Cash News
The problem
Traditional financial markets’ exposure to inefficiencies, the risk of fraud, and manual oversight increases costs, can hinder or delay real-time transactions due to reliance on intermediaries, and raises the potential for errors and criminality. Addressing inefficiencies through automation can lead to additional risks.
Opportunities
Smart contracts (coded sets of rules and conditional actions stored on a blockchain) could improve financial markets’ transparency and efficiency. The contracts automatically execute based on pre-set conditions and can be integrated with verified real-world financial data through information bridges, called oracles. AI’s ability to process and analyze large datasets provided by oracles can be used to efficiently generate pertinent inputs for smart contracts. The combination of smart contracts and AI could streamline markets by automating routine tasks, such as financial settlement, contract execution, and compliance checks, reducing the need for manual oversight and minimizing human error. Multi-party computation protocols can be used in the creation of decentralized oracles that ensure the security and accuracy of data across blockchains operating in a trustless system. AI compliance tools can play an important role in enhancing security in automated financial markets by identifying anomalies and potential fraud. They can monitor transactions in real-time and automatically trigger smart contracts to take preventive actions, such as halting suspicious transactions.
Crypto wallets can allow AI agents to transact with each other through on-chain payments. This could, for example, enable an AI trading bot to acquire inferences from another AI model that is trained on a data set that is not generally available. Obviously AI agents do not have access to bank accounts in the traditional payment system, but they can be set up with crypto wallets and smart contracts, allowing them to exchange with each other, for example using tokens to pay for data. In September 2024, Coinbase’s CEO announced the first such AI-to-AI transaction. Potential applications of such interactions could also be much broader than in financial markets.
Risks and challenges
Vulnerabilities in oracles, such as susceptibility to data manipulation, can compromise the integrity of oracle-connected financial systems. Determining liability in such scenarios can be complex, due in part to the uncertainty of the legal framework and regulatory environment for crypto and AI-driven financial systems, particularly across international borders. AI models’ complexity can render decision making opaque, posing audit and accounting challenges. Smart contract enforceability may be legally uncertain, potentially limiting their application in traditional financial systems.