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American Journal of  Environmental
Economics (AJEE) 

Analysis of  Financial Policy of  China’s Economy Based on Artificial Intelligence and 
Innovation

Yuan Mengying1, Zhao Yuhan1*

Volume 4 Issue 1, Year 2025
ISSN: 2833-7905 (Online)

DOI: https://doi.org/10.54536/ajee.v4i1.3911
https://journals.e-palli.com/home/index.php/ajee

Article Information ABSTRACT

Received: October 19, 2024

Accepted: November 22, 2024

Published: April 22, 2025

In the context of  the rapid development of  globalization and digitalization, China’s 
economy faces complex and changeable challenges and opportunities. Artificial intelligence 
(AI), an important technology in the modern economy, has shown great potential in many 
fields, especially in formulating and implementing economic and financial policies. This 
paper explores how artificial intelligence and innovation can reshape China’s economic and 
financial policies. Through reviewing relevant academic journals, books, policy reports, etc., 
to sort out existing research results and identify key topics and theoretical frameworks in the 
research. To systematically review and analyze existing theoretical and empirical studies on 
AI, innovation and their impact on economic and financial policies. Utilize AI techniques 
to extract valuable information from large amounts of  data to support policy analysis. 
Analyze specific cases and explore practical experiences of  successful application of  AI and 
innovation to economic and financial policies.

Keywords

Artificial Intelligence, Economy and 
Finance, Policy Analysis

1 Belarusian State University, Minsk, Belarus
* Corresponding author’s e-mail: yuhanzhao375@gmail.com

INTRODUCTION
Since the reform and opening up, China’s economy has 
experienced rapid and profound development and has 
become the second largest economy in the world. However, 
with the change in the global economic environment, 
the traditional economic growth model has gradually 
exposed many problems, especially in the face of  financial 
risks, inefficient allocation of  resources, and insufficient 
innovation ability. Therefore, promoting innovation and 
the transformation of  economic and financial policies 
has become an urgent problem that needs to be solved. 
The rise of  artificial intelligence (AI) technology provides 
new ideas and methods for this transformation. Artificial 
intelligence technology, covering machine learning, data 
mining, natural language processing and other fields, its 
application in information processing, decision support 
and intelligent forecasting, etc., is changing the way the 
economic and financial fields operate. Through in-depth 
analysis of  large amounts of  data, AI can not only improve 
the efficiency of  policy making, but also enhance the 
scientific and targeted nature of  policies. In addition, the 
application of  artificial intelligence in financial services, 
risk management and market regulation is leading new 
economic and financial changes.

LITERATURE REVIEW
In recent years, the Chinese government has attached 
great importance to the development of  financial 
technology and introduced a series of  policy measures 
to promote scientific and technological innovation. The 
core intention of  the policy is to use modern science 
and technology to promote high-quality economic 
development and realize the transformation and 
upgrading of  the economic structure. However, there 

are still a series of  problems in the implementation of  
the policy. How to effectively embed artificial intelligence 
technology to support scientific and intelligent economic 
and financial policies has become the focus of  research. 
With the rapid penetration of  artificial intelligence 
technology into various fields of  society, the research 
of  artificial intelligence on employment, industrial 
integration, economic growth and other aspects is 
increasing day by day. For example, Autor et al. (2001) 
conducted an empirical study based on the combination 
of  robot data and macro data and found that the use 
of  robots promoted economic growth (Longpeng & 
Shuangzhi, 2020). When studying the impact of  artificial 
intelligence on total employment, Acemogl et al. found 
that substitution effect and creation effect played an 
important role (Li et al., 2024; O’Leary, 1991). Zhang 
Longpeng et al. found that the integration of  artificial 
intelligence and manufacturing industry is constantly 
improving (Qin & Li, 2023). Although there are many 
kinds of  studies, there is no consensus on the impact 
of  artificial intelligence on economic development 
(such as Aghion & Howitt, 1994; Xianpeng & Haoxuan, 
2024; Autor et al., 2001). Artificial intelligence also has 
a significant impact on the employment structure, which 
is mainly reflected in the job polarization effect, that is, 
technological progress mainly replaces the middle-skilled 
labor force, which tends to decrease the proportion of  
middle-skilled workers while the proportion of  high-
skilled workers increases (e.g. lijun Ли & Жудро, 2023). 
As for the cause of  employment polarization, some 
scholars believe that high-skilled workers are engaged in 
complex and irregular labor, and low-skilled workers are 
engaged in simple and irregular labor. Compared with 
medium-skilled workers, the two are more difficult to be 



