Credit card fraud detection using graph algorithms | |
| Author | Yampali, Vamshi Kanth Reddy |
| Call Number | AIT RSPR no.IM-23-08 |
| Subject(s) | Credit card fraud--Prevention Credit cards--Security measures Fraud investigation Graph algorithms Machine learning |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information Management |
| Publisher | Asian Institute of Technology |
| Abstract | Fraud is a significant issue for companies of all sizes. Graph databases provide a novel approach to detecting fraud that can be used to identify complicated fraud rings and pat terns. This study investigates the use of the graph database platform Neo4j for detecting fraud. The study has three main objectives, to study behavioral fraud in credit card fraud, Using Cypher query language to identify fraud rings. And to predict fraudulent trans actions using a machine learning model with using graph features and to compare with a baseline model. |
| Year | 2023 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Chutiporn Anutariya |
| Examination Committee(s) | Vatcharaporn Esichaikul;Mozumder, Chitrini |
| Scholarship Donor(s) | AIT Scholarships |
| Degree | Research studies project report (M. Eng.) - Asian Institute of Technology, 2023 |