India’s retail lending market is on a rapid growth trajectory, expected to reach $1.3 trillion by 2030. This surge is fuelled by increasing disposable incomes, rising consumer aspirations, and the proliferation of fintech platforms enabling digital credit access.
India’s retail lending market growth, however, is accompanied by a rise in delinquencies and Non-Performing Assets (NPAs).
Unsecured personal loans and credit cards, while popular, pose higher repayment risks—particularly during economic slowdowns or inflationary pressures.
BFSI institutions face mounting challenges in maintaining profitability while managing credit risk.
Aggressive lending practices and limited borrower financial literacy have further contributed to repayment issues, intensifying the need for smarter recovery methods.
To address these issues, banks and lenders are increasingly adopting AI-powered collections strategies. AI enables intelligent segmentation by analyzing borrower profiles and prioritizing high-risk accounts for recovery efforts.
Through hyper-personalized outreach, AI tools tailor communication channels and messages to each borrower, boosting engagement and improving the likelihood of repayment while preserving customer goodwill.
Automation also streamlines collection workflows, handling repetitive tasks like reminders and follow-ups, thus reducing operational costs and allowing staff to focus on complex recovery cases.
AI-driven predictive analytics identifies early signs of default, giving lenders time to offer restructuring or assistance.
Overall, AI transforms collections into a more proactive, efficient, and customer-centric process, essential for sustaining growth in India’s booming retail lending sector.
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