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Am. J. Environ Econ. 4(1) 73-78, 2025

replaced by machines, and they are distributed at both ends 
of  the job skills, resulting in employment polarization. 
Empirically, many scholars have verified the phenomenon 
of  employment polarization by studying the employment 
situation of  different countries. The research shows that 
the phenomenon of  employment polarization already 
exists in the United States, Western Europe, and other 
countries and regions. Yongqin et al. (2024) found that 

industrial robots have a significant substitution effect on 
the middle-skilled labor force in China’s manufacturing 
industry. The purpose of  this study is to systematically 
review the literature related to artificial intelligence and 
economic development and to review the application of  
artificial intelligence to employment, economic growth, 
industrial integration, and other aspects in order to form 
a more comprehensive overall view of  this field.

Figure 1: The co-occurrence knowledge graph of  foreign research keywords on artificial intelligence and economic 
development from 2003 to 2024

In addition, based on WoS journal analysis, it can be 
found that foreign scholars have rich and closely related 
keywords involved in research in this field, among which 
the keywords that pay more attention are “artificial,” 
“model,” “technology,” and “intelligence.” The main 
focus of  foreign scholars on learning “big data” and 
“impact” can be divided into two categories: one is the 
technology field related to artificial intelligence; Another 
type is the impact of  artificial intelligence on employment, 
which is similar to the focus of  Chinese scholars. In 
addition, foreign scholars are particularly interested in 
the predictive capabilities of  artificial intelligence and 
its relationship with innovation. This also reflects from 
the side that the theme of  domestic research on the 
impact of  AI on the economy is relatively centralized, 
while foreign research shows a diversified trend, so it is 
necessary to encourage the diversified development of  
China’s AI from other perspectives such as technology 
manufacturing integration application, innovation 
prediction, etc.

The Development of  Artificial Intelligence
Starting from the Dartmouth Conference in 1956, 
artificial intelligence has a research and application 
development history of  over 60 years. During this process, 
we experienced three waves of  development. The first 
rise of  computers originated from their ability to solve 
complex tasks that were originally only achievable by 
humans, such as algebraic application problems, proving 

geometric theorems, learning and using English, and 
so on. However, due to the incomplete algorithms and 
insufficient computer hardware capabilities at that time, 
artificial intelligence did not achieve the expected results 
and fell into a low point. The second rise of  artificial 
intelligence came into people’s sight with the concept 
of  “expert systems”. The irreconcilable contradiction 
between the limitations of  algorithm architecture and the 
high complexity of  actual production business seriously 
reduces the practical value that artificial intelligence can 
bring, causing it to once again enter a state of  silence.
Since the second half  of  the 1990s until now, artificial 
intelligence has experienced its third rise. At this stage, 
the rapid development of  the Internet and computer 
hardware industry has made great progress in the three 
core elements of  algorithm, data and hardware that 
support the development of  AI. At the algorithmic level, 
deep learning technology has developed rapidly in recent 
years, promoting the multi domain landing of  artificial 
intelligence applications; At the data level, the massive 
data accumulation brought about by the development of  
the Internet provides a good data basis for the practice 
of  artificial intelligence algorithms; At the hardware level, 
new generation chips such as GPU (Graphics Processing 
Unit) and TPU (Tensor Processor), as well as new 
hardware facilities such as FPGA (Field Programmable 
Gate Array) heterogeneous computing servers, are also 
being widely used for specialized artificial intelligence 
computing.



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At present, artificial intelligence technologies and 
algorithms represented by deep learning, computer vision, 
natural language processing, and reinforcement learning 
are accelerating innovation and breakthroughs. Various 
artificial intelligence technologies have established a 
phased research and application foundation, promoting 
many business and life scenarios to become smarter and 
more efficient, especially in the fields of  finance, retail, 
manufacturing, healthcare, security, transportation, etc., 

giving rise to many new formats and business models, 
which are having a profound impact and transformation 
on the digital transformation of  these industries. Overall, 
from algorithms to hardware, artificial intelligence 
technology still has broader development prospects. In 
the process of  accelerating the implementation of  various 
technological applications, the development of  artificial 
intelligence technology in the future will be promoted by 
both scientific research and commercial applications.

