CA Manish Gugliya
Quick Summary
1. Introduction: Shift from Traditional to AI-Based Lending in India The loan approval system in India has changed significantly in recent years. Earlier, banks mainly focused on collateral, personal relationships, and manual assessment while approving business loans. However, with the rise of Arti
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FAQ :
AI has made the loan approval system in India more data-driven and automated. Instead of relying on collateral and manual assessment, AI analyzes multiple financial data points like ITR, GST returns, and bank statements for faster and more accurate eligibility decisions.
AI-based lending heavily relies on financial data (ITR, GST returns, financial statements), banking data (bank statements, cash flow trends, EMI behavior), and alternative data (utility payments, digital transactions) to assess creditworthiness.
CAs are crucial in structuring financial data, ensuring accuracy and consistency between reports like GST and ITR, advising businesses on financial health, and managing documentation and compliance for loan applications.
Benefits include faster processing times, reduced NPAs through better risk assessment, improved transparency, cost efficiency for lenders, and increased financial inclusion for MSMEs and small businesses.
Challenges include data inconsistency issues (e.g., GST-ITR mismatch), poor banking discipline, and difficulties in proving financial strength due to informal transactions, which can lead to loan rejection.
Data consistency between GST, ITR, and bank statements is crucial because AI systems detect mismatches as high rejection risks. Accurate and aligned data is essential for improving loan approval chances.
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