Why AI and Fintech Face the Same Dangerous Problem
Fintech’s Fee Fight Shows Why AI Rules Cannot Wait
The fight over free bank transfers is not only about money. It is also a lesson for the AI industry.
The Bangko Sentral ng Pilipinas is pushing banks and e-wallets to cut transfer fees. The rule is based on a simple idea: customers should not pay a large charge when the real cost of moving money is small. BPI and RCBC are leading the change. BPI has made many transfers to other banks and e-wallets free. RCBC has also removed many InstaPay fees, though limits apply.
This puts pressure on the rest of the market. Once customers see that free transfers are possible, they will ask why other firms still charge.
That question is now aimed at GCash, Maya, and other e-wallets. For years, these platforms grew by making digital payments easy. But they also earned from transfer fees, cash-in charges, cash-out charges, and other small costs. Those charges were easy to ignore because each one looked small. At scale, they became big business.
The same pattern is forming in AI. Many AI tools are now cheap or free. They help users write, search, study, code, and create images. But free tools still have a business model. A company may later earn from user data, ads, work tracking, automated scoring, or paid access to decisions.
The public must ask early: what is the real price of the service? That price may not always be money. It may be privacy, lost jobs, unfair ranking, false content, or decisions that no one can explain. The fintech case shows why regulation often comes late.
The gambling issue is a clear example. In 2025, regulators ordered e-wallets to remove direct links to online gambling services. The move came after public anger over addiction, debt, and damage to families. The order was needed. But it also exposed a hard truth. Some digital growth came from making risky behavior easier.
This should worry the AI sector. AI companies are also rewarded for growth, clicks, use, and engagement. That can lead to tools that spread false content, copy people’s work, target weak users, or keep people online for longer than is healthy. A fast-growing product is not always a good product. High adoption does not prove safety.
The new payment rules also create pressure for GCash and Maya to earn more from loans, insurance, investments, and other services. That shift may help them grow, but lending creates new risks. AI may soon be used to decide who gets a loan, how much they can borrow, and what rate they must pay.
That is where fintech and AI rules meet. An AI credit system may claim to be smart. But it can still be unfair. It may use poor data. It may punish people for where they live, what phone they use, or how they behave online. It may deny a loan without giving a clear reason.
That should not be allowed. People must know when AI affects a major decision. They must have a way to challenge it. Regulators must be able to test the system.
The impact on eGov is just as important. Cheaper payments can help citizens pay taxes, permits, fines, and other public charges online. They can also help government send aid, pensions, and benefits.
AI will likely be added to these services. It may answer questions, check forms, detect fraud, or guide people through public systems. But government AI must meet a higher standard than a private app. It must be fair, clear, safe, and open to review. It must also work for people who speak different languages, have weak internet access, or are not skilled with technology.
The main lesson is simple. We should not wait for AI harm to become a national scandal before we act. The gambling-link issue showed what happens when rules come after the damage. The transfer-fee issue showed what happens when digital services become too important to be left to private pricing alone.
AI is moving toward the same point. It is becoming infrastructure.
That means adoption must come with accountability, and innovation must come with rules.
About Me:
Dominic “Doc” Ligot is one of the leading voices in AI in the Philippines. Doc has been extensively cited in local and global media outlets including The Economist, Channel News Asia, South China Morning Post, Washington Post, and Agence France Presse. His award-winning work has been recognized and published by prestigious organizations such as NASA, Data.org, Digital Public Goods Alliance, the Group on Earth Observations (GEO), the United Nations Development Programme (UNDP), the World Health Organization (WHO), and UNICEF.
If you need guidance or training in maximizing AI for your career or business, reach out to Doc via https://docligot.com.
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