Figure 2: Distribution of  unicorn numbers in China in 2024
Note: In the fields of  business and finance, “unicorn” specifically refers to non publicly listed companies that grow rapidly in their early 
stages and have a market value exceeding $1 billion

Concept of  China’s Economic and Financial Policies 
China’s economic and financial policies refer to a series of  
measures and policies taken by the Chinese government 
to promote economic development and maintain 
financial stability. These policies aim to regulate economic 
operations, promote economic growth, maintain healthy 
development of  financial markets, and address domestic 
and international economic and financial risks.
Macro control is an important component of  China’s 
economic and financial policies. The Chinese government 
adjusts its monetary policy, fiscal policy, and industrial 
policy to influence the overall size and structure of  the 
economy, in order to achieve economic growth and 
stability. Monetary policy mainly controls the money 
supply and liquidity by adjusting interest rates, reserve 
requirement ratios, and credit policies to achieve the 
goals of  stabilizing prices and promoting economic 
growth. Fiscal policy regulates economic operation and 
promotes economic development by adjusting taxes and 
expenditures. Industrial policy refers to the government’s 
support and guidance for different industries to promote 
industrial upgrading and structural optimization. Financial 
reform is an important component of  China’s economic 
and financial policies. Through financial system reform, 
the Chinese government has promoted the opening and 
development of  financial markets, and improved the 
competitiveness and service level of  financial institutions. 
Financial reform includes promoting interest rate 
liberalization, advancing exchange rate liberalization, 

deepening financial market reform, and strengthening 
financial supervision. The Chinese government hopes to 
improve the efficiency and risk management capabilities 
of  financial institutions through financial reform, 
promote the healthy development of  the financial market, 
and provide better financial services and support for the 
real economy.

The Current Situation of  China’s Economic and 
Financial Policies
Against the backdrop of  continuous changes and 
development in the global economy, China’s economic and 
financial policies have undergone continuous adjustments 
and optimizations to cope with the complex internal and 
external environment. In recent years, China’s economic 
development has faced multiple challenges, including a 
global economic slowdown, weak domestic demand, and 
increased financial risks. Therefore, the country has carried 
out a series of  reforms and innovations in economic and 
financial policies to achieve high-quality development.

Adaptive Adjustment of  Monetary Policy
As the central bank, the People’s Bank of  China is 
responsible for formulating and implementing monetary 
policies to maintain the moderate growth of  the money 
supply, stabilize prices, and promote employment. In 
recent years, facing the pressure of  slowing economic 
growth, the People’s Bank of  China has adopted a flexible 
and moderate monetary policy.



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Positive Expansion of  Fiscal Policy
In terms of  fiscal policy, the Chinese government actively 
takes measures to promote economic development in 
the context of  “stable growth”. The government has 
increased fiscal expenditure by increasing infrastructure 
investment, promoting new urbanization, and upgrading 
industrial structure.

Standardization and Opening up of  Financial Markets
China’s financial market has gradually formed a 
relatively complete system in the process of  continuous 
development. The securities, bond, insurance, and 
foreign exchange markets are gradually moving towards 
standardization, marketization, and transparency. In 
order to improve the openness of  the financial market, 
the country actively promotes the reform of  the capital 
market and encourages foreign investment to enter.

Risk Prevention and Control Measures
With the rapid development of  the economy, the 
importance of  financial risk management is increasingly 
prominent. In recent years, the Chinese government has 
focused on strengthening financial regulation, especially 
in areas such as shadow banking and the real estate 
market. By refining regulatory policies, strengthening 
stress testing and liquidity management for financial 
institutions, China has to some extent curbed the trend 
of  rising corporate leverage ratios.

Motivate Innovation and Promote Transformation
To promote high-quality economic development and 
industrial transformation, the Chinese government has 
formulated a development strategy driven by innovation. 
Various financial policies have been tilted towards 
supporting key areas such as technological innovation 
and green finance. For example, in terms of  venture 
capital and private equity, the government has introduced 
corresponding tax incentives to encourage funds to invest 
in high-tech enterprises.

Policy Interaction from a Global Perspective
Faced with the complex international economic situation, 
China actively participates in global economic governance 

and engages in mutually beneficial cooperation with other 
countries. By enhancing cooperation with international 
financial organizations, China actively participates in the 
formulation and improvement of  global financial rules.

