The concept of the “Three Body Problem,” originally from Liu Cixin’s acclaimed science fiction novel, extends beyond physics into the realm of financial services, where the interactions between various AI entities introduce unpredictable chaos. As non-human customers—referred to as “custobots” or “economic avatars”—begin to emerge, they will add a layer of complexity to the banking landscape. The three entities in this scenario include the bank bot, regulatory bot, and customer bot. Each entity operates with distinct objectives and goals, thereby reshaping how products and services are delivered and monitored within the financial services industry. This transformation necessitates a re-evaluation of existing processes, compliance frameworks, and the fundamental nature of customer interactions.
The deployment of artificial intelligence (AI) in banking is currently fueled by the imperative to enhance efficiency and customer service while maintaining a competitive advantage in an increasingly digital marketplace. Financial institutions are investing heavily in various AI technologies, including machine learning, data analytics, and natural language processing. These tools serve to personalize customer experiences, streamline operations, and improve risk assessment and fraud detection capabilities. Despite claims of revolutionary changes, the current application of AI primarily appears as an augmentation of traditional banking processes, suggesting that while banks are evolving, they are not yet reinventing the wheel.
Concurrently, regulators are also adopting AI technologies to aid compliance in areas such as anti-money laundering and risk assessment. Early applications of AI in these domains are reportedly gaining traction, according to a Bank of England and U.K. Financial Conduct Authority survey conducted in 2022. However, the relationship between compliance bots and regulatory bots raises important questions about how they will interact in the future. The potential for friction exists, as these AI systems work towards different objectives: compliance with regulations, consumer protection, and risk management. Addressing these interactions will be crucial for ensuring that AI’s implementation serves not only to enforce regulations but also to maintain consumer trust and safeguard interests.
As the presence of AI agents, or “economic avatars,” becomes more pervasive in financial transactions, a significant paradigm shift occurs. These bots, capable of negotiating and purchasing goods autonomously, will dramatically influence the dynamics of customer behavior and institutional response. If a customer bot were to outstrip human intelligence, it could challenge traditional banking systems and established products in real-time negotiations, creating unpredictable scenarios. The bank bot’s mission to optimize revenues while complying with regulatory standards becomes even more complex in an environment where a highly capable customer bot engages actively in negotiations.
This dynamic interplay among three AI entities—the bank bot, regulatory bot, and customer bot—introduces an unpredictable element that traditional strategic planning cannot adequately address. As these bots interact, they will revolutionize concepts of value, trust, and identity in financial services. The unprecedented speed and complexity of bot interactions will require new regulatory frameworks and a rethink of customer relationships. Instances of AI entities forming their own languages or social structures during interactions highlight the potential for unforeseen developments within this new ecosystem.
The central challenge posed by this “three-bot problem” is the acceleration of interactions among the bots. Unlike the current pace of regulatory change—where feedback mechanisms exist—instantaneous AI interactions could precipitate rapid changes in customer behavior, bank responses, and regulatory demands. Using the example of instant payments and the ensuing fraud risks, one can envision a rapid feedback loop where consumer complaints and regulatory mandates prompt immediate adjustments by banks, leading to ongoing cycles of adaptation. This scenario presents an opportunity for fintech innovations targeting bot-on-bot solutions, emphasizing the need for agility and responsiveness in the face of this emerging complexity. As AI continues to develop in financial services, addressing these challenges will be vital for ensuring innovation does not compromise consumer trust and regulatory integrity.
