Discussions regarding the future of banking are increasingly moving beyond traditional digital channels, cloud migration, and mobile applications, as highlighted by Huawei at Mobile World Congress 2026 in Barcelona. During its dedicated Digital Finance session, Huawei convened leading financial institutions and technology partners to explore how artificial intelligence (AI) is fundamentally reshaping the core foundations of modern banking operations. The event, themed “Powering Resilient Intelligence, Co-creating Finance Future,” served as a crucial platform for Huawei to unveil significant upgrades to its Banking AI and Foundation Model Solutions, designed to spearhead the industry's next phase of transformation.

A central focus of the session was the keynote address delivered by Alvin Feng, President of International Financial Business at Huawei’s Digital Finance division. Feng's presentation meticulously detailed the accelerating role of AI in banking and underscored why financial institutions are now compelled to reassess how technology integrates into their overarching long-term strategies. He posited that while the past two decades were characterized by digital optimization, with online banking, mobile services, and data platforms enhancing customer interactions and operational efficiency, AI now heralds a far deeper and more pervasive transformation, influencing every stratum of banking operations.

“AI is becoming the defining force reshaping the global financial industry,” Alvin Feng declared during his address, emphasizing that intelligent capabilities are beginning to permeate all aspects, from direct customer engagement and sophisticated risk management to intricate internal decision-making processes. Banks have historically navigated successive waves of technological evolution, from automating back-office functions and digitizing records, to expanding customer access through internet banking, and finally, making financial services ubiquitous via mobile technology. The current era marks another pivotal transition, with the widespread adoption of AI compelling banks to fundamentally rethink service delivery models and internal workflow mechanisms.

Customer interaction stands as a prime example of this evolution. Gone are the days of rigid menus and structured forms; users are increasingly engaging through intuitive conversational interfaces capable of interpreting requests articulated in natural, everyday language. Personalization is also being scaled to unprecedented levels. Whereas tailored financial advice was once predominantly reserved for high-value clients, advanced AI systems now analyze vast datasets to deliver personalized insights and recommendations to significantly broader segments of the customer base.

Internally, financial institutions are witnessing a profound shift in work patterns. While many teams already leverage automated tools for data analysis and reporting, AI agents are introducing an additional layer of support. These agents assist staff in complex tasks such as reviewing applications, meticulously analyzing documents, and proactively identifying unusual transaction activities. Alvin Feng encapsulated this multifaceted shift as one that extends across several critical dimensions of banking operations, including customer engagement, decision-making processes, and the underlying technology architecture. He stated, “The transition from traditional banks to AI-driven banks brings profound changes in customer interactions, human-machine collaboration, decision-making approaches, system architecture, and customer experience.”

A consistent thread throughout the session was the increasing proximity of technology to the very heart of business strategy. For many years, technology was largely perceived by banks as an essential infrastructure component, primarily enabling services or reducing operational costs. However, the burgeoning reliance on AI has fundamentally altered this perspective, prompting a comprehensive reassessment of technology’s direct contribution to growth and competitive advantage. Alvin Feng articulated that financial institutions now recognize the imperative for a much clearer, more direct linkage between strategic business objectives and the tactical deployment of technology, acknowledging a significant gap that many are actively striving to bridge.

To facilitate this integration, Huawei introduced its Intelligent Finance Value Implementer framework, drawing on extensive collaboration with global banks. This model is meticulously designed to assist financial institutions in identifying impactful AI scenarios, crafting robust supporting enterprise architectures, and deploying intelligent systems in a manner that aligns seamlessly with long-term business priorities. Selecting the most pertinent use cases is paramount in this process, with projects focused on enhancing customer experience, fortifying risk control, and boosting operational efficiency often yielding the most immediate and tangible impact. Once these foundational elements are firmly established, institutions can progressively expand their AI capabilities across a wider array of services and departments. This paradigm shift is underpinned by a fundamental change in mindset: “Technology is no longer a support function. It is now a value center at the heart of the business,” Alvin Feng emphasized.

Several real-world examples shared during the event vividly illustrated how these advanced AI concepts are already being rigorously tested and implemented within contemporary banking environments. In the realm of document processing for credit card applications, AI-assisted systems have dramatically reduced manual review times from approximately twenty minutes per application to a mere twenty seconds, all while maintaining optical character recognition accuracy above 95 percent. Conversational services offer another compelling glimpse into the evolving banking experience, where natural language interfaces, coupled with specialized AI agents, empower customers to interact with digital assistants for tasks such as checking balances, making deposits, or exploring investment options. Over time, these sophisticated systems develop a deeper, individualized understanding of user behavior by analyzing patterns in transactions and past interactions, culminating in a service experience that is adaptive and personalized, rather than uniformly generic.

Small and medium enterprise (SME) lending represents yet another fertile ground for AI innovation. Loan applications in this segment frequently necessitate intricate coordination among multiple internal teams. Some forward-thinking banks are actively experimenting with systems that simulate these roles through distinct AI agents, providing invaluable support to relationship managers, operations teams, and risk analysts throughout the evaluation process. While human oversight remains undeniably critical, these intelligent tools significantly condense the time required to gather comprehensive information and formulate informed recommendations. As the President of Huawei Digital Finance International articulated, the true essence of AI banking resides in employing systems engineering to seamlessly unify AI infrastructure with open ecosystems, thereby reengineering banking processes through a potent collaboration between human and artificial intelligence.

The successful deployment of such sophisticated AI applications demands an exceptionally robust technical foundation. Financial institutions operate under stringent requirements for reliability, security, and performance, necessitating infrastructure capable of supporting demanding AI workloads without compromising overall system stability. Addressing these critical needs, Huawei utilized the Digital Finance session to introduce several pivotal upgrades. Key technologies highlighted included the SuperPoD computing platform, an advanced AI data platform, and the innovative Xinghe AI network architecture. Collectively, these systems are engineered to provide the immense computing capacity and seamless connectivity essential for powering cutting-edge financial applications driven by artificial intelligence.

Furthermore, significant engineering improvements were detailed. Huawei reported that novel optimization techniques have drastically shortened AI agent development cycles from several months to mere weeks, concurrently enhancing prompt accuracy and substantially reducing end-to-end processing latency. Such advancements are particularly crucial for large banks grappling with the challenge of integrating nascent technologies with their deeply entrenched, long-established core systems. Recognizing that no single technology provider can independently address the inherent complexity of financial services, Huawei emphatically underscored the critical importance of collaboration through its RongHai partner program.

This strategic initiative actively brings together a diverse array of technology vendors, consulting firms, and system integrators dedicated to developing financial solutions across various global markets. The program now boasts over 150 solution partners, complemented by more than 11,000 consulting, sales, and service partners worldwide. This extensive network fosters joint development, enabling banks to deploy bespoke solutions meticulously tailored to specific regulatory environments while simultaneously benefiting from a shared pool of expertise across the entire ecosystem. Huawei’s digital finance business currently extends its support to thousands of financial institutions in over eighty countries, having collaborated on projects spanning from infrastructure modernization to the implementation of large-scale data platforms.

The discussions at the MWC session strongly suggested that the financial industry is indeed poised at another momentous turning point. Artificial intelligence continues its relentless expansion into domains traditionally handled exclusively by human teams. Institutions that are proactively experimenting with these transformative tools are steadily uncovering novel and more efficient methodologies for serving customers, meticulously managing risk, and significantly enhancing operational efficiency. Alvin Feng concluded his insights with a simple yet profound observation regarding the future trajectory of the sector, underscoring the irreversible shift towards an AI-driven financial landscape.