MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202621022878 A) filed by Ritesh Kumar Verma, Bhopal, Madhya Pradesh, on Feb. 26, for 'a data-driven model for assessing credit risk of small and medium enterprises (smes) in india using financial, behavioral, and macroeconomic indicators.'
Inventor(s) include Ritesh Kumar Verma.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a computer-implemented system and method for assessing the credit risk of Small and Medium Enterprises (SMEs) in India for predicting probability of default and evaluating borrower willingness to repay. The invention provides a structured, multi-layered risk assessment framework that integrates financial, behavioral, business, demographic, collateral, and organizational indicators into a unified predictive architecture. The system comprises: (i) a data acquisition module configured to collect validated enterprise-level risk indicators; (ii) a variable classification and transformation engine configured to process and reduce multidimensional inputs into statistically significant risk components using dimensionality reduction techniques; (iii) a predictive analytics engine configured to generate a probability-based credit risk score using discriminant analysis, regression-based modeling, and neural network architectures; and (iv) a validation module configured to evaluate model robustness and classification accuracy across datasets. The invention enables automated classification of SME accounts into performing and non-performing categories and produces a quantified risk score for lending decision support. The model demonstrates high predictive accuracy and operational reliability and is adaptable for deployment within banking systems, non-banking financial institutions, and digital credit platforms. The invention enhances credit appraisal efficiency, improves early risk detection, and enables structured, data-driven lending decisions within the SME sector."
Disclaimer: Curated by HT Syndication.
