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RBI Governor Shaktikanta Das on Wednesday said that based on the encouraging response received from several jurisdictions, the apex bank is now focusing on making "UPI and RuPay truly global". 

"The deployment of UPI-like infrastructure in foreign jurisdictions, facilitating QR code-based payment acceptance through UPI apps at international merchant locations, and interlinking UPI with Fast Payment Systems (FPS) of other countries for cross-border remittances are on top of our agenda," Das said in his address at the Global Fintech Fest here. 

He pointed out that notable progress in this direction has already been made in countries like Bhutan, Nepal, Sri Lanka, Singapore, the UAE, Mauritius, Namibia, Peru, France and a few other countries.

"These endeavours underscore collaborative efforts for the adoption of India’s initiatives across the globe. I would like to compliment the NPCI and my colleagues in the Reserve Bank for what has been achieved so far, but we must resolve to do more in this national endeavour," the RBI Governor said. 

He also said that India’s CBDC (Central Bank Digital Currency), which is in the pilot stage, is another example of possible international cooperation. "We are now utilising features like programmability to provide credit or government assistance to landless tenant farmers and carbon credits to farmers through CBDC. While we have successfully demonstrated the interoperability of CBDC with retail fast payment systems like UPI, we continue to gain from our experimentation on off-line solutions. As we make progress, we would be happy to cooperate with other nations in their CBDC efforts," he remarked. 

The RBI Governor further stated that looking towards the future of India's financial landscape, the integration of cutting-edge technologies promises transformative advancements across various facets of our life. 

Artificial Intelligence and Machine Learning (AI/ML) are poised to revolutionise financial services in unprecedented ways. AI algorithms are already being deployed for fraud detection. Machine learning models are increasingly being employed in credit scoring, leveraging predictive analytics to assess creditworthiness, and expand access to credit. As AI and ML capabilities continue to evolve, their potential applications in regulatory compliance, investment advisory services, and algorithmic trading are expected to further redefine the financial landscape, he added. 

At the same time, Das underscored the need to fully understand the risks posed by AI and facilitate calibrated and responsible adoption. Players in the financial sector, Central banks and governments should facilitate the development of trustworthy AI, keeping in mind the concerns surrounding data privacy, explainability, accountability and transparency, he stressed.