Introduction: The growth of the DeFi sector is crucial for the development of the entire cryptocurrency ecosystem. However, there are still challenges in the design, implementation, and maintenance of DeFi exchanges, liquidity pools, and smart contracts. To address these challenges, artificial intelligence (AI) technology has been widely applied in the DeFi ecosystem.

Market competition and changes

Defining the concepts of AIGC and DeFi

AIGC (AI Generated Content) refers to content generated by artificial intelligence, and as the technology continues to evolve, the application of AIGC becomes more and more widespread. In the DeFi field, AIGC can be used for data analysis and smart contract writing, but it also faces issues of content quality and authenticity. In the future, the combination of AIGC and DeFi will bring more opportunities and solutions to the digital economy, such as decentralized NFT markets and digital identity authentication. However, new technologies and mechanisms need to be developed to ensure the quality and authenticity of the content generated by AIGC.

The development of the DeFi market

The application of artificial intelligence in the DeFi market is in a stage of rapid growth and will provide more support for various DeFi services in the future. The decentralized and open data characteristics of DeFi provide great opportunities for training and developing AI models, such as arbitrage robots that attempt to maximise profits in expected asset price fluctuations. However, protecting the basic data used for training AI models is crucial, and various protection technologies can be adopted, such as protecting it as a trade secret or applying for patents. Emerging services in the DeFi market, such as smart contracts, decentralized exchanges, and lending platforms, can improve the efficiency and accessibility of financial services, but the regulation and risk management of these new services still need to be continuously improved. In the future, with the increase of data volume, the prospects of AI applications will become more extensive, and the potential and space for financial innovation in the DeFi market can be further expanded.

The Application of AIGC in DeFi

AI technology can be applied to optimise and automate DeFi systems, achieving more precise risk control and efficient trading strategies through AI algorithms. In addition, the data and transaction records of DeFi systems can provide a wealth of training data and application scenarios for AI, further improving the application and development of AI technology. Intelligent investment, credit assessment, smart contracts, and decentralized governance are important application scenarios for the combination of DeFi and AI, which can enhance system security and governance efficiency. The combination of DeFi and AI will drive innovation and transformation in the financial sector, leading to the following three major trends in future financial markets:

The Application of AIGC in Trading

AI has enormous potential in trading. The use of unsupervised learning methods can generate token ranking predictions, while clustering algorithms and dimensionality reduction techniques can extract relevant features and cluster datasets. This helps to better understand market trends and make more informed decisions. AI can also assist traders in executing arbitrage trades and optimising asset allocation strategies. In terms of risk assessment in trading, AI can also play an important role in identifying and flagging suspicious activity, protecting users from fraud and other financial crimes. With the continuous development of the DeFi market and the constant progress of AI technology, the potential for AI in DeFi smart trading algorithms will continue to grow and is expected to play an important role in establishing trust in the DeFi ecosystem.

The Application of AIGC in Asset Management

AI technology has enormous potential in the field of DeFi asset management. Automated market makers (AMM) are one of the key areas where AI can optimise algorithms and reduce bid-ask spreads, providing more cost-effective trading options. By leveraging AI to manage dynamic token collections, DeFi protocols can optimise asset allocation and liquidity management, providing investors with efficient, low-risk investment choices. AIGC technology can quickly screen the most promising investment targets and avoid risks to increase returns. In the future, AIGC technology will become an important component of DeFi asset management.

The Application of AIGC in Smart Contracts

AI can enhance the security and reliability of smart contracts through methods such as identifying malicious code, monitoring network traffic, and detecting abnormal behaviour. At the same time, automatically generating smart contract code can avoid developer errors and omissions, improving the quality and reliability of the contract. In addition, smart contract generation tools can enable non-professional developers to quickly generate smart contract code, thereby promoting the popularisation and development of DeFi applications. Most importantly, AIGC technology can achieve automated contract development and testing through intelligent contract generation and testing, improving development efficiency and reducing labour and time costs.

Future Direction and Core Issues

The application of AI in DeFi may become the main barrier for both DeFi and AI applications in the future, and security issues will attract more attention in future research, including research on intrinsic and extrinsic security. The applicability of AI in financial institutions requires more data support, but the limitation of security issues leads to insufficient experimental data. We believe that the issues that need to be addressed in AI research in DeFi include whether the application of AI can add value to the original liquidity of DeFi, whether the application of AI meets security requirements, and what trade-offs will occur between the robustness, reliability, and security of the system.

Impact of AIGC Technology on Privacy

• Data privacy and security issues: AIGC technology may leak personal privacy information, and strict privacy protection measures must be taken, such as encrypting user data and restricting the scope of data use.
• Dissemination of misleading and false information: AIGC technology can quickly generate a large amount of natural language content, which may contain false or misleading information. It is necessary to improve the quality and accuracy of AIGC technology, as well as strengthen regulation and review of the content it generates.

Security Issues of DeFi

• Vulnerabilities in smart contracts: AI-generated content may have some degree of error and defects, which may cause vulnerabilities in the code of smart contracts and leave room for hackers to attack. It is necessary to strengthen the audit and testing of smart contracts.
• Robot attacks and fraudulent behaviour: Attackers can use AIGC technology to generate false natural language content to induce fraudulent behaviour or system security breaches. It is necessary to enhance the security and preventive measures of AIGC technology, such as strengthening user identity verification and access control.

Conclusion and Findings

We believe that AI technology will play an increasingly important role in the DeFi ecosystem. Specifically, we are optimistic about the application of AI in the following segments:

1. Market forecasting and intelligent investment decision-making: AI technology can improve the accuracy of market trend prediction through machine learning and predictive analysis, and provide technical and fundamental analysis services to traders. This provides an opportunity for automated trading and portfolio management in DeFi.
2. Automated auditing/security protection: AI technology can improve the speed and accuracy of smart contract auditing through NLP and image recognition technology, automatically improve the effectiveness of smart contracts, and reduce the error rate of KYC/AML and fraud risk.
3. Fraud detection and credit scoring: AI technology can identify dishonest activities by analysing trends in large datasets, while also using credit scoring to promote lending activities and provide more favourable loan pricing.
4. Automated portfolio management: AI technology can use machine learning predictive models to perform tasks such as portfolio planning, strategy evaluation, pool weight calculation, signal generation, and sentiment monitoring, and build automated agents for active portfolio management.
5. Distributed lending: AI technology and distributed ledger technology can work together to design smart contracts, improve standardisation, automation, data frequency, and sensitivity, and achieve more efficient lending operations.

For these segments, we believe that the application of AI technology will bring higher efficiency, better risk control, more reliable investment strategies, and more standardised and efficient lending operations to the DeFi ecosystem. In these segments, we are optimistic about those who combine AIGC technology with other technologies to achieve higher levels of innovation and development.