The Application of  Artificial Intelligence in 
Financial Policy Analysis
With the rapid development of  artificial intelligence 
(AI) technology, the ways and means of  financial policy 
analysis are undergoing profound changes. AI not only 
improves the efficiency of  data processing, but also 
provides more accurate prediction and decision support 
capabilities, making the formulation and implementation 
of  financial policies more scientific and reasonable.
The core advantage of  artificial intelligence lies in its 
powerful data processing capabilities. Financial policy 
analysis relies on massive amounts of  data for decision-
making, and AI technology can quickly extract and 
analyze big data to identify potential economic trends and 
risk points. For example, by applying machine learning 
algorithms, analysts can monitor in real-time the impact 
of  economic indicators, financial market dynamics, 
and policy changes on the market in a rapidly changing 
market environment. This ability significantly improves 
the timeliness and accuracy of  policy analysis.
By building complex models, AI can identify and predict 
potential risks in financial markets, such as credit risk, 
market risk, and liquidity risk. This predictive ability 
enables policy makers to prepare contingency measures 
in advance. Taking credit risk as an example, AI can 
analyze borrowers’ historical data to evaluate their credit 
worthiness, help financial institutions optimize credit 
policies, and reduce default risk. By utilizing deep learning 
techniques, researchers can establish multidimensional 
models covering macroeconomic indicators, industry 
data, and market sentiment, and simulate economic trends 
under different policy scenarios through simulation. This 
model not only improves the accuracy of  predictions, 
but also makes policy-making more comprehensive and 
rational.
The widespread application of  artificial intelligence in the 
field of  financial technology has further promoted the 
development of  financial policy analysis. Many financial 

Figure 3: Annual trend of  artificial intelligence patent applications in China from 2000 to 2023



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institutions are beginning to utilize AI technologies such 
as chatbots and intelligent customer service systems to 
provide personalized services and advice. By analyzing 
customer needs and behaviors, financial institutions 
can develop targeted financial policies for different 
types of  customers, which not only improves customer 
satisfaction but also provides practical reference for 
policy adjustments.
In the modern financial field, the rapid development 
of  artificial intelligence (AI) and machine learning 
(ML) technologies has provided new perspectives and 
tools for financial policy analysis. AI can process large 
amounts of  financial data, conduct in-depth analysis, and 
provide decision support, helping decision-makers make 
accurate decisions in complex economic environments. 
The powerful computing power of  artificial intelligence 
makes it an ideal tool for processing and analyzing 
massive amounts of  financial data. Traditional methods 
often struggle to effectively handle data diversity and 
complexity, while AI algorithms can quickly analyze 
historical data, identify patterns, and provide meaningful 
insights for policy makers.

Actual Case: Federal Reserve System (Fed) of  the 
United States
The Federal Reserve System (Fed) uses AI technology 
for economic data analysis to guide its monetary policy 
decisions. For example, the Fed has developed an AI 
tool called “Point of  View” that uses big data analysis 
technology to monitor and analyze multiple dimensions 
of  indicators such as economic trends, labor markets, 
and consumer confidence in real time, helping decision-
makers adjust interest rates and monetary policy more 
accurately. This data-driven decision-making process 
enhances the speed and effectiveness of  policy responses.

Actual Case: J.P. Morgan
JPMorgan Chase has introduced AI algorithms in risk 
management, particularly in credit risk assessment. 
The bank uses machine learning technology to analyze 
borrowers’ credit records, transaction behavior, and 
social media data to predict their default risk. AI models 
can identify risk factors that traditional credit scoring 
models cannot capture, thereby helping JPMorgan Chase 
better manage its credit portfolio. In addition, they also 
introduced AI algorithms to analyze risks during market 
turbulence, in order to adjust investment strategies in a 
timely manner.

Actual Case: Goldman Sachs
Goldman Sachs uses machine learning technology to 
conduct market forecasting, in order to better understand 
market changes and future trends. They use AI to analyze 
social media, news reports, and research reports to obtain 
market sentiment and influencing factors. AI algorithms 
can not only quickly aggregate and analyze large amounts 
of  unstructured data, but also provide forward-looking 
insights into upcoming market changes. Especially during 

periods of  economic volatility and market turbulence, 
Goldman Sachs’ AI tools can quickly capture changes 
in market sentiment and provide support for trading 
strategies.

