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@article{190667,
        author = {Ms. Revati Vilas Patil and Mr. Sarang Bhika Patil},
        title = {From Carts to Credits: Behavioral Approaches in Indian FinTech Lending},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {1111-1115},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190667},
        abstract = {The trending expansion of FinTech-driven digital lending platforms in India has significantly enhanced access to credit, particularly for new-to-credit and under banked customers. Despite this progress, accurate assessment of credit risk continues to remain a big challenge, as traditional bureau-based credit scoring models often fail to capture behavioural and transactional nuances of borrowers. In this context, FinTech firms are increasingly exploring alternative data sources to strengthen their risk assessment frameworks.
The present study attempts to analyze the relevance of e-commerce behavioural data as an alternative input for credit risk modelling in Indian FinTech lending platforms. Behavioural indicators such as order frequency, return-to-origin (RTO) rates, payment mode preference, refund behaviour, and transaction consistency are examined to identify their association with loan repayment outcomes. A data driven analytical approach, supported by exploratory data analysis and behavioural segmentation, is adopted to evaluate the predictive significance of these variables.
The findings shows that selected e-commerce behavioural signals exhibit a meaningful relationship with credit performance and can effectively complement traditional financial indicators during underwriting. The study further outlines key business and product-level implications, including improved on boarding risk filters, dynamic credit limit allocation, and reduction in early- stage defaults. By reviewing the practical application of alternative data, this research offers actionable insights for FinTech lenders seeking to balance financial inclusion with sustainable portfolio performance in the Indian digital lending ecosystem.},
        keywords = {FinTech Lending, Credit Risk Modeling, E-Commerce Behaviour, Alternative Data, Data Analytics.},
        month = {January},
        }