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This study provides a comparative analysis of the evolution of lending systems in India and the United States from the 1990s to the present, highlighting how historical legacies, regulatory philosophies, and technological transitions have shaped distinct credit ecosystems. India’s lending system transformed from a state-directed, highly regulated structure into a liberalized and increasingly digital framework driven by the Narasimham Committee reforms, asset-recovery legislation such as SARFAESI and the IBC, and large-scale financial inclusion initiatives. In contrast, the United States followed a market-led trajectory characterized by deregulatory reforms, rapid financial innovation, and subsequent systemic crises—most notably the 2008 subprime collapse—that prompted substantial re-regulation through the Dodd-Frank Act. The paper demonstrates how cultural factors—India’s historically debt-averse environment versus the U.S.’s entrenched pro-credit culture—influence credit access, loan-to-deposit ratios, and risk-taking behaviour. It further examines the rise of digital and alternative lending in both countries, showing that India treats fintech credit as a tool for financial inclusion while the U.S. prioritizes consumer protection and algorithmic fairness. Despite divergent paths, both systems are converging on technology-driven underwriting, non-bank intermediation, and data-governed credit models. The paper concludes by outlining future policy challenges—ranging from CBDCs and instant payments to AI governance, platform finance, and macro-financial risks—that will shape the next phase of lending-system evolution in both economies.
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"A Comparative Study of Lending Systems’ Evolution in India and the USA", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.a6-a18, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512002.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator