COMPARISON OF HOME LOANS SCHEME OF DIFFERENT BANKS

The rapid urbanization and evolving financial aspirations of individuals in emerging and developed economies have significantly increased the demand for home loans. As a result, banks—both public and private—have introduced a wide variety of home loan schemes tailored to different customer segments, ranging from salaried employees to self-employed individuals, NRIs, and senior citizens. This study provides a comprehensive comparative analysis of home loan offerings by major financial institutions, including State Bank of India (SBI), HDFC Bank, ICICI Bank, Punjab National Bank (PNB), Bank of Baroda, Axis Bank, and select non-banking financial companies (NBFCs) such as LIC Housing Finance and Bajaj Finserve. The objective is to evaluate the interest rate structures, repayment tenures, processing fees, eligibility conditions, prepayment penalties, and digital onboarding processes associated with each bank’s home loan scheme. Furthermore, the study integrates customer feedback, service quality, loan disbursement efficiency, and grievance redressal mechanisms into the comparative framework. In the post-pandemic financial landscape, banks have increasingly adopted technology-driven solutions such as AIpowered credit scoring, paperless documentation, mobile-based KYC, and automated EMI calculators to improve loan processing efficiency and customer experience. To offer a holistic and accurate evaluation, the study utilizes both primary data (surveys from 250+ borrowers and bank officers) and secondary data (official websites, RBI circulars, bank brochures, interest trackers, and consumer complaint forums). Additionally, the research incorporates machine learning tools such as clustering algorithms to classify customer preferences and regression analysis to examine how variables like tenure and applicant income influence interest rates across banks. Key findings reveal significant differences in loan-to-value (LTV) ratios, subsidy integration under PMAY (Pradhan Mantri Awas Yojana), and floating vs fixed interest offerings, which can drastically affect the overall cost of borrowing. Public sector banks generally offer lower interest rates and higher tenure flexibility, while private banks often provide faster disbursal and more customized digital experiences, albeit at higher costs. NBFCs, though attractive in terms of relaxed eligibility, may have steeper hidden charges and limited post-loan service support. The study underscores the importance of financial literacy and personalized loan comparison tools, especially for first-time borrowers, and recommends the integration of AI-based loan recommendation engines to aid customers in selecting optimal financing options based on their profiles. The research also advocates for greater regulatory standardization in home loan terms to reduce customer confusion and promote transparency in the retail credit ecosystem. This comparative study is intended to serve as a vital resource for policy makers, banking professionals, fintech developers, and home buyers, aiming to enhance customer-centric loan offerings and promote responsible lending in the housing finance sector.

Authors

Publication Details

Journal
Scientific Digest Journal of Applied Engineering
Published
2025-06-24
DOI
https://doi.org/10.70864/joae.2025.v13.i6.pp221-230
Primary Topic
Islamic Finance and Banking Studies
Type
article
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0.00
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article

COMPARISON OF HOME LOANS SCHEME OF DIFFERENT BANKS

R. Anusha, CH Dharmender, M.Pavani
Scientific Digest Journal of Applied Engineering
Islamic Finance and Banking Studies
article

COMPARISON OF HOME LOANS SCHEME OF DIFFERENT BANKS

R. Anusha, CH Dharmender, M.Pavani
article en

Abstract

The rapid urbanization and evolving financial aspirations of individuals in emerging and developed economies have significantly increased the demand for home loans. As a result, banks—both public and private—have introduced a wide variety of home loan schemes tailored to different customer segments, ranging from salaried employees to self-employed individuals, NRIs, and senior citizens. This study provides a comprehensive comparative analysis of home loan offerings by major financial institutions, including State Bank of India (SBI), HDFC Bank, ICICI Bank, Punjab National Bank (PNB), Bank of Baroda, Axis Bank, and select non-banking financial companies (NBFCs) such as LIC Housing Finance and Bajaj Finserve. The objective is to evaluate the interest rate structures, repayment tenures, processing fees, eligibility conditions, prepayment penalties, and digital onboarding processes associated with each bank’s home loan scheme. Furthermore, the study integrates customer feedback, service quality, loan disbursement efficiency, and grievance redressal mechanisms into the comparative framework. In the post-pandemic financial landscape, banks have increasingly adopted technology-driven solutions such as AIpowered credit scoring, paperless documentation, mobile-based KYC, and automated EMI calculators to improve loan processing efficiency and customer experience. To offer a holistic and accurate evaluation, the study utilizes both primary data (surveys from 250+ borrowers and bank officers) and secondary data (official websites, RBI circulars, bank brochures, interest trackers, and consumer complaint forums). Additionally, the research incorporates machine learning tools such as clustering algorithms to classify customer preferences and regression analysis to examine how variables like tenure and applicant income influence interest rates across banks. Key findings reveal significant differences in loan-to-value (LTV) ratios, subsidy integration under PMAY (Pradhan Mantri Awas Yojana), and floating vs fixed interest offerings, which can drastically affect the overall cost of borrowing. Public sector banks generally offer lower interest rates and higher tenure flexibility, while private banks often provide faster disbursal and more customized digital experiences, albeit at higher costs. NBFCs, though attractive in terms of relaxed eligibility, may have steeper hidden charges and limited post-loan service support. The study underscores the importance of financial literacy and personalized loan comparison tools, especially for first-time borrowers, and recommends the integration of AI-based loan recommendation engines to aid customers in selecting optimal financing options based on their profiles. The research also advocates for greater regulatory standardization in home loan terms to reduce customer confusion and promote transparency in the retail credit ecosystem. This comparative study is intended to serve as a vital resource for policy makers, banking professionals, fintech developers, and home buyers, aiming to enhance customer-centric loan offerings and promote responsible lending in the housing finance sector.

Scientific Digest Journal of Applied EngineeringVol. 13(6)
Openalex Percentile: Top 67%
Islamic Finance and Banking Studies
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