The Taiwan Banker

As global finance continues to deepen its focus on AI, the market is looking at the prices of affected stocks, and is full of expectation for the deeper development of related services. Situated between a variety of players in this new market, the financial industry is both poised for new opportunities, and worried about the challenges that may arise. Looking back at the last six years of fintech development, AI and big data applications have always been important, but the current rise of generative AI, compared with developments such as blockchain and cloud computing, marks the elevation of AI in the financial industry to a whole new level. We are approaching the “iPhone moment” of fintech. The previous stages have generated massive amounts of data, including fund deposits and exchanges, customer product selection, and risk preferences. Built using this data, the information processing capabilities and judgment ability of generative AI are almost beyond imagination. For example, robo-trading has already become an important force in capital markets, and has also been blamed for triggering the previous circuit breakers in the U.S. stock market. Interestingly, the circuit breaker mechanism was originally meant to prevent (human) investor panic from exploding, but now applies more to algorithmic trading. Following the “iPhone moment,” these algorithms will be revised and advanced to challenge the physiological limitations of human fund managers. Passive investment has gradually become more attractive than active investment; in the future, to become a top fund manager, you will not only have to compete with other humans, but also with AI. AI is challenging not only fund managers, but also front-, mid- and back-end financial practitioners. Tellers and the even most basic customer service staff may be the first on the line. Looking forward, the role of traditional indirect finance will be replaced by smarter, unbiased AI. In this new landscape, it will be critical for global regulators to protect consumer rights and maximize financial stability. When it comes to black box AIs, regulators can only trust the words of the manufacturer. The outdated regulatory techniques of the past will have difficulty adapting to this new ecosystem. It will at least be necessary to formulate regulations to standardize the scope of AI application and responsibility, giving financial institutions a clearer structure for consumer rights protection, even as certain key technologies will remain opaque. Fortunately, the government has already started executive and legislative discussions on the establishment of a unique “Financial Development Bureau.” As an information powerhouse, if we can develop local AI regtech through effective investment, we may also become a model for international regulatory development. This is by no means an unattainable dream.