Editor's note: From October 30 to 31, 2023, the Central Financial Work Conference was held in Beijing. The meeting clearly put forward the goal of accelerating the construction of a financial power, emphasizing the promotion of high-quality financial development in the mainland, and providing strong support for comprehensively promoting the construction of a strong country and the great cause of national rejuvenation with Chinese-style modernization. The Central Financial Work Conference raised the banner and planned the layout, providing a fundamental follow and action guide for promoting high-quality financial development in the new era and new journey. In order to better unify thoughts and actions to the spirit of General Secretary Xi Jinping's important speech and the decision-making and deployment of the Party Central Committee, this journal specially organizes a special topic and invites relevant professionals to discuss and exchange ideas on how to study and implement the spirit of the Central Financial Work Conference in the field of wealth management.
Zeng Shengjun, Senior Researcher, Greater Bay Area Financial Research Institute, Bank of China Shenzhen Branch
Synopsis:
- Relying on open technology, generative AI will expand more and more application scenarios, reshape business models in various industries, and have a profound impact on society as a whole.
- Finance is one of the industries with the most applications of artificial intelligence, and new technologies will support digital financial innovation, improve the level of financial services, and create more opportunities for industrial financial services.
- Deploying generative AI solutions across industries will fundamentally change the way businesses in industries operate, creating new opportunities and improving accuracy and productivity while reducing the cost of doing business.
In recent years, OpenAI has launched new generative AI models such as ChatGPT and Sora, setting off a new wave of global AI development. The breakthrough of generative AI technology also symbolizes another major progress in the development of human science and technology. Relying on open technology, generative AI will expand more and more application scenarios, reshape business models in various industries, and have a profound impact on society as a whole.
Finance is one of the industries with the most applications of artificial intelligence, and new technologies will also support digital financial innovation, improve the level of financial services, and create more opportunities for industrial financial services.
Generative AI, a milestone in technological advancement
Generative AI refers to a class of artificial intelligence technology that is capable of generating new data, images, voice, video, music, and other content to expand the application of AI systems. The global popularity of generative AI has made the disruptive potential of this technology truly visible to users around the world. Compared to traditional AI, generative AI has made significant technological progress.
Firstly, the encoder-decoder (Transformer) architecture is adopted, and the natural language processing technology (NLP) based on deep learning is used to conduct self-supervised learning through large-scale text data, so that the model can learn the latent structure, grammar rules and semantic relationships of the language. Transformer is able to process sequence information in parallel, without the need for hierarchical step-by-step processing like recurrent neural networks, and has powerful parallel computing capabilities, which can support efficient training and inference, not only learning faster, but also better understanding the overall context. Secondly, the diffusion model is used to simulate the diffusion process commonly found in nature to synthesize new data, which is better in the field of image and video synthesis. Finally, generative adversarial networks (GANs) are used to produce realistic and dynamic video sequences. GANs work by pitting two neural networks against each other: one generates content (generator) and the other evaluates its authenticity (discriminator). Through this adversarial process, the generator learns to create more and more realistic videos. With the support of a series of new technologies, the level of automation and operational efficiency of artificial intelligence have been significantly improved, and products and services have become more personalized and customized, showing stronger creativity and greater transparency.
The emergence of ChatGPT shows that large language models (LLMs) have reached a level equal to or even surpassed by humans in terms of text, audio, image creation and conception capabilities, and the application prospects are very broad. Especially since 2023, from the rapid growth of ChatGPT users to the release of GPT-4 and Sora, generative AI has not only shown great potential for technological innovation, but also promoted in-depth research and thinking in the whole society and the participation of more tech giants. For example, Google has developed Bard for natural language processing and Studio Bot for coding, IBM has developed Watson for natural language processing and IBM Research artificial intelligence systems for computer vision, and Microsoft has developed Copilot, a productivity assistant, and Azure AI Vision for computer vision. Baidu is based on the general model, according to the actual needs of customers to provide differentiated services, Wenxin Yiyan industry model number reached 11, covering energy and power, finance, aerospace, media, film and television, automobiles, urban management, gas, insurance, electronics manufacturing and social science and other fields. According to Bloomberg data, the generative AI market revenue was $40 billion in 2022 and is expected to reach $399 billion in 2027 and $1,304 billion in 2032. McKinsey predicts that AI as a whole will have a positive economic impact of up to $25.6 trillion on the global economy, of which generative AI will contribute up to $7.9 trillion.
Generative AI helps high-quality economic development
Deploying generative AI solutions across industries will fundamentally change the way businesses in industries operate, creating new opportunities and improving accuracy and productivity while reducing the cost of doing business.
Generative AI is reshaping the creation, consumption patterns, and business value of content-related industries. Generative AI can create personalized recommendations for movies, TV shows, and music based on consumers' personal preferences, and can even replace some of the work done by human writers, artists, photographers, and other creative professionals, potentially saving entertainment production companies.
