In this session, we will consider the ways in which AI will affect the subset of human interactions associated with financial transactions. The reliability and predictability that is required of systems operating in the general area of “finance,” and the large scales over which it is conducted, depend heavily on more formal, objectively measurable system performance parameters than is the case in many other domains of human behavior.
In the 20 minute presentation by James Garza, the transformative impact of artificial intelligence (AI) in finance will be discussed, particularly focusing on quantitative analysis and reinforcement learning, a subset of AI. Reinforcement learning can be more consistent than human traders, and this reliability allows for consistent and stable returns. Furthermore, reinforcement learning’s ability to rapidly process vast amounts of data helps identify patterns and insights humans might miss. Reinforcement Learning operates as a decision-making agent, learning from the consequences of its actions to maximise long-term rewards while minimising risks
AI-powered information elements introduce both helpful and potentially harmful variables into the financial space. Also, the ways in which AI is integrated into finance can offer reproducible patterns for AI implementation in other domains, as well as lessons to be learned about potential system harms.
The session will offer just a glimpse of the potential AI holds for the future of finance. By harnessing AI responsibly, we can create a more inclusive, efficient, and secure financial system for all.
Let’s explore together:
- Future of Personalized Finance: How might AI systems act as financial advisors that know you better than you know yourself? AI-powered algorithms can analyze your spending habits, financial goals, and risk tolerance to create personalized investment portfolios, budgeting plans, and even predict future financial needs. How will AI democratize access to financial advice, previously reserved for the wealthy.
- Frictionless Transactions: The reliability of finance has historically been associated with endless paperwork to generate auditable paper trails for interaction accounting. AI-powered chatbots can handle routine tasks like account inquiries, fund transfers, and even loan applications, making financial transactions seamless and available 24/7.
- Enhanced Fraud Detection AI will help to identify patterns of fraudulent activity in real-time, by analyzing massive datasets of transactions to help curb and prevent costly criminal activity. Greater reliability and confidence is a pathway to greater trust in financial systems.
- Algorithmic Trading: With lightning-fast analysis and the ability to execute trades in milliseconds, AI-powered algorithms are already powering high-frequency trading. In the future, their impact could extend beyond Wall Street, potentially making automated investment management commonplace for individual investors. However, ethical considerations and potential market manipulation risks need careful attention.
- Democratizing Access to Capital: AI can open doors for those traditionally excluded from traditional financial services. By assessing creditworthiness based on alternative data sources beyond credit scores, AI can enable lenders to extend loans to underserved communities, promoting financial inclusion and economic growth. This also comes with challenges, like ensuring fair and unbiased lending practices.
By the end of our session, attendees will have a broader perspective on the role of finance among a broad array of information systems, and how financial institutions and processes, and the many processes that are affected by finance, can be changed – for better and worse – with AI.
