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[HTML][HTML] Financial fraud: a review of anomaly detection techniques and recent advances
With the rise of technology and the continued economic growth evident in modern society,
acts of fraud have become much more prevalent in the financial industry, costing institutions …
acts of fraud have become much more prevalent in the financial industry, costing institutions …
[HTML][HTML] Fraud detection: A systematic literature review of graph-based anomaly detection approaches
Graph-based anomaly detection (GBAD) approaches are among the most popular
techniques used to analyze connectivity patterns in communication networks and identify …
techniques used to analyze connectivity patterns in communication networks and identify …
Financial cybercrime: A comprehensive survey of deep learning approaches to tackle the evolving financial crime landscape
Machine Learning and Deep Learning methods are widely adopted across financial
domains to support trading activities, mobile banking, payments, and making customer credit …
domains to support trading activities, mobile banking, payments, and making customer credit …
Generating synthetic data in finance: opportunities, challenges and pitfalls
Financial services generate a huge volume of data that is extremely complex and varied.
These datasets are often stored in silos within organisations for various reasons, including …
These datasets are often stored in silos within organisations for various reasons, including …
[KNYGA][B] Machine learning and AI for risk management
We explore how machine learning and artificial intelligence (AI) solutions are transforming
risk management. A non-technical overview is first given of the main machine learning and …
risk management. A non-technical overview is first given of the main machine learning and …
A survey of community detection methods in multilayer networks
X Huang, D Chen, T Ren, D Wang - Data Mining and Knowledge …, 2021 - Springer
Community detection is one of the most popular researches in a variety of complex systems,
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …
Detecting money laundering transactions with machine learning
Purpose The purpose of this paper is to develop, describe and validate a machine learning
model for prioritising which financial transactions should be manually investigated for …
model for prioritising which financial transactions should be manually investigated for …
Stgsn—a spatial–temporal graph neural network framework for time-evolving social networks
S Min, Z Gao, J Peng, L Wang, K Qin, B Fang - Knowledge-Based Systems, 2021 - Elsevier
Abstract Social Network Analysis (SNA) has been a popular field of research since the early
1990s. Law enforcement agencies have been utilizing it as a tool for intelligence gathering …
1990s. Law enforcement agencies have been utilizing it as a tool for intelligence gathering …
Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review
Money laundering has been affecting the global economy for many years. Large sums of
money are laundered every year, posing a threat to the global economy and its security …
money are laundered every year, posing a threat to the global economy and its security …
KYC optimization using distributed ledger technology
The know-your-customer (KYC) due diligence process is outdated and generates costs of up
to USD 500 million per year per bank. The authors propose a new system, based on …
to USD 500 million per year per bank. The authors propose a new system, based on …