Discussions about the future of banking often revolve around digital channels, cloud migration and mobile apps. At Mobile World Congress 2026 in Barcelona, Huawei placed the spotlight on what comes next.
During its Digital Finance session, the company gathered financial institutions and technology partners to discuss how artificial intelligence is beginning to reshape the foundations of modern banking.
The event carried the theme “Powering Resilient Intelligence, Co-creating Finance Future” and served as the backdrop for Huawei to introduce upgrades to its Banking AI and Foundation Model Solutions aimed at supporting the next phase of industry transformation.
Attention quickly turned to the keynote delivered by Alvin Feng, President of International Financial Business at Huawei’s Digital Finance division.
His presentation explored the growing role of AI in banking operations and why many financial institutions are now rethinking how technology fits into their long-term strategy.
According to Alvin, the industry has spent the past two decades focused on digital optimisation.
Online banking and mobile services changed how customers interact with financial institutions while data platforms helped banks improve operational efficiency.
Artificial intelligence now opens the door to a deeper transformation, one that is beginning to influence how banks operate at every level.
“AI is becoming the defining force reshaping the global financial industry,” Alvin said during his speech, noting that intelligence is starting to influence everything from customer engagement to risk management and internal decision making.
Banking Begins Another Technology Transition
Banks have moved through several waves of technological change. Early systems focused on automating back office processes and digitising records.
Internet banking expanded customer access. Mobile technology later made financial services available almost anywhere.
Another transition is beginning to take shape.
Growing adoption of artificial intelligence is pushing banks to reconsider how services are delivered and how internal workflows operate.
Customer interaction already offers a clear example. Instead of navigating menus and structured forms, users increasingly interact through conversational interfaces where systems interpret requests expressed in everyday language.
Personalisation also begins to operate at a different scale.
In the past, tailored financial advice often remained limited to high value customers.
AI systems now analyse patterns across large datasets which allows banks to deliver personalised insights and recommendations to far wider segments of their customer base.
Inside financial institutions, work patterns are also changing. Many teams already rely on automated tools for data analysis and reporting.
AI agents add another layer by assisting staff in tasks such as reviewing applications, analysing documents or identifying unusual transaction activity.
Alvin described the shift as one that extends across several dimensions of banking operations including customer engagement, decision making processes and the technology architecture supporting financial services.
As he put it:
“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.”
Linking Business Strategy With Technology Execution
A recurring theme throughout the session centred on how technology is gradually moving closer to the heart of business strategy.
For a long time, banks viewed technology primarily as infrastructure that enabled services or reduced operational costs.
Increasing reliance on artificial intelligence has started to change that perspective, prompting a reassessment of how technology contributes to growth and competitiveness.
Alvin explained that many financial institutions now recognise the need for a clearer connection between business goals and technology deployment.
He said this while pointing to a gap that many institutions are still working to close.
Building that link requires more than adding isolated AI projects.
Drawing on its work with global banks, Huawei introduced a framework known as the Intelligent Finance Value Implementer.
The model is intended to help financial institutions identify meaningful AI scenarios, design supporting enterprise architecture and deploy intelligent systems in ways that align with long term business priorities.
Selecting the right use cases plays a central role in that process. Projects tied to customer experience, risk control and operational efficiency often deliver the most immediate impact.
Once those foundations are in place, institutions can expand AI capabilities across additional services and departments. Underpinning this shift is a broader change in mindset.
“Technology is no longer a support function. It is now a value center at the heart of the business,” Alvin mentioned.
Where Banks Are Testing AI Todays
Several real world examples shared during the event illustrated how these ideas are already being tested in banking environments.
Document processing for credit card applications offers one illustration. Staff members traditionally review customer documents manually, a process that can take around twenty minutes per application.
AI assisted systems now perform the initial review in roughly twenty seconds while maintaining optical character recognition accuracy above 95 percent.
Conversational services provide another glimpse into how banking experiences may evolve.
Natural language interfaces combined with specialised AI agents allow customers to interact with digital assistants that guide them through tasks such as checking balances, making deposits or exploring investment options.
Over time, these systems build a more detailed understanding of user behaviour by analysing patterns in transactions and previous interactions.
The result is a service experience that adapts to individual customers rather than offering the same responses to everyone.
Small and medium enterprise lending represents another area where AI tools are beginning to appear. Loan applications in this segment often require coordination between multiple teams.
Some banks are experimenting with systems that simulate these roles through separate AI agents that support relationship managers, operations teams and risk analysts during the evaluation process.
Human oversight remains essential, yet intelligent tools help reduce the time required to gather information and prepare recommendations. Bringing these elements together requires more than isolated tools.
As the President of Huawei Digital Finance International noted, the key to AI banking lies in using systems engineering to unify AI infrastructure with open ecosystems, reengineering banking processes through human and artificial intelligence collaboration.
Preparing Banking Systems for AI Workloads
Applications such as these depend on a strong technical foundation.
Financial institutions operate under strict requirements for reliability, security and performance. Infrastructure must therefore support demanding AI workloads without compromising stability.
Huawei used the Digital Finance session to introduce several upgrades designed for that purpose.
Among the technologies highlighted were the SuperPoD computing platform, an AI data platform and the Xinghe AI network architecture.
Together these systems aim to provide the computing capacity and connectivity required to support advanced financial applications powered by artificial intelligence.
Engineering improvements were also discussed.
Huawei reported that new optimisation techniques have shortened AI agent development cycles from months to weeks while improving prompt accuracy and reducing end to end processing latency.
Such changes matter for large banks that must integrate new technologies with long established core systems.
Scaling AI Innovation Through Industry Partnerships
No single technology provider can address the complexity of financial services on its own. Huawei therefore emphasised the importance of collaboration through its RongHai partner program.
The initiative brings together technology vendors, consulting firms and system integrators working on financial solutions across different markets.
More than 150 solution partners now participate alongside over 11,000 consulting, sales and service partners worldwide.
Joint development through this network allows banks to deploy solutions tailored to specific regulatory environments while benefiting from shared expertise across the ecosystem.
Banks Face the Next Stage of Digital Change
Huawei’s digital finance business now supports thousands of financial institutions across more than eighty countries.
Over the years, the company has worked with banks on projects ranging from infrastructure modernisation to large scale data platforms.
Conversations at the MWC session suggested that the industry may be approaching another turning point.
Artificial intelligence continues to expand into areas that were once handled entirely by human teams. Institutions experimenting with these tools are beginning to uncover new ways of serving customers, managing risk and improving operational efficiency.
Alvin closed his thoughts with a simple observation about what lies ahead for the sector.
Featured image: Edited by Fintech News Malaysia based on an image by Austler via Freepik
