Nvidia Blog 02月16日
AI Pays Off: Survey Reveals Financial Industry’s Latest Technological Trends
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NVIDIA最新报告显示,金融机构正将AI应用从测试转向实际落地,显著提升了AI能力并推动业务增长。近70%的受访者表示,AI已带来至少5%的营收增长,其中10%-20%的增长比例显著上升。超过60%的受访者表示,AI帮助降低了至少5%的年度成本。生成式AI在交易和投资组合优化方面的投资回报率最高,其次是客户体验和互动。随着数据管理水平的提高,金融机构更有能力利用AI提高运营效率、安全性和创新能力。

📈 AI助力营收增长和成本节约:近70%的受访者表示AI驱动了至少5%的营收增长,超过60%的受访者表示AI帮助降低了至少5%的年度成本,近四分之一的受访者计划使用AI创造新的商业机会和收入来源。

🤖 生成式AI应用场景扩展:生成式AI在金融服务行业的使用率仅次于数据分析,已扩展到客户体验、交易和投资组合管理等领域。尤其是在客户体验方面,通过聊天机器人和虚拟助手的使用率翻了一番以上,从25%上升到60%。

🛡️ 克服AI应用障碍:越来越多的金融机构部署了生成式AI服务或应用,同时,报告缺乏AI预算的公司数量下降了50%,表明对AI开发和资源分配的投入正在增加。数据问题和隐私问题以及对模型训练数据不足的担忧也有所减少。

🤝 Agentic AI驱动创新:金融机构将受益于Agentic AI,该系统利用来自各种来源的大量数据,并使用复杂的推理来自主解决复杂的多步骤问题。银行和资产管理公司可以使用Agentic AI系统来加强风险管理、自动化合规流程、优化投资策略和个性化客户服务。

The financial services industry is reaching an important milestone with AI, as organizations move beyond testing and experimentation to successful AI implementation, driving business results.

NVIDIA’s fifth annual State of AI in Financial Services report shows how financial institutions have consolidated their AI efforts to focus on core applications, signaling a significant increase in AI capability and proficiency.

AI Helps Drive Revenue and Save Costs 

Companies investing in AI are seeing tangible benefits, including increased revenue and cost savings.

Nearly 70% of respondents report that AI has driven a revenue increase of 5% or more, with a dramatic rise in those seeing a 10-20% revenue boost. In addition, more than 60% of respondents say AI has helped reduce annual costs by 5% or more. Nearly a quarter of respondents are planning to use AI to create new business opportunities and revenue streams.

The top generative AI use cases in terms of return on investment (ROI) are trading and portfolio optimization, which account for 25% of responses, followed by customer experience and engagement at 21%. These figures highlight the practical, measurable benefits of AI as it transforms key business areas and drives financial gains.

Overcoming Barriers to AI Success

Half of management respondents said they’ve deployed their first generative AI service or application, with an additional 28% planning to do so within the next six months. A 50% decline in the number of respondents reporting a lack of AI budget suggests increasing dedication to AI development and resource allocation.

The challenges associated with early AI exploration are also diminishing. The survey revealed fewer companies reporting data issues and privacy concerns, as well as reduced concern over insufficient data for model training. These improvements reflect growing expertise and better data management practices within the industry.

As financial services firms allocate budget and grow more savvy at data management, they can better position themselves to harness AI for enhanced operational efficiency, security and innovation across business functions.

Generative AI Powers More Use Cases  

After data analytics, generative AI has emerged as the second-most-used AI workload in the financial services industry. The applications of the technology have expanded significantly, from enhancing customer experience to optimizing trading and portfolio management.

Notably, the use of generative AI for customer experience, particularly via chatbots and virtual assistants, has more than doubled, rising from 25% to 60%. This surge is driven by the increasing availability, cost efficiency and scalability of generative AI technologies for powering more sophisticated and accurate digital assistants that can enhance customer interactions.

More than half of the financial professionals surveyed are now using generative AI to enhance the speed and accuracy of critical tasks like document processing and report generation.

Financial institutions are also poised to benefit from agentic AI — systems that harness vast amounts of data from various sources and use sophisticated reasoning to autonomously solve complex, multistep problems. Banks and asset managers can use agentic AI systems to enhance risk management, automate compliance processes, optimize investment strategies and personalize customer services.

Advanced AI Drives Innovation

Recognizing the transformative potential of AI, companies are taking proactive steps to build AI factories — specially built accelerated computing platforms equipped with full-stack AI software — through cloud providers or on premises. This strategic focus on implementing high-value AI use cases is crucial to enhancing customer service, boosting revenue and reducing costs.

By tapping into advanced infrastructure and software, companies can streamline the development and deployment of AI models and position themselves to harness the power of agentic AI.

With industry leaders predicting at least 2x ROI on AI investments, financial institutions remain highly motivated to implement their highest-value AI use cases to drive efficiency and innovation.

Download the full report to learn more about how financial services companies are using accelerated computing and AI to transform services and business operations.

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金融服务 人工智能 生成式AI 投资回报率
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