MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202641071658 A) filed by Malla Reddy Engineering College For Women Autonomous; Malla Reddy University; Malla Reddy Mr Deemed To Be University; and Malla Reddy Vishwavidyapeeth Deemed To Be University on June 09, 2026, for Enhanced Ai-Based Credit Underwriting Framework With Document Verification And Chat Assistance.
Inventors include Dr. Y. Madhaveelatha; Ms Contractor Gajala Akhtar; Mr. Obulesh Kallubhavi; Mr. Raviprakash Perike; Mr. L Vijay Kumar; Dr. Naga Chandrika Vaidya; Dr. Shaik Javed Parvez; and Dr. Syed Mohd Faisal.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: Credit underwriting plays a crucial role in financial decision-making and risk assessment, yet traditional evaluation methods often suffer from delays, manual errors, and lack of scalability. This project focuses on developing an enhanced AI-based credit underwriting framework that integrates automated document verification, loan eligibility prediction, and intelligent chat assistance to streamline lending processes and improve accuracy. The proposed system uses applicant-submitted documents such as ID proofs, income statements, and bank records as input, and applies machine learning and OCR-based extraction techniques to validate authenticity and extract key financial parameters. A trained AI model analyzes these parameters to predict creditworthiness and classify applicants into categories such as low-risk, moderate- risk, and high-risk borrowers. Deep learning–based OCR modules are used to enhance document clarity through preprocessing steps including noise reduction, text enhancement, and standardization. After risk classification, the system provides personalized recommendations such as optimal loan amount, EMI planning, and documentation guidance. The inclusion of an AI-powered chat assistant further supports applicants by answering queries, guiding uploads, and explaining eligibility criteria in real time. The proposed approach aims to assist financial institutions in faster, more transparent decision-making while helping applicants understand their credit standing. By combining automated document verification, predictive underwriting, and interactive assistance, the system enhances efficiency, reduces fraud risk, and expands access to credit, particularly in regions with limited financial advisory resources.
Disclaimer: Curated by HT Syndication.
