AI is the talk of 2024, with ChatGPT, Claude, Perplexity and other tools taking centre stage, but how will this technology transform the very fabric of some vital industries that we rely on today?
The truth is that AI is evolving so fast it is difficult to predict the long-term impact. What is clear is that it is now a supportive tool within many organisations and is quickly becoming an integral part of how companies operate.
As AI agents become more autonomous, it is crucial that we take a step back to understand where society can benefit most. According to Capgemini research, 82 per cent of organisations with over US$1 billion in revenue plan to integrate AI agents within the next one to three years. Companies will begin to trust them with tasks like email generation, coding, and data analysis.
Today, let’s focus on one sector that is poised for a major transition: banking and finance. With profound implications for efficiency, personalisation, and security. As these agents start transacting with one another there are profound implications for personalisation and security in the entire financial services sector.
AI agents facilitating autonomous transactions
As AI agents become more capable, they will be able to conduct transactions and complex processes without the need for human intervention. However, it is important to put the right safeguards in place to ensure the right levels of accountability when it comes to AI decision making. According to Charles Dray, Founder of Resonance Security,
“As of today, November 2024, AI requires a human operator. Without an operator confirming accuracy of replies, and continuous AI threat modeling which tests the AI to see how much it takes to make it provide an incorrect reply and correcting it, the AI can stray away from its expected behavior.
AI providing incorrect replies for financial services companies can be a major risk. Not only can it damage reputation, and feed incorrect actionable information, but it will reduce the personal touch customers love. On the other hand, deploying new technology helps technology scale, so it’s a matter of who wants to dive in first. Chances are we’ll learn a lot from early adopters “
You only have to consider the scenarios to see the risks. Imagine AI agents autonomously negotiating loans, executing trades, or even processing insurance claims between different banks or financial institutions.
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The autonomous nature of these transactions will mean that banks and fintech companies will be able to execute real-time financial decisions. Whether it’s approving loans based on AI-verified data or negotiating cross-border payments, the speed and accuracy of these processes will be unparalleled.
Transforming customer engagement with hyper-personalisation
AI agents excel at analysing vast amounts of data, allowing them to tailor financial services to individual customers. These agents can interact naturally with both humans and other AI systems, enabling a new level of hyper-personalisation in banking. From personalised loan offers to real-time investment advice, AI agents can cater to the unique needs and preferences of each customer.
Chris Sotraidis of Autonomys, a decentralised network designed to enable secure, sovereign collaboration between humans and artificial intelligence, notes that AI agents are already dramatically enhancing customer service by providing personalised, human like support.
“The transition has happened rapidly and is already evident. Proactive customer support is the next evolution. Chatbots, and even real-time phone bots are in beta.”
A new era of hyper-personalisation is coming and will give customers more control over their finances, allowing personal AI agents to proactively manage their savings and optimise their investments.
AI agents revolutionising fraud detection and risk management
Traditional fraud detection systems are often slow and reactive, identifying issues after the fact. In contrast, AI agents can autonomously analyse massive volumes of transactions, quickly identifying suspicious behaviours or fraudulent activities.
For instance, Mastercard has already begun using AI to double the speed of identifying potentially compromised cards while reducing false positives. This ability to detect anomalies instantaneously allows financial institutions to act before the fraud can escalate, protecting both institutions and customers.
Sotraidis cautions against relying AI models to execute all transactions autonomously speaking about the risk of adversarial attacks on AI models where data can be easily manipulated.
“This creates a need for new governance structures to manage accountability, especially in the case of incorrect or fraudulent transactions initiated by compromised agents. It will be essential for money managers to fully understand and trust the fidelity of their decision-making systems,” says Sotraidis.
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The new frontier in finance with decentralised finance (DeFi)
One of the most exciting developments today is the potential of AI agents within DeFi. DeFi platforms allow peer-to-peer financial transactions without intermediaries, and AI agents can interact with these protocols, executing trades, loans, and asset management. This opens up a future where AI agents could manage entire portfolios.
In this scenario, AI agents could even cooperate across different blockchains, managing transactions, and ensuring compliance with complex regulatory frameworks. For example, an AI agent could autonomously navigate through the DeFi ecosystem, lending assets on one platform while borrowing on another, all while managing risk dynamically based on real-time market conditions.
AI agents driving financial inclusion
In many parts of the world, access to traditional financial services is limited due to lack of adequate infrastructure. As Sotraidis points out,
“AI-driven mobile banking solutions will expand access to professional services in remote regions where in-person advisory at traditional branches is impractical.”
He explains that this helps to reduce the cost of delivering services and also enables institutions to provide tailored financial products to underbanked populations. By interacting with local economies and learning from local data, these agents can offer financial products tailored to specific needs.
It is clear that AI is continuing to play a growing role in our everyday lives and transforming traditional industries in ways that are unprecedented. However, as we embrace this new era, challenges around data privacy, transparency, and bias in AI decision-making must be addressed to ensure that these systems serve everyone fairly and responsibly.
Using decentralised finance to add a layer of transparency and immutability makes sense as we begin to allow these autonomous agents to act on our behalf.
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