The Reserve Bank of India (RBI) will commence the pilot for a Public Tech Platform for Frictionless Credit on August 17, 2023.
During the pilot, the platform will focus on products such as Kisan Credit Card loans up to Rs 1.6 lakh per borrower, Dairy Loans, loans to Micro, Small and Medium Enterprises (MSME) without collateral, Personal loans and Home loans through participating banks, the RBI said in a statement.
The platform is expected to enable linkage with services such as Aadhaar e-KYC, Aadhaar e-signing, account aggregation by Account Aggregators (AAs), land records from onboarded State Governments (Madhya Pradesh, Tamil Nadu, Karnataka, Uttar Pradesh, and Maharashtra). The platform will enable linkage with Satellite data, Permanent Account Number (PAN) Validation, Transliteration, Aadhaar e-signing, account aggregation by Account Aggregators (AAs), milk pouring data from select dairy co-operatives, house/property search data, and so on.
The Platform is being developed by Reserve Bank Innovation Hub (RBIH), a wholly owned subsidiary of the RBI.
With rapid progress in digitalisation, India has embraced the concept of digital public infrastructure. This encourages banks, Non-Banking Financial Companies (NBFCs), Financial Technology (FinTech) companies, and start-ups to create and provide innovative solutions in payments, credit, and other financial activities.
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For digital credit delivery, the data required for credit appraisal are available with different entities like Central and State governments, account aggregators, banks, credit information companies, digital identity authorities, and so on. However, they are in separate systems, creating a hindrance in frictionless, the RBI added.
The end-to-end digital platform will have an open architecture, open Application Programming Interfaces (APIs) and standards, to which all financial sector players can connect seamlessly in a 'plug and play' model.
The Platform will be rolled out in a calibrated fashion, both in terms of access to information providers and use cases. It is expected to bring about efficiency in the lending process in terms of reduction of costs, quicker disbursement, and scalability.