Intellectual Property India Publishes Patent Application for Researching The Role Of Artificial Intelligence In Credit Risk Assessment And Customer Support

MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641094936 A) filed by Dr. P. Rasool Begum; Mrs. Sudharani. M; Dr. Viral Atulkumar Chauhan; Mrs. Rajalakshmi K.; Mrs. R. Jeya Malar; Dr. Y. Moydheen Sha; Dr. A. Senthil Raghavan; Dr. D. Vijayalakshmi; Dr. V. Kannan; Prof. Dr. Parul Goyal; Adhithya Vishagan. C. K.; and Akshaya Shivani. C. K on August 05, 2026, for Researching The Role Of Artificial Intelligence In Credit Risk Assessment And Customer Support.

Inventors include Dr. P. Rasool Begum; Mrs. Sudharani. M; Dr. Viral Atulkumar Chauhan; Mrs. Rajalakshmi K.; Mrs. R. Jeya Malar; Dr. Y. Moydheen Sha; Dr. A. Senthil Raghavan; Dr. D. Vijayalakshmi; Dr. V. Kannan; Prof. Dr. Parul Goyal; Adhithya Vishagan. C. K.; and Akshaya Shivani. C. K.

The application for the patent was published on August 14, 2026, under issue no. 33/2026.

Abstract: ABSTRACT RESEARCHING THE ROLE OF ARTIFICIAL INTELLIGENCE IN CREDIT RISK ASSESSMENT AND CUSTOMER SUPPORT The proposed innovation introduces an Artificial Intelligence-Based Credit Risk Assessment and Customer Support System (AI-CRACS) that enhances financial decision-making and customer service through intelligent automation and predictive analytics. The framework integrates Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Big Data Analytics, Cloud Computing, and Blockchain Technology to evaluate customer creditworthiness, detect financial risks, and provide automated customer support. Unlike traditional banking systems that rely on manual credit evaluation and rule-based customer service, the proposed system continuously analyzes customer financial behavior, transaction history, repayment patterns, and credit scores to generate accurate risk predictions. AI-powered virtual assistants provide instant customer support, loan status updates, complaint handling, and personalized financial guidance. The proposed framework reduces loan defaults, minimizes fraud, improves operational efficiency, enhances customer satisfaction, and supports intelligent lending decisions. The system is suitable for banks, financial institutions, digital lending platforms, insurance companies, and fintech organizations.

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