How regulators can help make AI work for India’s digital payments

India’s digital payments story is one of the few that can be called a global success. Among other achievements, we have constructed a real-time, low-cost payments system that works with other systems and has become a model for the rest of the globe. Artificial intelligence (AI) will be a key part of the next phase of this journey. It will help avoid fraud, make payments more personal, improve operational efficiency, give people access to credit and make the payments value chain more resilient.

But technology alone isn’t enough for AI to really work in India’s digital payments system. The rules that govern the use of AI in payments will have a big impact on how safe and reliable payments end up becoming.

Regulators in India today have a difficult but important job: they need to protect trust on a large scale while also allowing innovation to happen quickly.

Why AI is different and regulation is important

AI is very distinct from other kinds of financial technologies that have come before it. AI models learn, change and make judgments based on probabilities, which is different from rules-based systems. This brings in new hazards that previous regulatory methods weren’t made to deal with, like lack of transparency, bias, gaps in explainability and systemic dependencies.

In payments, where trust, speed and no room for error are all important, these dangers are even worse. An AI system that isn’t well-managed can:

– Block a lot of real transactions by mistake
– Have a bigger effect on some categories of users
– Become easy to manipulate by enemies
– Make people lose faith in the whole payment system

This is exactly why legislation shouldn’t be seen as a limit to AI, but as a way to make responsible use of it possible.

From making rules to taking care of the ecosystem

Indian regulators need to stop making just rules and start taking care of the whole ecosystem if they want AI to reach its full potential in digital payments. This necessitates a transformation across four essential aspects.

1) Regulation based on principles, not rules

Static rulebooks can’t keep up with AI innovation. Regulations that are too strict could stop innovation or move it into murky areas. Instead, policymakers should base AI governance on explicit, enforceable rules, like:

– Responsibility for results driven by AI
– Transparency and explainability in relation to risk
– Fairness and no discrimination
– Privacy via design and data minimisation

This method lets regulated businesses come up with new ideas while still making sure they are in line with what is best for the public.

2) Regulatory differentiation based on risk

Not all AI use cases in payments have the same amount of risk. AI that is utilised for backend reconciliation or predictive maintenance is very different from AI that doesn’t accept transactions or flags fraud or affects how people spend their money.

So, regulatory monitoring should be risk-tiered, with more scrutiny for AI systems that have a direct impact on customer rights, access or financial results. This keeps the focus on the most important things without making it harder for low-risk innovation.

3) Everyone in the value chain is responsible for their part

AI in payments is not usually owned by just one company. Banks, fintechs, technology providers and platforms should commonly share models, data, infrastructure and decision-making layers.

Regulators can play a key role by making it clear who is responsible for what in AI supply chains while setting expectations for audits, monitoring and model governance. Encouraging ecosystem participants to be clear about their contracts and how they work will help avoid gaps and makes the system stronger as a whole.

4) Regulatory sandboxes that grow, not stop

India was one of the first countries to use regulatory sandboxes. The next step must be to focus on speed to scale. AI sandboxes should provide access to real-world transaction volumes in a regulated way, allow quick changes with feedback from regulators and make it easy to see how to go from pilot to production deployment.

Sandboxes should help people accept new ideas, not be places where people can experiment without any consequences.

The real currency is trust

Trust is what makes digital payments work. AI can make that trust stronger by cutting down on fraud, making transactions and processes more reliable, and enhancing user experience. But it can also break trust if the results are not what people expect or are unjust.

This is a one-of-a-kind chance for Indian regulators. India can show the world how public digital infrastructure, private innovation and smart regulation can all function together on a large scale by setting global standards for responsible AI in payments.

Regulators and the industry can’t decide what the future of AI in payments will be. It needs ongoing conversation, learning from each other and working together to create governance structures.

The best thing regulators can do is not just allow or limit AI, but also make it such that trustworthy AI is the default choice. AI will do more than just make digital payments smarter if India gets this balance right. For a billion people and more, it will make them safer, fairer and inclusive.

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