These measures include expanding consumer loans, building electric-vehicle charging facilities, developing affordable housing, and promoting wearable technology. China aims to transition its growth strategy from relying heavily on investments to prioritising consumption.

In this context, Chinese banks are increasingly emphasising improving the customer experience and advancing the business through third-party collaboration supported by AI technologies. In fintech, Chinese banks leverage GenAI, data analytics, and anti-fraud to traverse macroeconomic headwinds.

ICBC and China CITIC lead on the GenAI front, with ICBC holding a significant scale of GenAI models and algorithms in the industry and China CITIC integrating multimodal touchpoints such as images and video seamlessly with user interactions. Today, nine out of 10 first-tier mega and joint-stock banks in China have large language models in production

Many banks, apart from the largest, still have ageing infrastructure unfit for modern applications. For AI scaling, banks prioritise a robust data foundation and efficient data and analytics infrastructure. These will help achieve structured data integration, real-time data processing, and generate actionable insights. At least one joint-stock bank uses AI data analytics for decision-making on market strategy planning.

Traditional rule-based systems are now insufficient to combat fraud, with banks leveraging AI and machine learning to analyse more data. Banks have evolved from systems with a narrow set of rules to advanced models that include hundreds of features. Most implementations include a near-real-time enterprise-wide fraud detection system that covers all internal and external channels and products, as well as pre-screening to flag potential fraud. There are even cases of further integration with data analytics to allow seamless anti-money laundering detection in data across multiple operation systems.

In retail finance, the focus is on strengthening the financial and non-financial ecosystems, followed by the customer experience, digital lending, and inclusive finance. The goal is clear: to drive new revenue streams and profitability through digitalisation and personalisation of the customer journey across banking functions.

Platforming and AI have opened new avenues for banks to reach customers beyond traditional means through embedded finance and banking-as-a-service (BaaS). Launched in 2020, BoC’s Life Ecosystem Service Platform seamlessly integrates a customer’s financial services with non-financial sectors such as education, healthcare, and entertainment. In 2023, the percentage of BoC monthly active users who used non-financial life services rose by 22%.

The customer experience focus is on instant, simplified, and personalised services. China CITIC Bank’s DNA service management project has significantly improved the customer experience by integrating digital platforms and monitoring customer sentiment to create a seamless and personalised service journey.

Small and medium-sized enterprises (SMEs) have also benefited from AI in the inclusive finance category. AI-driven platforms help banks analyse non-traditional SME data, opening new streams of revenue for SMEs that are unqualified under standard metrics. For instance, CCB offers a Personal Business Quick Loan using a digital credit model that integrates multi-dimensional data and has to date achieved over RMB 500 billion ($68.7 billion) in loan balance, serving over one million customers by the end of 2023.

Shift from a technology-centric to customer-centric strategy

Chinese banks have been primarily managing their retail banking business through technology-driven strategies, but now they must add an important layer that focuses on the needs of each customer, with customer experience coming in second. While technological advancements are significant, a strong emphasis on customer experience must complement it. The need to drive additional revenue streams pushes banks to provide products and services through digital lending capabilities and to engage with SMEs on credit scoring via inclusive finance. Customers’ relationships with their banks have deepened as banks create platforms to support their financial and non-financial needs, harnessing continuous technological improvements through big data analytics and automation to enhance customer-centric strategies and prioritise customer needs.