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Updated: July 06, 2025 07:48
At 2:14 a.m., a Jaipur home decor businessperson requests a working capital loan. Her credit score? A decent 680. A red flag six years ago. But today's lending is not just about calculating numbers—it reads between the lines. With machine learning, her GST payments, export patterns, and seasonal inventory spikes are tracked in real time. The outcome? A custom-made loan offer, not a rejection letter.
Transformation Highlights
AI presently relies on borrower intent and credibility based on behavioral patterns rather than credit scores
Account Aggregator frameworks enable secure, opt-in data sharing for faster, richer insights
GenAI solutions generate open, compliant credit, compliance, and sales decision justifications
Human lenders are complemented—not replaced—by AI, with empathy at the forefront of lending
Beyond Automation
The first wave of digitization was about automating the mundane steps—technologists' jargon for the happy paths
But then comes complexity, and automation cannot be enough
Augmented intelligence steps in to handle nuance, context, and exceptions with sensitivity and empathy
One of India's largest public sector banks used this approach to distribute over ₹35,000 crore in four years in 15 digital loan products
Behavioral Intelligence in Action
Traditional models often exclude new-to-credit clients and MSMEs
AI now analyzes cash flow patterns, invoice cycles, and supplier relationships to build a more nuanced credit profile
Every payment becomes a signal—read not just for risk, but for opportunity
This evolution is especially significant in developing economies, where business activity is high but credit information is low
The Road Ahead
The future of lending is agentic autonomy: systems not only analyzing but acting with situational awareness AI will more and more perform as a co-pilot—alerting underwriters, triggering red flags, and modifying financial products in real time
The goal is not just faster loans, but fairer ones—where information enables more intelligent and empathetic decisions to be made
Sources: MSN India, Economic Times, Enova International, Forbes Tech Council
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