Based on an analysis of the research background, objectives, and significance, this paper employs a variety of research methods to examine the manifestations of credit risk prevention and control in China's banking industry. It further identifies the underlying causes of these risks from four perspectives: the external economic environment, internal banking operations, borrowers, and institutional factors. In response to the emerging trends and challenges facing bank lending, the paper proposes a series of countermeasures, including strengthening risk awareness, enhancing risk management, improving early warning systems, making effective use of credit risk mitigation instruments, implementing sound credit authorization policies, optimizing corporate governance structures, making appropriate dynamic adjustments to credit limits, and reinforcing governance functions, with the aim of improving credit risk prevention and control across China's banking sector.

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From ancient bronze coinage to modern blockchain-based tokens, the form of money has undergone a clearly identifiable process of evolution. Yet its fundamental dilemma has remained unchanged: how can a symbol devoid of intrinsic value—the "name"—be made to assume the function of measuring real social wealth—the "substance"? At first glance, the "treasure currency system" introduced by Wang Mang in the late Western Han dynasty appears entirely unrelated to contemporary stablecoins. In essence, however, both confront the same predicament—the separation of name and substance. This study therefore presents a perceptive and logically rigorous comparison of their respective credit mechanisms. Wang Mang's monetary reform ultimately collapsed under the issuance of "nominal values" driven by state power, whereas the central challenge for stablecoins lies in how to anchor their nominal value to credible "substance" within a decentralized framework. From this perspective, the paper naturally arrives at the conclusion that only when name and substance are unified through a credible credit anchor can monetary stability be achieved. The historical experience thus provides a valuable point of reference not only for the study of ancient monetary reforms, but also for contemporary discussions on the regulation of digital currencies, the internationalization of the Renminbi, and the ongoing process of monetary digitalization.

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Owing to the low occurrence frequencies of extreme financial risk events, risk prediction models are prone to being dominated by the majority of the normal samples encountered during the pretraining process when using financial risk data. This weakens the ability to effectively learn abnormal characteristics and thus reduces the sensitivity and stability of the developed predictive model. To overcome these limitations, a data class-balancing model, Financial Wasserstein Generative Adversarial Network with Gradient Penalty (FinWGAN-GP), is constructed on the basis of the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) framework. Experimental results reveal that the FinWGAN-GP model achieves high-fidelity generation and expansion for high-risk samples, and a balanced dataset is conducive to improving the training effect of the early warning model. Through the integration of multisource heterogeneous data and Artificial Intelligence (AI) methods, the proposed model can identify potential financial risks earlier and more accurately, helping enhance the forward-looking and scientific nature of financial regulation.

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In the context of the digital wave sweeping across all industries and the increasingly homogenized competition in the information product market, how enterprises can build differentiated competitive advantages has become a key issue. This article takes Xiaomi Group as the research object and systematically explores its differentiated competitive strategy based on an ecological perspective. The aim of the research is to reveal how technology enterprises in the digital era can create core competitiveness through ecological construction and differentiated layout in the era of digitalization, providing theoretical references and practical inspirations for information industry-related enterprises. This study adopts the methods of literature analysis and case study, and comprehensively utilizes secondary data such as public financial reports, academic papers, and industry data to systematically sort out and analyze the competitive strategy evolution and differentiated practices of Xiaomi Group. The research finds that Xiaomi's differentiated competitive strategy has undergone a dynamic evolution process from the early stage of "cost-effectiveness—online channels" to the construction of the Artificial Intelligence of Things (AIoT) ecosystem, and then to the implementation of the "human-car-home full ecosystem" strategy, and has formed a three-dimensional differentiated system covering business model, ecosystem, product technology, channel marketing, and brand users. In the digital era, enterprise competition has shifted from single-product competition to comprehensive game at the ecosystem level. Building a "product, user, data" virtuous cycle is the key path to achieving sustainable differentiated advantages.

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