MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641097841 A) filed by Dr. Vadithe Mallikarjuna Naik on August 13, 2026, for Ai-Based Context-Aware Fraud Prevention, Bc/Aeps Agent Risk Assessment And Secure Digital Financial.
Inventor includes Dr. Vadithe Mallikarjuna Naik.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: An artificial intelligence-based context-aware fraud-prevention system is disclosed for assisted digital financial transactions in tribal, remote and low-connectivity environments. The system creates a user-specific Digital Financial Trust Profile and analyses transaction behaviour, device, location, velocity, beneficiary, authentication and BC/AePS agent activity. A dedicated agent-risk engine generates an agent-specific risk score, which is combined with customer and transaction indicators to produce a transaction-specific Combined Fraud Risk Score. Based on the score, the system dynamically authorizes, re-verifies, holds or blocks a transaction and may provide multilingual voice confirmation. Edge processing enables selected fraud assessment during network disruption, while confirmed transaction outcomes update subsequent fraud-detection parameters. INote:TDetailredFckscriliiiion;ICtraffnkif-11•ind ETG 1--F16-: 1041rawhigs are attached- separately as part of the complete specification An artificial intelligence-based context-aware fraud prevention and secure digital financial transaction system is disclosed for assisted, remote, rural, tribal, and low-connectivity financial environments. The system establishes a Digital Financial Trust Profile for a user and analyses transaction behavior, device characteristics, location, transaction velocity, beneficiary information, authentication patterns, and assisted banking activity. A BC/AePS Agent Risk Engine evaluates an agent using transaction volume, withdrawal values, biometric failures, transaction reversals, post-DBT withdrawal activity, shared- device usage, complaints, geographic anomalies, and historical fraud information. Customer and agent risk indicators are processed by an artificial intelligence engine to generate a combined transaction-specific fraud-risk score. Based on the score, an adaptive authentication engine may authorize the transaction, request additional authentication, initiate multilingual voice or biometric reverification, temporarily hold the transaction, or block the transaction. An edge-processing module enables selected fraud-risk assessment during limited network connectivity. Confirmed genuine and fraudulent outcomes are used to update subsequent fraud-detection parameters. P
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