ARTIFICIAL INTELLIGENCE-BASED FRAUD DETECTION SYSTEM

Abstract

The present invention relates to an Artificial Intelligence-based Fraud Detection System designed to detect and prevent fraudulent activities in digital transactions. The system includes a data collection module for gathering transaction-related and user behavior data from multiple sources, a feature extraction module for processing and generating relevant features, and a machine learning module that applies a trained model to classify transactions as legitimate or fraudulent. A fraud detection module issues real-time alerts and initiates actions such as blocking transactions or triggering additional verification. The system further includes a feedback mechanism that updates the machine learning model based on feedback from fraud detection results, enabling continuous improvement in fraud detection accuracy and the adaptation to new and evolving fraud patterns. The invention provides an efficient, scalable, and adaptive solution for real-time fraud detection across various industries, including financial serv

Specification

Description:The embodiments of the present invention generally relates to a system and method for detecting fraud using artificial intelligence (AI) and machine learning (ML) technologies. More specifically, it pertains to a fraud detection system that analyzes transaction and user data from various sources, applies machine learning models for detecting fraudulent activities, and adapts over time through continuous learning. The invention can be applied to various domains such as financial services, e-commerce, healthcare, and identity management to enhance the security and reliability of digital transactions.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present discl , Claims:1. An Artificial Intelligence-based fraud detection system for detecting fraudulent activities in digital transactions, comprising:
a data collection module configured to gather transaction-related data, user behavior data, and external data sources;
a feature extraction module configured to process the collected data and generate features relevant for fraud detection;
a machine learning module configured to apply a trained machine learning model to the extracted features to classify transactions as either legitimate or fraudulent;
a fraud detection module configured to issue alerts and take action based on the classification results;
a feedback mechanism configured to update the machine learning model with new data based on the outcome of fraud detection, enabling continuous improvement of fraud detection accuracy.

2. The system of claim 1, wherein the data collection module is further configured to collect data from multiple sources, including transaction logs, user profiles, geolocation data, and external

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