By Jyothirlatha B, Chief Technology Officer, Godrej Capital
The Indian lending landscape is at a turning point. With a diverse borrower base, from salaried professionals in metros to micro-entrepreneurs in small towns, expectations from lenders have never been higher. Customers want speed, personalisation and trust. Meeting these demands requires more than digitisation; it requires intelligence. Artificial Intelligence (AI) is now at the heart of this transformation.
AI: Moving Beyond Automation
In lending, AI is not just about speeding up workflows. It is about reimagining how we understand and serve customers. Traditional credit assessment relies on limited, static data points. AI allows financial institutions to analyse vast streams of structured and unstructured data, including transaction histories, income flows, mobile usage and alternate signals like utility bill payments, in real time.
For a country where millions remain outside the formal credit system, this is game-changing. A small business owner with consistent digital transactions or a vendor with regular UPI payments may lack a credit score, but AI-powered models can build a credible financial profile from real behaviour. This opens the door to credit inclusion at scale.
Hyper-Personalised Lending Journeys
Generative AI (GenAI) is taking personalisation a step further. By building “Customer 360” profiles with insights from service interactions, transaction history and feedback, lenders can offer tailored loan options, anticipate needs and resolve issues in the customer’s preferred language. AI-powered translation and dynamic document generation make complex financial documents accessible, breaking language barriers and making onboarding seamless.
Financial institutions, including NBFCs like ours, are experimenting with multilingual chatbots, pre-filled application forms and predictive nudges that guide borrowers towards healthy repayment habits. These hyper-personalised journeys are becoming a key differentiator in a competitive market.
Transforming Risk Assessment and Fraud Prevention
Risk management is shifting from reactive to proactive. AI-powered systems can detect anomalies in real time, flagging suspicious transactions before they escalate.
In credit underwriting, machine learning (ML) models along with AI now combine traditional bureau data with alternate signals such as geolocation analytics, market insights and behavioural trends to generate accurate, dynamic risk scores along with insights. Real-time integration with credit bureaus, government databases and banking APIs enables instant verification and CAM generations reducing fraud and improving accuracy. This helps lenders intervene before defaults occur.
Responsible AI: The Cornerstone of Trust
The Reserve Bank of India projects AI could add up to $438 billion to India’s GDP by 2029–30. With this opportunity comes the responsibility to use it wisely. Transparency, fairness and explainability must underpin every algorithm.
Many AI models, especially deep learning systems, operate as “black boxes.” For lenders, explainability is essential both to comply with regulations and to maintain customer trust. Regular algorithm audits, bias checks and adherence to anti-discrimination laws ensure equal opportunity for all applicants.
Cybersecurity and data protection are equally critical. Encryption, role-based access controls and guardrails protect customer data. Regular security audits and vulnerability assessments guard against threats like spoofing and data tampering. For NBFCs like ours, strong governance frameworks and continuous monitoring are as important as innovation itself.
Beyond Lending Decisions: Building Financial Resilience
AI’s role in lending extends well beyond approvals and collections. Predictive analytics can identify customers at risk of financial stress and offer flexible repayment options. Intelligent nudges can promote financial literacy, budgeting and better credit behaviour.
By integrating AI into every stage, from lead generation and onboarding to servicing, collections and post-loan engagement, lenders can create a 360-degree ecosystem that is efficient, inclusive and customer-centric.
The Road Ahead: Agentic AI and Open Finance
The next leap will come from agentic AI, autonomous systems capable of managing end-to-end lending journeys. Imagine an AI that can not only process an application but also conduct verification, sanction the loan and initiate disbursal without human intervention. This will free people to focus on complex cases and customer relationships.
Open banking and Account Aggregator frameworks will amplify AI’s capabilities, enabling richer data-driven decisions while giving customers greater control over their financial information.
Laying the Foundations for Scalable AI
While the promise of AI is transformative, success depends on building the right foundations. The first step is always to establish a strong, unified data layer that enables accurate and real-time insights. Equally important is adopting a platform approach backed by a strong governance structure and clear frameworks.
Human-in-loop models will remain critical before moving towards full autonomy. This ensures accountability, transparency and responsible decision-making. Many POCs in the industry do not progress to production because the right use cases are not prioritised. Selecting business-impacting use cases is key to realising value.
At an organisational level, investing in AI literacy is non-negotiable. Initiatives such as setting up an AI Academy can equip employees with the skills to design, deploy and monitor intelligent systems responsibly. A formal AI roadmap, coupled with a governance committee, provides long-term direction and oversight.
Most importantly, AI is not a silver bullet. Creating real business impact requires a holistic approach starting with process optimsation, applying automation, and then layering intelligence through AI/ML, supported by continuous training and skill development. Force-fitting AI where it does not belong risks minimal or no impact.
Conclusion
AI is no longer an optional tool for lenders; it is the accelerator for the next era of financial services. By blending data intelligence with human empathy, financial institutions can design lending experiences that are not just faster, but fairer and more inclusive.
For a country where access to credit is a gateway to opportunity, the responsibility is clear: build AI systems that learn, adapt and respect every borrower’s individuality. Done right, AI can transform lending into a force for financial empowerment across India.