India's lending ecosystem has undergone a comprehensive digital transformation through strategic public-private partnerships and technological innovation. According to Mint, the evolution reflects systematic building of digital pathways for data and analytics, creating seamless credit decisions that were previously impossible through traditional paperwork. The foundation of this transformation is built on Aadhaar digital identity, extensive mobile payment infrastructure, and consent-based data sharing systems that have fundamentally changed how financial institutions operate. This digital foundation enables near-real-time credit decisions and easy access to products like buy-now-pay-later and instant personal loans via digital lending apps, representing a fundamental shift from the paper-based processes that once dominated the industry.
The Account Aggregator (AA) framework is fundamentally changing how lenders assess borrowers, replacing traditional paperwork with secure digital data sharing. According to reports from Mint, as of December 2025, 64 lenders had onboarded onto the Reserve Bank of India's (RBI) Unified Lending Interface, using more than 136 data services to assess borrowers beyond traditional credit scores. The network facilitated approximately ₹1.47 trillion of lending across 15 million loans between April and September 2025, with nearly one in 10 personal loans now processed through AA-enabled data sharing. As reported by Mint, lenders can now assess cash flows, income stability, spending patterns, and existing liabilities in real time, providing a comprehensive picture of borrower repayment capacity. The AA ecosystem ensures encrypted data transfers between financial information providers and authorised financial information users, enabling lenders to access trusted, contextual financial data without the need to repeatedly collect and submit documents.
The richer data access is particularly beneficial for self-employed borrowers, those with irregular income, and new credit users. According to Sachin Seth, regional managing director of CRIF India and South Asia, as reported by Mint, this enhanced data can translate into higher approval odds and better pricing, higher credit limits, or more tailored credit offers. The system enables lenders to track salary consistency, examine mutual fund holdings, and calculate debt-to-income ratios, providing a more comprehensive assessment than traditional credit scores. The AA ecosystem includes around 15 entities licensed as Account Aggregators that integrate data from nearly 170 Financial Information Providers (FIPs) and disseminate this information to over 800 Financial Information Users (FIUs). This interconnectedness of payment platforms, credit bureaus, and account aggregators facilitates secure, consent-driven financial data sharing, reducing duplication, improving transparency, and supporting more informed lending decisions.
The AA framework operates on consent-based data sharing, with each sharing instance requiring specific purpose-based approval. As reported by Mint, the data shared is limited to what users have linked and approved on AA apps, across categories including bank accounts, mutual funds, and insurance policies. However, Yatin Pednekar, co-founder of Mobicule Technologies, highlights a critical gap: "A real safeguard missing today is purpose limitation, meaning that data collected to assess your loan shouldn't quietly get reused for debt collection or marketing later." While lenders are legally forbidden from sharing data for these purposes, monitoring compliance remains challenging in practice. Rajat Deshpande of Finbox notes that customers grant consent primarily for convenience rather than complete understanding of data processing.
The RBI has released draft rules aimed at reducing hidden risks in AI-based lending, requiring lenders to explain automated decisions and hold bank boards accountable for AI-related issues. According to Mint, Sahamati proposed its own framework in June, introducing what Kiran Gopinath, chief innovation officer of Sahamati Labs, calls "confidential computing" environments - secure, neutral spaces where AI processes data without storage. Under this proposal, borrowers would receive processing receipts detailing every action performed on their data, enabling them to track how their information is processed. The framework would also empower borrowers to dispute rejections by tracing data processing trails, addressing current limitations where borrowers can request data summaries but not AI decision logic. These regulatory initiatives aim to strengthen the collaborative architecture that enables lenders of different sizes and business models to operate within a common framework, contributing to greater consistency across the financial sector.
Until regulatory frameworks are finalized, borrowers should utilize RBI-recognized lending apps, which provide data localization protections and limits on app access to contacts and photo galleries. As reported by Mint, once loans are repaid, borrowers can request data deletion, though this applies only when lenders have no further legal reason to retain information. Anshul Verma of SKV Law Offices advises borrowers to verify what data is requested and for how long, and to avoid broad or recurring access when one-time consent would suffice. Deshpande recommends checking data requirements and duration, and avoiding broad access when specific, time-limited permissions would be sufficient. The visible speed of digital lending rests on an invisible foundation of identity systems, payment networks, credit information infrastructure, and consent-based data sharing, with this infrastructure continuing to shape how efficiently credit flows through the economy.
