MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115354 A) filed by Sri Eshwar College Of Engineering on September 24, 2026, for Ai-Driven Next-Generation Intelligent Banking System For Automated Loan Allocation Using Circular Fermatean Fuzzy Pattern Recognition.
Inventors include Dr. R. Vennila; Dr. A. Revathy; Dr. C. Gokila; and Ms. N. Akiladevi.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: ABSTRACT This invention is about a decision-support system and method that helps with automated loan allocation and recommendations in banking and finance. It is especially useful when the information about borrowers and the conditions for loan eligibility are not clear not precise or not complete. The system uses a framework called Circular Fermatean Fuzzy (CFF) to handle and compare information without turning it into exact numbers. In this system important details about borrowers, like information, credit history and repayment ability are shown using Fermatean Fuzzy Numbers (FFNs) and then turned into Circular Fermatean Fuzzy Numbers (CFFNs). The CFF method considers membership, -membership and circular uncertainty, which makes it a good way to represent uncertain evaluations of borrowers. The system also has a loan-profile database where the requirements and features of loan products are shown using CFF data. A method that looks for similarities is used to compare the borrowers details with the requirements of loan products. This method considers the membership, non-membership and circular uncertainty of each part. The similarity values for each part are added up to get a score for each loan product. Based on these scores the system ranks the loan products. Suggests the one with the highest score as the best option. The system can also show a list of possible loan products along with their similarity scores. This helps bank staff or borrowers compare options and understand how the recommendation was made. This invention offers a way to handle uncertainty when matching borrowers with the loan products. It helps make loan decisions more consistent, clear, efficient and easy to explain. By keeping the uncertain information during the whole process the system solves problems that come with older methods that usually use fixed or single values. The system can be used as a computer-based tool that is fully automated or partly automated. It can be connected to systems that handle loans, customer information and financial decisions. This helps with checking if someone is eligible, for a loan choosing the product giving the loan and suggesting personalized options.
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