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AI assisted fraud detection and prevention system
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Abstract
Information
Inventors
Applicants
Specification
Documents
ORDINARY APPLICATION
Published
Filed on 13 November 2024
Abstract
This patent describes a system and method for real-time fraud detection and prevention, leveraging artificial intelligence (AI) and machine learning algorithms to analyze transactional and behavioral data. It integrates various data sources to identify fraudulent activities across domains, such as financial transactions, e-commerce, and identity verification. The system mitigates fraud risks by promptly flagging suspicious transactions and recommending preventive measures. A system and method for detecting and preventing fraudulent activities using artificial intelligence (AI) is disclosed. The system utilizes machine learning algorithms to analyze data from various sources, including transactional data, user behavior data, and external data feeds. The system extracts relevant features from the data, trains machine learning models using labeled datasets, and scores transactions in real-time to identify potentially fraudulent activity. The system also includes a decision engine that uses the risk score to make decisions on whether to approve, reject, or flag a transaction for further review. The system continuously updates and improves the machine learning models using feedback from users, analysts, and other stakeholders. The system provides improved accuracy, real-time detection, and adaptability to new types of fraud.
Patent Information
Application ID | 202441087504 |
Invention Field | COMPUTER SCIENCE |
Date of Application | 13/11/2024 |
Publication Number | 47/2024 |
Inventors
Name | Address | Country | Nationality |
---|---|---|---|
Dr A.C. SANTHA SHEELA, Sathyabama Institute of Science & Technology | Associate Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Ms.J.DEEPA, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology | Assistant Professor, Department of Information, Technology, School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, India | India | India |
Dr.S.SHALINI, Sathyabama Institute of Science & Technology | Assistant Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Mrs.G.SANGEETHA, PERI Institute of Technology | Assistant Professor, Department of Computer Science and Engineering, PERI Institute of Technology, Chennai, India | India | India |
Mr.MUTHU V, Panimalar Engineering College | Assistant Professor, Department of AI&ML, Panimalar Engineering College, Chennai, India | India | India |
Ms.KEERTHANA P, Sathyabama Institute of Science & Technology | Assistant Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Dr. PRABU M, Amrita Vishwa Vidyapeetham | Assistant Professor (Sl. Gr.), Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai, 601103 | India | India |
Dr.G.ANBU SELVI, Sathyabama Institute of Science & Technology | Assistant Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Dr.N.S.USHA, Sathyabama Institute of Science & Technology | Associate Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai- 600119, India | India | India |
Dr.E.Murali, Sathyabama Institute of Science & Technology | Associate Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai- 600119, India | India | India |
Applicants
Name | Address | Country | Nationality |
---|---|---|---|
Dr A.C. SANTHA SHEELA, Sathyabama Institute of Science & Technology | Associate Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Ms.J.DEEPA, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology | Assistant Professor, Department of Information, Technology, School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, India | India | India |
Dr.S.SHALINI, Sathyabama Institute of Science & Technology | Assistant Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Mrs.G.SANGEETHA, PERI Institute of Technology | Assistant Professor, Department of Computer Science and Engineering, PERI Institute of Technology, Chennai, India | India | India |
Mr.MUTHU V, Panimalar Engineering College | Assistant Professor, Department of AI&ML, Panimalar Engineering College, Chennai, India | India | India |
Ms.KEERTHANA P, Sathyabama Institute of Science & Technology | Assistant Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Dr. PRABU M, Amrita Vishwa Vidyapeetham | Assistant Professor (Sl. Gr.), Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai, 601103 | India | India |
Dr.G.ANBU SELVI, Sathyabama Institute of Science & Technology | Assistant Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai - 600119, India | India | India |
Dr.N.S.USHA, Sathyabama Institute of Science & Technology | Associate Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai- 600119, India | India | India |
Dr.E.Murali, Sathyabama Institute of Science & Technology | Associate Professor, Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science & Technology, Chennai- 600119, India | India | India |
Specification
Description:This patent describes a system and method for real-time fraud detection and prevention, leveraging artificial intelligence (AI) and machine learning algorithms to analyze transactional and behavioral data. It integrates various data sources to identify fraudulent activities across domains, such as financial transactions, e-commerce, and identity verification. The system mitigates fraud risks by promptly flagging suspicious transactions and recommending preventive measures. A system and method for detecting and preventing fraudulent activities using artificial intelligence (AI) is disclosed. The system utilizes machine learning algorithms to analyze data from various sources, including transactional data, user behavior data, and external data feeds. The system extracts relevant features from the data, trains machine learning models using labeled datasets, and scores transactions in real-time to identify potentially fraudulent activity. The system also includes a decision engine that uses the risk score to make decisions on whether to approve, reject, or flag a transaction for further review. The system continuously updates and improves the machine learning models using feedback from users, analysts, and other stakeholders. The system provides improved accuracy, real-time detection, and adaptability to new types of fraud. , C , Claims:1. An artificial intelligence-assisted fraud detection and prevention system, comprising:
a. a data ingestion module for collecting and processing data from various sources;
b. a feature engineering module for extracting relevant features from the ingested data;
c. a machine learning module for analyzing the extracted features and identifying patterns indicative of fraudulent activity;
d. a model training module for training and updating the machine learning models using labeled datasets;
e. a real-time scoring module for scoring transactions in real-time using the trained machine learning models;
f. a decision engine module for making decisions on whether to approve, reject, or flag a transaction for further review; and
g. a feedback loop module for collecting feedback from users, analysts, and other stakeholders to continuously update and improve the machine learning models.
2. The system of claim 1, wherein the machine learning module utilizes supervised and unsupervised learning, deep learning, and natural language processing algorithms.
3. The system of claim 2, wherein the decision engine module uses a risk score generated by the real-time scoring module to make decisions on whether to approve, reject, or flag a transaction for further review.
Documents
Name | Date |
---|---|
202441087504-COMPLETE SPECIFICATION [13-11-2024(online)].pdf | 13/11/2024 |
202441087504-DECLARATION OF INVENTORSHIP (FORM 5) [13-11-2024(online)].pdf | 13/11/2024 |
202441087504-DRAWINGS [13-11-2024(online)].pdf | 13/11/2024 |
202441087504-FORM 1 [13-11-2024(online)].pdf | 13/11/2024 |
202441087504-FORM-9 [13-11-2024(online)].pdf | 13/11/2024 |
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