The pros and cons of AI-powered bots in payments and transactions (Part 1)
The integration of AI-based bots in financial systems is dramatically altering global payment infrastructures, bringing both speed and complexity to transactions. These bots are able to carry out transactions at impressive speeds with great accuracy, fundamentally altering financial interactions for both businesses and consumers. Major concerns about this shift include the effects on payment speed, security, and ethical dilemmas. Through their automation of decisions and management of real-time transactions, AI bots are likely to foster demand for new digital money forms, such as CBDCs and sophisticated stablecoins.
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A notable development in this space is that of Siemens becoming the first client of JP Morgan to use the bank’s new programmable payment functionality with the JPM Coin - this innovation allows companies to establish complex payment rules, moving beyond traditional conditional payments. Through a new ‘if-this-then-that’ interface, JP Morgan’s online treasury portal enables programmable payments that can trigger actions such as topping up accounts based on certain conditions - e.g. margin calls or enabling delivery v payment when buying and selling securities. Other use cases include releasing funds and paying stamp duty taxes when property title deeds are transferred; all of these transactions can happen 24/7, automatically. Siemens views this as a crucial step toward optimising working capital, supporting digital business models and enhancing scalability for its treasury operations. However, this shift towards increased automation also raises important concerns regarding accountability. As bots take over more tasks, will increased automation in payments lead to a rise in litigation, particularly regarding errors made by bots and the distribution of liability? Certainly, this evolving landscape invites critical discussions on both the benefits and challenges posed by the growing role of AI in financial transactions. In the world of payments and financial transactions, AI-powered bots are automating processes through advanced algorithms that analyse, execute and manage transactions instantly. These bots can pull data from a range of sources, such as market behaviour and customer activity, to make decisions; they can automatically initiate transactions, trigger payments when certain criteria are met and ensure settlements are completed on time. Additionally, they evaluate potential risks, ensure compliance with regulations and manage cash flow without human intervention. By combining AI with blockchain technology, bots can enable faster, more secure and transparent transactions, whereby minimising errors and lowering operational expenses. AI bots continuously improve their performance by learning from transaction data, so increasing both efficiency and accuracy - this automation boosts the speed, scalability and dependability of financial systems, making them highly beneficial for businesses aiming for streamlined operations and optimised capital management.
Moreover, key area where AI-powered bots have demonstrated remarkable impact is in the stablecoin space. Visa's recent research finds that bots account for 90% of stablecoin transactions, reflecting the growing role of automation in financial processes. The study also reveals that fewer than 10% of these transactions arise from real users, with only $149 billion of the $2.2 trillion total transactions last month driven by organic payments. This suggests that, whilst stablecoins show promise, they are still in the early stages of becoming a widely used form of payment. As McKinsey forecasts, the tokenised market capitalisation across various asset classes could reach $2 trillion by 2030 and, with such growth, digital payment solutions powered by AI will be vital. However, although Visa’s research signals a nascent stage for stablecoins as a payment method, it also points to their long-term potential. The market's limited demand and technological adoption, as noted by industry experts, underscore the challenge of making AI-powered systems and digital currencies more user-friendly and accessible. The payments and transactions space are being revolutionised by AI-powered bots, offering several benefits that boost efficiency, security and accessibility. As financial services evolve, AI is emerging as a key tool for automating processes, cutting down costs, enhancing fraud detection and providing highly customised bespoke experiences.
One of the most notable benefits of AI-powered bots is their ability to streamline payment operations, resulting in faster and smoother transactions. AI systems remove human delays, optimising payment flows and significantly reducing transaction processing time. For example, PayPal’s AI-driven fraud detection system processes over $1 trillion in payments annually with few errors. By leveraging extensive data, PayPal’s AI can identify fraudulent activities in real-time, offering speed and security. In turn, this prompts the question: can traditional banks, restricted by legacy infrastructure, compete with the speed and efficiency of AI systems? It also helps to explain why we are seeing such a surge in the number of FinTech firms - in the UK there are 1,600 and these are expected to double by 2030, in Holland there are 850 FinTech companies. But is it not only in Europe - look at the huge success of Brazilian-based, NUbank, which now has over 110million customers and has recently announced it is to move its legal HQ to London. Certainly, AI-powered bots are reshaping the financial landscape, handling 90% of stablecoin transactions and enabling instant, automated payments, but is this truly innovation or simply the beginning of a market dominated by machines? JP Morgan’s programmable payments and AI-driven fraud detection at PayPal and NUbank showcase efficiency, but at what cost? If bots are executing, verifying and even deciding transactions, who is accountable when things go wrong? As tokenised assets approach $2 trillion by 2030, the relevancy of banks and regulators remain questionable, with the possibility of AI-controlled finance rendering them obsolete. Traditional institutions will need to adapt and the rise of FinTech AI giants could leave them behind. And most critically, if bots are running the financial system, where does that leave real users? Are we automating efficiency or losing control?
In Part 2 we look at how AI-powered bots are revolutionising financial transactions, whereby enhancing speed, efficiency and fraud detection whilst introducing security and regulatory risks. However, concerns arise over cybersecurity risks, regulatory uncertainty and job displacement as AI takes over financial decision-making. So, as AI continues to dominate finance, the challenge remains: can automation enhance financial systems all the while ensuring trust, security and human oversight?