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Shanghai Financial Regulator Issues Measures to Boost AI Use in Banking and Insurance
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On September 24, the Shanghai Financial Regulatory Bureau issued a set of measures to promote the application of artificial intelligence in the city's banking and insurance industries. The policy outlines several key initiatives. It encourages financial institutions to optimize the allocation of intelligent computing resources by adopting a 'rent-and-purchase' model to build hybrid cloud computing platforms, leasing national computing nodes or industry infrastructure for flexible and scalable computing power. The measures also support the development of vertical domain models, allowing institutions to balance priorities like real-time performance, accuracy, and interpretability across different scenarios. A strategy of using 'general large models as a foundation plus industry-specific models for deployment' is recommended, along with the creation of a one-stop large model application platform with scenario-based templates to lower the barrier to entry. Furthermore, the policy urges financial institutions to improve their AI evaluation systems, align with industry practices and risk control requirements, and participate in setting model assessment and certification standards.
Source report
Shanghai, September 24 (Blue Whale News) — The Shanghai Financial Regulatory Authority has issued the Measures to Promote the Application of Artificial Intelligence in Shanghai's Banking and Insurance Industries. Key provisions include:
Optimizing Allocation of Intelligent Computing Resources
- Support financial institutions in adopting a "rent-and-purchase combined" model, under the premise of security and compliance, to build hybrid cloud computing platforms.
- Enable the leasing and use of national computing power nodes or industry infrastructure to achieve flexible allocation, elastic scheduling, and linear scaling of intelligent computing resources.
- Improve cloud-edge collaborative architectures by deploying cloud computing power to edge scenarios, and enhance data processing efficiency through distributed storage technologies to meet high-concurrency and high-capacity demands.
Coordinating Development and Application of Vertical Domain Models
- Support financial institutions in independently developing vertical domain models, balancing priorities across dimensions such as real-time performance, accuracy, and interpretability for different application scenarios.
- Adopt a model procurement strategy of "general large models as a foundation + industry-specific large models for implementation," establishing a layered and collaborative model architecture that combines large models with lightweight models.
- Build a one-stop large model application platform, offering scenario-based templates to lower the barrier to entry.
Encouraging Improvement of AI Evaluation Systems
- Encourage financial institutions to enhance their AI evaluation systems.
- Integrate industry practices with risk prevention and control requirements.
- Participate in the formulation of model evaluation and certification standards.
Source: Blue Whale News
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