One rapidly developing technology framework that is transforming lending in India is the India Lending Infrastructure, comprising APIs, Data Aggregators, and AI Models. It combines artificial intelligence (AI), account aggregators and application programming interfaces (APIs) to enhance accessibility, streamline processes, and promote financial inclusion.
Financial institutions, fintechs, and regulators are taking notice of this shift since the digital lending market in India is expected to expand at a compound annual growth rate (CAGR) of 36% between 2021 and 2026.
Overview of India’s Lending Infrastructure
Lending infrastructure APIs automate vital procedures, including client onboarding, credit evaluation, disbursement, and collections, by facilitating secure, real-time data exchange between lenders, borrowers, and third-party suppliers. This enables more individualized loan experiences, improves efficiency, and shortens processing times. By combining financial information from multiple sources, account aggregators provide borrowers with even more leverage, facilitating improved money management and informed borrowing decisions.
AI models enhance credit underwriting by combining traditional and alternative data, providing deeper insights into borrower risk profiles, particularly for individuals with limited credit histories. However, challenges remain, including potential biases in AI decision-making and the need for robust regulation. The Reserve Bank of India’s classification of AI lending models as high-risk underscores the importance of transparency and fairness.
Lending Infrastructure APIs
Lending infrastructure APIs are reshaping the financial services sector by enabling seamless communication between software systems involved in the lending process. These specialized Application Programming Interfaces streamline critical stages, such as customer onboarding, credit evaluation, loan disbursement, and collections, thereby driving operational efficiency and enhancing the borrower experience.
What Are Lending Infrastructure APIs?
APIs are tools designed to act as connectors between lenders, borrowers, and third-party services, including credit bureaus, identity verification systems, and payment gateways. APIs support real-time, secure data transactions by automating the entire loan process, from initial approval to generating loan agreements, disbursing funds, and managing the account in the future. This increased digitization enables faster loan processing, more accurate reporting, and ensures compliance.
By 2025, the standard digital loan onboarding process follows a streamlined, API-first sequence. This includes CKYC verification, Aadhaar eKYC with electronic signatures for agreements, retrieval of GST returns or licenses from DigiLocker, consent-based cash flow data sharing via Account Aggregators, and UPI-enabled disbursal with mandate setup. Each stage is fully driven by APIs, allowing lenders to provide credit that is fast, compliant, and frictionless at scale.
Key Components:
- Onboarding APIs – Simplify the onboarding process by gathering borrower information, preferred loan amounts, and repayment terms. Onboarding will take minutes instead of days.
- Credit Underwriting APIs – Pull data from credit bureaus and alternative sources to create accurate borrower profiles, supporting informed risk assessments.
- Loan Fulfilment APIs – Manage disbursement of funds, automate credit agreements, maintain accounts, and be upfront with borrowers about the loan process in an automated way.
- Loan Collection APIs – Automate the debiting of EMIs and sending of reminders, keep track of repayments in real time, and coordinate debt recovery on delinquent debts.
Importance in the Lending Ecosystem
The incorporation of lending infrastructure APIs is redefining the lending ecosystem. These APIs enhance operational efficiency by automating and streamlining various lending operations. They also improve customer satisfaction by increasing transparency and streamlining service delivery. Additionally, by automating these crucial steps in the loan process, they make it easier to comply with regulatory standards, like digital signatures and consent documents.
Data Aggregators
Regulated online systems, known as Account Aggregators (AAs) or Data Aggregators, streamline the management of financial data by combining data from multiple banks, insurers, mutual funds, and other financial institutions into a single interface. Without needing to log in to multiple accounts, this single view streamlines the process for individuals and businesses to manage their finances.
The Account Aggregator (AA) framework facilitates the regulated, consent-based sharing of financial data, including banking, GST, securities, and insurance, from Financial Information Providers (FIPs) to Financial Information Users (FIUs). This process is standardised by the Reserve Bank of India (RBI) and the Reserve Bank Information Technology Pvt Ltd (ReBIT), with stewardship by Sahamati. By the end of fiscal year 2025, this framework enabled the disbursement of ₹1.6 lakh crore in loans across 1.89 crore accounts, demonstrating its significant impact on credit access.
In 2025, the RBI took steps to formalise the governance of the ecosystem by inviting applications to recognise a self-regulatory organisation (SRO) for Account Aggregators. This move is a crucial step toward enhancing accountability and establishing standards within the sector.
Benefits of Data Aggregators
- Simplified Financial Management: By combining information from multiple accounts, AAs provide consumers with a comprehensive view of their financial situation. This holistic viewpoint supports better long-term goal planning, investment monitoring, spending tracking, and budgeting.
