IDC: The total market size of generative AI platforms and application solutions in China's financial industry is about RMB 914 million in 2024

Zhitong Finance App learned that the International Data Corporation (IDC) recently released the “Market Share of Generative AI Platforms and Application Solutions in China's Financial Industry, 2024: The Beginning of the Wind” research report. The report shows that in 2024, the total market for generative AI (Generative AI) platforms and application solutions in China's financial industry will be about 914 million yuan, accounting for about 14% of the overall AI platform and application market. This scale covers expenses for basic models, generative AI platforms and application layer products on top of the hardware infrastructure layer, and related consulting and customized IT services.

IDC predicts that by 2027, the market for generative AI platforms and application solutions in China's financial industry will rise to RMB 3,509 billion, an increase of 384% compared to 2024. In 2024, manufacturers of generative AI platforms and application solutions in China's financial industry are mainly concentrated in large Internet companies with comprehensive ecological capabilities, AI vendors that have accumulated in vertical scenarios, and large model native technology service providers. Their market share is shown in the figure below:

Judging from the deployment method

Due to the special nature of the industry, finance often has higher requirements for data security, privacy protection, and regulatory compliance than other industries. Most financial institutions will choose localized deployment methods to implement generative AI platforms and Gen AI applications. Localized deployment methods account for about 91% of the market size of generative AI platforms and application solutions in China's financial industry in 2024. Furthermore, financial institutions such as insurance, consumer/mutual finance, and brokerage firms will still use the MaaS (Model-as-a-Service (MaaS) model to connect to large models in scenarios such as contract review, intelligent customer service, and knowledge assistants, to provide a full-process large-scale model lifecycle tool chain and large model services delivered in a cloud service model.

At the generative AI platform layer

There is a strong demand for extensive model training and reasoning, application (agent) development tools and deployment, and data management. According to IDC's observation, 2024 is an important year for financial institutions to establish a foundation for generative AI platformization capabilities while proving concepts in scenarios. The commercialization demand for generative AI application (intelligent) development platforms and model management platforms is prominent. Technical service providers help industry customers build and deploy generative AI applications (agents) by providing more complete application development tool chains, model management platforms, and automated operation and maintenance tools.

At the generative AI application layer

According to IDC's observation, in 2024, China's financial industry model will enter the accelerated pilot application stage, and will mainly focus on internal productivity improvement application scenarios (such as digital operation assistants, content management, code generation, etc.), while business-related implementation mainly focuses on wealth and customer service scenarios. Furthermore, in 2024, some financial institutions will also use a public cloud subscription system to apply generative AI in internal productivity improvement scenarios such as knowledge quiz and office assistants. IDC believes that the market will explode in the next 2-3 years.

IDC believes that the basic model layer is evolving at an accelerated pace to multi-modal capabilities, promoting the application of large models in complex business scenarios through deepening cross-modal perception and understanding technology. The emergence of open source models has not only enabled AI inclusion, but also made “Foundation Model Agnostic” (Foundation Model Agnostic) the norm. This requires technology service providers to enhance model deployment and operation, application development, intelligent orchestration, and multi-agent collaboration capabilities at the platform layer, while deepening understanding of business scenarios, expanding applications from internal productivity improvement to core business scenarios to achieve AI-driven business innovation, and enhance collaborative efficiency with ecological partners to build a sustainable commercial monetization path.

Si Erxun, research manager of IDC China's financial industry, said that in 2024, the application of generative AI in the financial industry is in its infancy, and many manufacturers are in the process of building generative AI platform capabilities and exploring business scenario applications. With the improvement of model reasoning capabilities, model safety and performance capabilities, and the development of generative AI platform tool chains, generative AI will help financial institutions gradually move from interactive experience innovation to business logic innovation.

Gao Fei, director of financial industry research at IDC China, said that with the rapid iteration of technology stacks related to big models, the practice of generative AI in the financial industry is undergoing an upgrade from “local tools” to “enterprise-level platform capabilities.” Its application scenarios are also gradually expanding from a single efficiency improvement to business decision support and task execution. In this paradigm shift, the deep participation of business personnel is essential, and the integration of industry technology is a key force driving the true implementation of technology. At the same time, the construction of an AI governance system is also moving from system design to technology implementation. It not only provides a guarantee for the intelligent and orderly development of the financial industry, but is also a necessary prerequisite for dealing with future AI supervision.