Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{192283,
author = {Vedant Mohadikar and Bhavni Singh and Ziyan Sheikh and Mardav Jain},
title = {Dynamic Pricing & Risk-Based Loan Offers},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {9},
pages = {2270-2276},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=192283},
abstract = {This paper presents a student-oriented, implementable framework for Dynamic Pricing and Risk-Based Loan Offers aimed at digital lenders and fintech platforms. The approach fuses borrower-level credit risk assessment with market- aware pricing and constrained optimization to produce individualized loan terms in near real time. We expand on data curation and feature engineering, hybrid risk modeling (scorecards + gradient-boosted trees), acceptance-elasticity pricing, constrained optimization, and operational deployment notes. Simulated experiments demonstrate improved net interest margin (NIM) and acceptance rates while keeping portfolio PD within predefined limits. Emphasis is placed on explainability, fairness monitoring, and iterative feedback loops for safe adaptation in production environments.},
keywords = {Dynamic Pricing, Risk-Based Lending, Credit Scoring, Machine Learning, Optimization, Explainable AI, Fin- Tech},
month = {February},
}
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