- Increased Efficiency: The time and effort required for financial analysis are reduced with rapid, centralized access to economic data. With precise and up-to-date insights, users can make more informed judgments.
- Simplified Access to Financial Products: Lenders and other institutions can expedite the application process by customizing loans, investments, and insurance products based on a user's financial profile.
Operational Framework:
Data aggregators are governed by laws that ensure the secure exchange of financial information with external service providers, provided that users grant their permission. Because financial institutions have access to a customer's aggregated financial data, consent-based data sharing enables a more personalised and individualised financial service offering, resulting in customised products and services.
Uses and Applications
Account aggregators are useful tools in the financial ecosystem because they may be used for both personal and company accounts. To provide a comprehensive perspective necessary for efficient financial management and informed strategic decision-making, these aggregators enable organisations to consolidate financial data from multiple sources.
Impact on UPI Comparisons and Credit Scores
A user's credit score is not directly affected by using an account aggregator. That being said, it can provide financial organisations with a more accurate picture of a client's economic situation, which may influence credit decisions.
The Unified Payments Interface (UPI) and account aggregators serve different purposes. UPI is mostly concerned with making payments and money transfers easier, whereas Account Aggregators focus on offering a consolidated view of financial data.
AI Models in Lending
The lending industry in India is undergoing a transformation driven by artificial intelligence (AI), which enables quicker, more precise, and customer-focused loan processing. AI helps lenders reduce turnaround times, minimise errors, and streamline operations throughout the lending lifecycle through automation, advanced analytics, and predictive modelling.
Loan Processing Automation
The use of artificial intelligence (AI), machine learning (ML), and automation technologies has improved efficiency in loan origination and verification. AI-driven systems can quickly verify applicant information against multiple databases, reducing the need for manual background checks. This means lenders such as NBFCs can assess applications for pre-qualified customers in under three minutes. Online application forms are accompanied by the automation of regular tasks, including document verification, fraud validation, and compliance checks, allowing human agents to focus on more complex cases.
Advanced Credit Underwriting
AI’s greatest impact has been in its role in credit underwriting. Traditional scoring systems, based on credit bureau data, are seldom updated and can only evaluate credit files. AI models can utilise alternative data sources to assess creditworthiness, including utility bill payments, telecom usage patterns, and actual purchases made through e-commerce and social media.
Thin-file customers would be permitted access to credit through other means than a formal credit channel. With predictive algorithms, AI is helping to increase loan approvals, decrease defaults, and improve customer satisfaction.
Continuous Model Optimisation
AI models are continually monitored and retrained to account for changes in borrower behaviour and economic conditions, thereby promoting consistent accuracy, regulatory compliance, and fairness in lending decisions.
AI models represent more than just efficiency—they are catalysts for expanding financial inclusion and transforming lending into a more data-driven, inclusive process.
Future Trends: Overview of Fintech Disruptions
India's fintech scene is expected to undergo significant changes by 2030, driven by several major disruptions that will overhaul the financial industry. The development of artificial intelligence (AI), decentralised finance (DeFi), and embedded finance, the incorporation of financial services into non-financial platforms, are noteworthy examples of these.
- AI-Powered Finance
The most anticipated trend is the increase of AI-powered finance, leading to hyper-personalized budgeting, lending and investing in products and services. This will be possible as machine learning algorithms can develop real-time financial behaviors based on their understanding of an individual's preferences, and in turn, develop their financial products and services. - Decentralised Finance (DeFi)
The next trend is the growth of DeFi, as more people are expected to bypass traditional banking systems for platforms based on lending, savings and asset management on the blockchain. Removing conventional banks from the process will likely democratize access to financial services and reduce reliance upon the existing economic system. - Embedded Finance
Embedded finance will become commonplace, a type of inter-application ecosystem where financial services are injected into multiple platforms, including e-commerce, mobility and gaming. This trend will enable users to access financial services, such as banking, through common applications that facilitate various financial transactions as part of their daily lives. - AI + Human Advisors
Furthermore, robo-advisors and human financial advisors are expected to combine in the future to create hybrid financial planning solutions. By combining the effectiveness of AI with the compassion and expertise of human advisors, this approach aims to deliver more intelligent and responsive financial advice.
Conclusion
By 2025, India’s lending market will only be successful if APIs, data aggregators, open credit protocols, and AI develop in a unified socio-technical stack. Lenders who operate this way will provide credit more quickly, fairly, and widely. Lenders who don’t operate in this way run the risks of becoming irrelevant in a faster, broader, and fairer connected financial ecosystem.