2024年中国金融大模型产业发展洞察报告-艾瑞咨询-2024-34页_2mb

TMT Finance Group, iResearch Inc. 2024 China Financial Industry Development Insight Report

By: Sun Shi

Chapter Highlights
1. Introduction to Financial Industry Development Background
2. Financial Model Structure Features and Advantage Analysis
3. China Financial Model Excellence Awards
4. Future Development Trends of the Financial Industry
5. Industry Experts’ Insights

Table of Contents

1. Industry Development Background
2. Structure Features and Advantage Analysis
3. China Financial Model Excellence Awards
4. Future Development Trends
5. Industry Experts’ Insights

1. Industry Development Background

The background sets the stage for China’s rapid adoption of advanced AI models coupled with financial technology. The Chinese financial sector is undergoing a massive transition toward digital transformation, driven by strategic policy guidance and increased investment in technology infrastructure.

• two-fold benefits of this development
  • Reduced operational costs
  • Differentiated competitive positioning
  • Alignment with leading digital transformation trends

This phase forms a critical foundation for the widespread adoption of Generative AI (GenAI) tools within financial institutions.

2. Financial Model Structure Features and Advantage Analysis

2.1 Architectural Framework

• Three-Core Model:
  1. Base Model Support: Infrastructure derived from universal large models (e.g., GPT, LaMDA)
  2. Tool Chain Enhancement: Tools for optimizing model performance in domain-specific applications
  3. Domain-Specific Training: Fine-tuning using industry expertise and proprietary datasets

2.2 Usage Benefits

Three Implementation Stages:

• Stage 1: Deployment

  • Shorter timelines
  • Lower development costs
  • Built on evolving universal models

• Stage 2: Application

  • More precise results
  • Lighter model architecture
  • Efficient resource utilization

• Stage 3: Maintenance

  • Flexible updates & adaptation
  • Lower long-term ownership costs

3. Financial Model Excellence Awards

3.1 Selection Criteria

• Industry penetration
• Project diversification
• Service effectiveness
• Product adaptability
• Ecosystem expansion capabilities

3.2 Finalists

Leading technology providers are recognized for their contributions in shaping the future of financial AI applications, including deep-FinTech partnerships and advanced smart agent development.

4. Future Development Trends

4.1 Deployment Patterns

Edge deployment and lightweight models:

• Overcoming regulatory barriers in financial data usage
• Addressing compute limitations for smaller institutions
• Favoring models optimized for domain-specific tasks

4.2 AI Agent Evolution

Multi-functional systems will manage increasingly complex decision-making and operational workflows.

Future service models include:

• Co-pilot-style collaboration tools
• Enhanced decision support systems ↑
• Automated customer interaction platforms

5. Experts’ Insights

"We propose what we call the ‘1+V + n’ architecture," says Che Zhongliang: "a combination of a core universal platform, specialized vector databases, and a suite of small models for domain-specific applications."

Key recommendations from industry experts:

• Focus on lightweight models
• Prioritize financial domain expertise in AI development
• Build flexible governance frameworks to address regulatory requirements
• Standardize the way financial models handle compliance checking

End of Financial Industry Development Insights Summary