Actual Implementation Of CBDC Interoperability Would Pose Challenges: RBI Governor
Programming the end use for purchase is important, Das said.
The actual implementation of cross border digital currency interoperability would pose challenges and may involve certain trade-offs, Reserve Bank of India Governor Shaktikanta Das said on Monday.
"Technical barriers may be surmounted by using common (international) technical standards. Further, the governance structure or management framework for long-term sustainability would also need to be finalised," Das said at the RBI@90 Global Conference on 'Digital Public Infrastructure and Emerging Technologies' in Bengaluru.
This has come as the central bank has been creating awareness about central bank digital currency and its potential to underpin the payment systems of future, both for domestic as well as cross-border payments.
Speaking about the programmability feature of CBDC, which could serve as a key enabler for financial inclusion, Das said that programming the end use for purchase is important. For example, programming the end use for purchase of agricultural inputs can give the required comfort to banks and establish the identity of a farmer through the end use of funds being disbursed.
Other new use cases aimed at testing features such as anonymity and offline availability are also proposed to be rolled out gradually, he said.
Das also emphasised that there should not be any rush to roll out system-wide CBDC before one acquires a comprehensive understanding of its impact on users, on monetary policy, on the financial system and on the economy.
"Such understanding would emerge from generation of user data in pilots. Actual introduction of CBDC can be phased in gradually," he said.
\The emergence of artificial intelligence in financial services brings in significant opportunities for all stakeholders, Das said. However, rising concerns around data privacy must ensure that financial institutions make AI models explainable, such as why certain results were produced.
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Das has asked stakeholders to carefully examine the authenticity of data being used in training the models, possibility of biases and concerns of data privacy.
While AI promises to make processes simpler, efficient, financial institutions must ensure careful adoption of AI in critical decision-making segments such as loan sanctioning.
"While AI can definitely assist the process, the institutions using them should have proper understanding of the models and ensure accountability of the outcomes," Das said.
Further, financial institutions should also clearly outline the liabilities. On the other hand, central banks and governments should foster the development of trustworthy AI, keeping data privacy, explainability, accountability and transparency at its core, he said.
