Essays about: "fraud detection"
Showing result 1 - 5 of 63 essays containing the words fraud detection.
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1. Detecting Fraudulent User Behaviour : A Study of User Behaviour and Machine Learning in Fraud Detection
University essay from Uppsala universitet/Analys och partiella differentialekvationerAbstract : This study aims to create a Machine Learning model and investigate its performance of detecting fraudulent user behaviour on an e-commerce platform. The user data was analysed to identify and extract critical features distinguishing regular users from fraudulent users. READ MORE
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2. Credit Card Fraud Detection by Nearest Neighbor Algorithms
University essay from Göteborgs universitet/Institutionen för matematiska vetenskaperAbstract : As the usage of internet banking and online purchases have increased dramatically in today’s world, the risk of fraudulent activities and the number of fraud cases are increasing day by day. The most frequent type of bank fraud in recent years is credit card fraud which leads to huge financial losses on a global level. READ MORE
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3. Detection of insurance fraud using NLP and ML
University essay from Lunds universitet/Matematisk statistikAbstract : Machine-Learning can sometimes see things we as humans can not. In this thesis we evaluated three different Natural Language Procces-techniques: BERT, word2vec and linguistic analysis (UDPipe), on their performance in detecting insurance fraud based on transcribed audio from phone calls (referred to as audio data) and written text (referred to as text-form data), related to insurance claims. READ MORE
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4. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis
University essay from KTH/Matematik (Avd.)Abstract : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. READ MORE
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5. Performance comparison of data mining algorithms for imbalanced and high-dimensional data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Artificial intelligence techniques, such as artificial neural networks, random forests, or support vector machines, have been used to address a variety of problems in numerous industries. However, in many cases, models have to deal with issues such as imbalanced data or high multi-dimensionality. READ MORE