RESULTS AND DISCUSSION
The integration prospects of  artificial intelligence and 
financial policies
In this study, the analysis is carried out with the help 
of  secondary data, including statistics from major 
organizations, academic articles, industry reports and 
government releases. These data are mainly related to the 
following aspects:
Artificial Intelligence Patent Application Data: contains 
patent applications for various types of  AI technologies in 
China during the period 2000-2023, reflecting technology 
innovation trends.
Financial market data: covering key economic indicators 
such as interest rate changes, consumer confidence index, 
market demand and economic growth rate.
International case data: including the practical experience 
and effectiveness of  AI applications in the U.S. and U.S.-
based banks (such as JPMorgan Chase and Goldman 
Sachs).
We used a combination of  quantitative and qualitative 
methods to analyze the collected data, applying statistical 
methods to regression analysis of  annual trends in patent 
applications and other economic indicators to identify 
correlations and trends.
Through case studies, we analyze the specifics and effects 
of  AI applications by different financial institutions, and 
distill the elements of  success and innovation.
With the continuous advancement and widespread 
application of  artificial intelligence (AI) technology, the 
formulation and implementation of  financial policies 
face new opportunities and challenges. The introduction 
of  AI not only provides more efficient data analysis and 
decision support for financial markets but also powerful 
tools for policy makers to predict and monitor in the 
economic and financial fields. Especially in a rapidly 
developing economy like China, the integration of  AI 
and financial policies will have a profound impact on 
economic and financial development.
By analyzing Internet data, the government can grasp 
consumer confidence, market demand and other 
information in real time, so as to formulate more 
intelligent and timely economic and financial policies. 
China’s financial regulators can use AI tools to monitor 
market fluctuations in real time, adjust regulatory policies 
in time, and prevent financial foam and system risks. 
Through intelligent risk assessment and credit approval, 
more small and micro enterprises and individuals will 
be able to obtain financing support, thereby promoting 
comprehensive economic development. In addition, AI 
technology will also drive the development of  digital 
currencies and blockchain technology, bringing new 
opportunities to China’s financial system.



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In order to fully utilize the positive role of  AI in financial 
policies, the Chinese government and financial regulatory 
agencies can consider the following suggestions and 
implementation directions:

Improve Laws and Regulations
The primary task is to establish and improve relevant 
laws and regulations in response to the characteristics 
of  introducing AI technology into financial policies. The 
government should establish corresponding regulatory 
frameworks to ensure data security and privacy protection 
in the application process of  AI. This will help enhance 
public trust in the application of  AI in financial policies, 
while also protecting the healthy development of  financial 
markets.

Strengthen Talent Cultivation
With the increasing popularity of  AI technology, the 
demand for versatile talents in the financial field is 
gradually increasing. The government should increase 
its efforts to cultivate financial technology talents, 
strengthen cooperation between universities and financial 
institutions, and cultivate financial professionals with AI 
technology backgrounds. The cultivation of  talents will 
provide stronger support for policy implementation and 
technological application.

Encourage Innovation and Pilot Projects
The government can establish pilot projects to encourage 
financial institutions to actively explore the application 
of  AI technology in financial policies. Through small-
scale pilot projects, financial institutions can accumulate 
experience, find AI application scenarios that are suitable 
for their own and market needs, and provide reference 
for subsequent large-scale promotion.

Promote Cross Departmental Cooperation
The integration of  AI and financial policies not only 
involves the tasks of  the financial sector, but also 
requires cooperation from other relevant departments 
such as technology, education, and social security. Cross 
departmental collaborative policy-making will help 
establish a more comprehensive financial ecosystem, 
thereby improving the efficiency and response speed of  
financial policies.

CONCLUSION
The integration of  artificial intelligence and financial 
policies provides enormous potential and opportunities 
for the development of  China’s economy and finance. 
By fully leveraging the advantages of  AI, governments 
can formulate financial policies more accurately, manage 
financial risks more efficiently, and promote innovation 
and sustainable development. However, this process is 
also accompanied by challenges, which require efforts in 
legislation, talent cultivation, innovation pilot projects, 

and cross departmental cooperation to promote the 
effective application of  AI in financial policies. Only in 
this way can we ensure China’s steady progress in the 
transformation of  the global economic environment and 
the achievement of  high-quality development goals. From 
data analysis and decision support, risk management to 
market forecasting and trend analysis, AI technology 
helps financial institutions make more scientific decisions 
in complex and changing environments. With the 
continuous advancement of  AI technology, we have 
reason to believe that it will play a more important 
role in financial policy analysis in the future, helping 
to stabilize and promote the healthy development of  
financial markets. In the future, the effective application 
of  AI technology has brought significant results, but 
the complexity of  financial policy analysis still requires 
effective collaboration between human experts and AI to 
achieve optimal decision-making outcomes. Innovation 
driven economic and financial policies.

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