In the Media & Advertising industry, marketing and advertising powered by generative AI can lead to more personalized messages and products, increasing customer satisfaction and loyalty. For the retail industry, generative AI can also help retailers increase sales and optimize operations by optimizing inventory management and recommending the right products to customers based on their purchase history and browsing behavior.
The continued expansion of generative AI application scenarios can be used in healthcare, retail, public sector, and other fields to enable the visualization of patient care, dynamic product demonstration, and government service data and information.
In the medical field, it can be used to analyze medical images to help doctors improve the accuracy and efficiency of diagnosis. According to a trial conducted by five medical institutions affiliated with the Hopkins School of Medicine, the use of artificial intelligence algorithms to analyze medical images can reduce sepsis deaths in hospitals by 20 percent.
In transportation, generative AI can power self-driving cars, allowing them to navigate the roads and make real-time safe decisions. In addition, generative AI can also address issues such as traffic congestion, parking shortages, and long commute times, thereby improving the quality, safety, efficiency, and sustainability of future transportation systems.
In addition, the inability of productivity to meet the growing consumer demand is a key problem that plagues the economic development of various countries, and it is also the main reason why stubborn inflation is difficult to eliminate. In response to the current high inflation dilemma facing most countries around the world, generative AI-powered machines and robots can perform repetitive, dangerous tasks more accurately and faster, keep workers safe, increase production time, and improve productivity and efficiency across industries, thereby reducing overall manufacturing costs. Generative AI is expected to become an important technology to curb inflation, and it will play a certain role in promoting the government's reduction of inflation.
Generative AI creates new opportunities for the development of digital finance
According to a research report by Tsinghua University, generative AI is expected to bring 3 trillion yuan of incremental business value to the financial industry, involving application scenarios and industrial finance. The advantages of generative AI in processing big data make it an important tool for digital financial services. Generative AI is reshaping the financial industry's operating model and improving financial services by introducing innovative approaches to decision-making, risk assessment, and customer experience.
● Transform the investment and trading strategies of the traditional securities business by leveraging its analytical and data processing capabilities
AI algorithms can analyze market data, historical trends, and market sentiment to make accurate predictions and identify investment opportunities. This enables financial traders and investors to make data-driven decisions, optimize portfolios, and improve overall performance. Generative AI can also create trading algorithms that adapt to changing market conditions to execute trades with precision.
● Improve the financial services experience of wealth customers by providing more personalized presentation tools
AI chatbots and virtual assistants can understand customer inquiries, provide tailored financial optimization recommendations, and help resolve issues in a timely manner. These virtual assistants can leverage generative AI to simulate natural conversations and create personalized responses that increase customer satisfaction and engagement. Generative AI can also assist wealth managers in analyzing customer data and presenting investment analysis reports to customers through vivid video effects when presenting solutions, making family wealth planning solutions easier to understand and accept.
●Streamlining the risk assessment and compliance management process in the financial industry
By analyzing large amounts of data, including financial statements, market trends, and regulatory requirements, generative AI algorithms can identify potential risks and ensure compliance with regulatory frameworks. These algorithms can generate reports, perform stress tests, and provide in-depth analysis of potential vulnerabilities. Generative AI can also help financial institutions automate compliance procedures, reduce manual errors, and ensure compliance with complex regulations.
●Promote the digital development of green finance
Generative AI can simulate the risks and opportunities presented by climate change, helping investors and regulators understand the likely impact of their decisions and identify new opportunities for green investment, while improving ESG reporting. In 2023, many domestic commercial banks have begun to apply large models, and in the semi-annual reports of listed companies, more than 10 banks mentioned AIGC, large models and other related content. For example, Industrial and Commercial Bank of China (ICBC) has realized the application of tens of billions of basic large models in multiple scenarios such as knowledge operation assistant and financial market investment research assistant, Bank of China and SenseTime have jointly demonstrated a variety of generative AI large model applications and a variety of consumer-grade AI products at the 2023 CIIE, and Bank of Beijing has released the AIB platform to create seven Q&A robots such as operation assistant and customer service assistant, and launched "Beijing Bank Investment Advisory GPT".
According to the data released by the Ministry of Industry and Information Technology, the scale of the core domestic artificial intelligence industry has reached 500 billion yuan. Banks and other financial institutions should not only increase financial services and credit fund support in the development of the artificial intelligence industry, but also pay attention to the supporting needs of industrial finance, including special hardware, cloud platforms, basic models, model centers and core industry links such as MLOps, applications and services. Financial institutions can increase industry-university-research cooperation, jointly tackle key problems with technology enterprises, universities, open source ecology and other technical forces, achieve complementary advantages in industrial collaboration, and do a good job in the reserve and layout of technology and talents in advance, so as to grasp the major development opportunities in the era of artificial intelligence. By harnessing the power of generative AI, we can achieve high-quality development of the financial industry in the process of digital transformation, and at the same time help all walks of life accelerate the formation of new qualitative productivity.
(Editor in charge: Hou Haoyi)