In the competitive landscape of Chinese fintech, the role of artificial intelligence is rapidly evolving from a back-office novelty into a front-line operational necessity. While early AI applications in banking focused on parsing research reports or mapping supply chains, leading digital institutions like MYbank are now pushing the technology toward the core of small-business finance. The challenge remains daunting: understanding the disparate, often undocumented realities of millions of small and micro-enterprises (SMEs) that form the backbone of the Chinese economy.
Jin Xiaoxing, Chairman of MYbank, argues that the true value of AI lies in its ability to 'read' a business rather than just a balance sheet. By utilizing multi-modal data—including phone calls, video verifications, and real-time operational context—AI models are beginning to reconstruct the actual health of a business where traditional financial records are sparse. This shift allows for a more granular assessment of an enterprise’s position within its industry, moving beyond simple credit scores to a dynamic understanding of operational capacity.
However, the transition to AI-driven banking is not without significant friction. High-ranking executives at MYbank acknowledge that while large language models (LLMs) are efficient assistants, they are not yet ready to hold the keys to core fiduciary decisions. The persistence of 'hallucinations' in AI output and the lack of a clear regulatory framework for algorithmic accountability mean that for now, AI remains a layer of support rather than a final arbiter. The industry is currently experimenting with stacking specialized data on top of general models to minimize risks in sensitive sectors like agriculture and wealth management.
Beyond risk assessment, the integration of AI is forcing a radical rethink of internal bank structures. Feng Liang, President of MYbank, suggests that the future of banking may rely on 'intelligent agents' rather than traditional staff for routine operations. This transition requires more than just better code; it demands a fundamental shift in 'production relations' within the bank. Without organizational reform that aligns with AI capabilities, these tools risk remaining mere peripheral assistants rather than catalysts for a new era of high-efficiency, inclusive finance.