Page 41 - Banking Finance August 2025

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These AI-driven credit models are not only expanding ac- The Future of Credit Scoring and Alterna-
cess to credit but also reducing lending costs and fraud risks
for financial institutions. tive Lending in India
India's credit ecosystem is undergoing rapid transformation,
Regulatory Developments Challenges and driven by fintech innovation, regulatory advancements, and
Initiatives: growing digital adoption. The future of credit scoring and
alternative lending will be defined by deeper financial in-
As innovations in credit scoring continue to evolve, regula- clusion, greater reliance on technology, and a robust regu-
tory frameworks must keep pace ensuring consumer pro-
latory framework to ensure responsible lending.
tection, data security, and responsible lending practices.
RBI Guidelines on Digital Lending and Data Privacy:
The Reserve Bank of India (RBI) has introduced new Future Trends in Alternative Credit Lend-
regulations for digital lending, emphasizing transpar- ing:
ency, fair lending practices, and borrower rights. The AI, Blockchain, and Alternative Credit Models: AI will
guidelines mandate that all loan disbursals and repay- continue to refine credit risk assessment, while
ments must be executed directly between the borrower
blockchain technology could introduce secure, tamper-
and the regulated entity, reducing the risk of preda-
proof credit histories. Alternative credit scoring will
tory lending practices.
incorporate biometric data, psychometric testing, and
Potential Risks: Data Security, Algorithmic Bias, and real-time transaction monitoring to create more inclu-
Consumer Protection Concerns: sive financial profiles.
o Data Security: With the increasing use of personal India as a Global Leader in Fintech-Driven Credit So-
financial data, concerns around data breaches and lutions: With its booming fintech ecosystem, govern-
data misuse are growing. Fintech companies must
ment support, and large unbanked population, India is
comply with strict data protection measures.
poised to set global benchmarks in alternative lending.
o Algorithmic Bias: AI models can sometimes inherit With a conducive environment for Fintech, we may
biases based on the data they are trained on, lead- witness exporting of digital credit models to emerging
ing to discriminatory lending decisions. Addressing markets worldwide.
these biases is crucial to ensuring fair credit access.
o Consumer Protection: Many borrowers may not Conclusion
fully understand how AI-driven credit scoring
Credit scoring and alternative lending have emerged as
works. There is a need for greater transparency
transformative forces in India's financial inclusion journey.
and consumer education to prevent exploitation.
Traditional credit assessment methods often excluded large
Need for Balance between Innovation and Regula- segments of the population, but advancements in fintech,
tory Oversight: While regulatory intervention is nec- AI-driven credit models, and the use of alternative data
essary to protect borrowers, excessive restrictions could have helped bridge this gap. By leveraging mobile transac-
stifle innovation in fintech lending. A balanced approach tions, utility payments, and behavioral analytics, lenders can
is required to encourage responsible lending while al- now access creditworthiness beyond conventional metrics,
lowing new technologies to flourish. enabling first-time borrowers, gig workers, and MSMEs to

The Role of Government and Public Sector Initia- access credit.
tives: Recognizing the importance of financial inclusion,
the Indian government has launched several initiatives By embracing innovation while ensuring regulated lending
like the Pradhan Mantri Mudra Yojna, Stand Up India, practices, India has the potential to become a global leader
PM SVANidhi etc. to support credit expansion. Govern- in financial inclusion, paving the way for a more equitable
ment initiatives have accelerated credit access and economic future.
strengthened India's financial inclusion framework and
these initiatives vastly employ alternative credit scor- References:
ing models to assess the borrowers. Various Sources.

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