In this thesis we propose BankSealer, an effective online banking semisupervised and unsupervised fraud and anomaly detection framework, with the goals of automatically detecting frauds and anomalies in a real online banking dataset. For the realisation of this project, we collaborated with an an IT...
Fraud classification is challenging because of the severe class imbalance. In a fraud dataset, there are many more non-fraudulent transactions than fraudulent transactions. Typically, less than 1 percent of a dataset contains fraudulent transactions. If it's not addressed, this imbalance can cause a...
The experimental results, conducted on a real bank transaction dataset, show the advantage of HDF-CNN over the existing methods. 1. Introduction According to Cornell University Law School (CULS) [1], bank fraud is defined as "whoever knowingly executes, or attempts to execute, a scheme or ...
it exploited a linear loopy belief propagation algorithm to estimate the posterior probability distribution and predict the label of an account.Finally,it compared the proposed method with CIA and SybilRank on both synthetic dataset and real-world dataset.The results show that the proposed method ...
Use data cleansing and normalisation techniques to fix inconsistencies, redundancies, and errors in data to create a clean, reliable dataset for integration. Use a centralised data repository or data warehouse to consolidate and manage data from multiple sources. This creates a single source of truth...
This CaixaBank use case is focused on advanced analysis of bank transfers executed by employees on financial terminals to detect possible fraud, or any other potential anomalies that differ from the standard working procedure. The used dataset is composed of different attributes which record the diffe...
Further, to check for these elements, the data protection authority must ensure that the developer’s anonymisation techniques make it impossible to single out, link and infer information from an anonymised training dataset. The authority should factor in all reasonable means a person might take to...
settlement accounts (hereinafter to be referred as IMGF) for detecting the riskiness of gambling and fraud in bank personal settlement accounts, considering the industry characteristics such as high dimensionality, massive size and noise information complexity of the Bank of Beijing customer dataset [7...
To understand the temporal behavior and characteristics of the dataset and its elements, we n... M Gupta,G Jing,Y Sun,... - European Conference on Machine Learning & Knowledge Discovery in Databases 被引量: 55发表: 2012年 An Outlier Detection Model Based on Cross Datasets Comparison for ...
According to Bank of International Settlements, which keepsdata on CBDC projectsaround the world, in the latest available dataset from January of 2023 10 countries used conventional (database) ledgers in their implementations, 8 countries used DLTs, and 15 countries a combination of...