In the past two years, the cross-border payment industry has continued to be booming, but it has also entered a stage of obvious involution.
Many industry insiders bluntly stated that traditional channel rates continue to fall and the dividends from low-price competition have basically peaked.
When there is no way to “fight for low prices”, a technology competition with AI Agent as the core has begun in the field of cross-border payments.
Recently, we have learned that many companies have launched AI technology competition in the cross-border payment track.
Domestic and overseas players such as Ant International, Lianlian Digital, PingPong, Yeka, Visa, MasterCard, and Payne have stepped up their efforts in intelligent layout. The logic of industry competition is no longer simply “fighting for price”, but also “fighting for technology, service, and ecology.”
Payment companies focus on cross-border payment tracks and roll up AI.
The global vice president of YeahPay, Yeka’s overseas payment brand, pointed out that price competition in the cross-border payment industry has intensified. In the past, the hidden handling fees in the exchange process have become more transparent, and now they can only compete with each other to determine the level of handling fees.
In the settlement and fund management links, traditional cross-border payment methods have problems such as many transfer links, complex fees, and slow arrival. However, after the popularization of real-time settlement networks and virtual account systems, hidden costs are gradually reduced, and the competition in the future will be overall services.
Foreign-funded institutions specializing in cross-border business also have similar views.
The relevant person in charge of Paanying said that the dividends of the “price war” that relied solely on reducing traditional channel rates have basically peaked, and the industry has entered an era with “high value-added services” and “technological innovation” as the core.
On the one hand, the basic capabilities of cross-border payment are gradually becoming more and more popular, and it is difficult to form a differentiated advantage simply by relying on payment channels; on the other hand, Chinese enterprises entering the overseas market have entered a stage of deep globalization. Enterprises are not only concerned about “whether they can complete collection and payment”, but also more efficient fund management, smarter risk control, richer global resources and better customer experience.
AI is a good choice in the cross-border payment track.
Yeka has built an integrated platform that integrates domestic payment, cross-border collection and payment, fund management and risk control into the same system to help merchants reduce the operational burden caused by multi-system docking and complex reconciliation.
AI is responsible for real-time analysis and intelligent judgment, making capital flow and resource allocation more worry-free.
Other payment companies also have deeper manifestations.
Recently, Alipay announced the launch of the world’s first AI wallet for individual users, and Ant International launched a mobile intelligent agent protocol to solve key problems in the global operation of intelligent commerce, such as payment experience and security for global consumers when shopping in AI intelligent agents, as well as cross-market interconnection of merchants.
Paragon has promoted the company’s transformation into an “AI-driven” direction, embedding artificial intelligence into the platform, operations and market systems, applying AI to the product development process, and also strengthening risk control and compliance capabilities through AI assistance.
PingPong believes that in the AI era, the core competitiveness of cross-border payments is to help global companies improve their globalization capabilities and accelerate large-scale growth. Global payment platforms need to quickly understand Agent profiles, behavioral patterns, and capital flow rules between scenarios, and provide safe, convenient, and reliable global payment services. This is inseparable from the understanding of cross-border transaction scenarios, business model accumulation, and the construction of underlying infrastructure.
In the situation where the heroes are vying for the throne, each player has different playing styles.
AI applications in the field of cross-border payments are divided into three directions: infrastructure AI, compliance AI, and merchant intelligence AI. It is a progressive capability system. Currently, everyone pays more attention to merchant intelligence AI.
The goal of some institutions is to “systematize the upgrade of AI from the entire process of production and research to business scenario applications.” For example, Pay Anying wants to build a digital cross-border financial infrastructure suitable for “next generation global commerce”; Ant International, Lianlian Digital, etc. are taking an open, cross-ecological route, exporting underlying technical capabilities, launching market-oriented products, and helping merchants complete intelligent transformation; some institutions are optimistic about the development space of merchant intelligent AI and focus on exploration. For example, Visa has launched a variety of products to support AI agents to safely complete transactions and establish trust mechanisms.
However, the entire industry is getting together to deploy AI, which seems to be hot, but some institutions are still stuck in “verbal submission”, and there are difficulties in implementing core payment scenarios.
Data and compliance barriers are a major difficulty. Cross-border business involves many places around the world, and data storage, transmission, and usage rules are different. The problem of data islands is prominent. It is difficult for institutions to collect compliant and high-quality data to train models. Algorithm operation and data processing face regulatory constraints.
The popularization of AI agents will easily give rise to new financial risks, and most institutions have not yet established complete agent authority management, risk warning, and emergency response mechanisms.
Cost and technical barriers have also widened the industry gap. Small and medium-sized payment institutions are unable to afford investments in AI R&D and can only test the waters in edge scenarios.
Limited by practical difficulties, many institutions tend to be conservative.
From price competition to technology duel, the transformation of the cross-border payment industry is the general trend.
AI and AI agents have opened up new growth space for the industry, but intelligent transformation does not happen overnight.
The era of AI is not about “the strong take all”. Leading institutions can contribute to the underlying infrastructure and global ecology. Small and medium-sized institutions can take root in regional markets and vertical industries to create customized services and form an industrial structure with complementary advantages to avoid falling into a new round of technological involution.
In the future, only institutions that can balance technological innovation, compliance operations, and commercial value can gain a firm foothold in the industry reshuffle, and the cross-border payment industry will also move towards a new stage of high-quality development.
