fraud detection

Zhuanzhuan Tech

Mar 20, 2025 · Backend Development

Implementing Geolocation‑Based Fraud Detection with Redis GEO Commands

This article outlines a fraud‑detection use case that leverages Redis GEO commands to compare user order addresses with known malicious locations, discusses technology choices among MySQL, Redis, and Elasticsearch, explains Redis’s Sorted‑Set and GeoHash implementation, and provides Java code examples for GEOADD, GEOPOS, GEODIST, and GEORADIUS.

GeoHashGeolocationRedis

0 likes · 9 min read

Implementing Geolocation‑Based Fraud Detection with Redis GEO Commands

DataFunSummit

Mar 18, 2025 · Artificial Intelligence

Application and Implementation of Multimodal Relational Networks in Financial Risk Control

This article presents the background, key technologies, system architecture, data processing pipeline, and practical use cases of multimodal relational networks for enhancing financial risk control, highlighting how integrating image, voice, text, and device data improves fraud detection, modeling, and operational efficiency.

AIfinancial technologyfraud detection

0 likes · 15 min read

Application and Implementation of Multimodal Relational Networks in Financial Risk Control

DataFunSummit

Feb 13, 2025 · Information Security

Building and Optimizing a Comprehensive Security System: Practices, Innovations, and Future Outlook

This article presents a detailed walkthrough of constructing a robust security architecture, covering single‑person security team strategies, risk perception and quantification, rapid incident response, automated detection, precise strike mechanisms, deterrence tactics, and forward‑looking plans for intelligent, data‑driven risk management.

automationfraud detectionincident response

0 likes · 21 min read

Building and Optimizing a Comprehensive Security System: Practices, Innovations, and Future Outlook

DataFunSummit

Feb 11, 2025 · Information Security

War‑Like Strategies for URL Anti‑Fraud: Threat Analysis, Detection Techniques, and Operational Intelligence

The article examines the growing threat of black‑market malicious websites, outlines a five‑part war‑themed framework for comprehensive opponent analysis, detection strategies across traffic, channel, content and relationship dimensions, and advanced detection models—including fingerprint, text, image, graph, and multimodal approaches—while highlighting the supporting operational and intelligence systems.

fraud detectioninformation securitymachine learning

0 likes · 14 min read

War‑Like Strategies for URL Anti‑Fraud: Threat Analysis, Detection Techniques, and Operational Intelligence

AntTech

Oct 26, 2024 · Artificial Intelligence

CCF Technology Achievement Awards Recognize Ant Group’s Advances in AI‑Driven Financial Risk Modeling and Edge Intelligence for Alipay

The 2024 CCF Technology Achievement Awards honored Ant Group’s two projects—complex behavior modeling for digital inclusive finance security and Alipay terminal intelligent technology—highlighting their AI‑driven risk control, edge inference innovations, extensive research output, and large‑scale real‑world deployments.

AlipayAnt GroupArtificial Intelligence

0 likes · 6 min read

CCF Technology Achievement Awards Recognize Ant Group’s Advances in AI‑Driven Financial Risk Modeling and Edge Intelligence for Alipay

DataFunTalk

Jul 27, 2024 · Information Security

Classification of Risk Control and Full-Scenario Anti-Cheat Strategies in the Internet

The article outlines how internet and financial risk control are categorized into anti‑cheat, anti‑fraud, and content security, describes full‑scenario cheating types, and presents a three‑step joint defense framework using perception, identification, and mitigation with feature‑based analysis.

Feature Engineeringanti-cheatfraud detection

0 likes · 7 min read

Classification of Risk Control and Full-Scenario Anti-Cheat Strategies in the Internet

AntTech

Jul 11, 2024 · Information Security

Enhancing Fraud Transaction Detection via Unlabeled Suspicious Records (GIANTESS Framework)

The paper presents GIANTESS, a novel semi‑supervised fraud detection framework that leverages online‑identified suspicious transactions to augment the feature space, generating pseudo‑labels for out‑of‑distribution samples and employing a hybrid loss to improve detection of covert fraudulent activities, achieving notable recall gains on real‑world datasets.

GIANTESSSemi-supervised Learningfraud detection

0 likes · 6 min read

Enhancing Fraud Transaction Detection via Unlabeled Suspicious Records (GIANTESS Framework)

Model Perspective

Jun 26, 2024 · Artificial Intelligence

Unlocking Fraud Detection: Build a Hidden Markov Model with Python

This article explains the fundamentals and mathematics of Hidden Markov Models, illustrates their core components and basic problems, and walks through a complete Python implementation for credit‑card fraud detection, including data preparation, model training, and evaluation.

Hidden Markov ModelPythonfraud detection

0 likes · 10 min read

Unlocking Fraud Detection: Build a Hidden Markov Model with Python

DataFunSummit

Mar 16, 2024 · Information Security

Building a Fraud Advertising Flow Risk‑Control System: Eight Key Elements and Practical Practices

This article shares practical experience from Shumei on constructing a fraud‑advertising flow risk‑control system, detailing eight essential elements, scenario analysis, black‑industry pathways, event design, strategy formulation, implementation methods, value demonstration, and a Q&A session for developers and product teams.

advertising securitybusiness strategyfraud detection

0 likes · 17 min read

Building a Fraud Advertising Flow Risk‑Control System: Eight Key Elements and Practical Practices

DataFunSummit

Mar 1, 2024 · Artificial Intelligence

Applying Artificial Intelligence to Cross‑Border Risk Control: Architecture, Practices, and Insights

This article presents how AI techniques are applied to cross‑border risk control, covering the company background, a layered intelligent risk‑prevention system, detailed transaction and marketing fraud scenarios, model architectures such as sequence embeddings, CNN/LSTM/Transformer, and graph neural networks, and concludes with a Q&A on challenges and future directions.

AIGraph Neural Networkscross-border

0 likes · 19 min read

Applying Artificial Intelligence to Cross‑Border Risk Control: Architecture, Practices, and Insights

Model Perspective

Dec 30, 2023 · Fundamentals

Why Does Benford’s Law Reveal Hidden Fraud? A Deep Dive into Data

This article explains Benford’s Law—the first‑digit distribution rule—its discovery, mathematical basis, and wide‑range applications, from exposing Enron’s accounting fraud to analyzing 2022 Forbes billionaire wealth, age, and regional data, highlighting both its strengths and limitations.

Benford's LawForbes Billionairesdata analysis

0 likes · 9 min read

Why Does Benford’s Law Reveal Hidden Fraud? A Deep Dive into Data

AntTech

Dec 13, 2023 · Artificial Intelligence

IEEE ICDM 2023 Graph Learning Challenge: Community Detection and Fraud Group Mining

The IEEE ICDM 2023 Graph Learning Challenge, co‑hosted by Ant Group and Zhejiang University, showcased deep graph learning approaches for community detection and fraud‑group mining, highlighting the winning team's Risk‑DCRN method and emphasizing the importance of pretrained models in large‑scale network analysis.

ICDMcommunity-detectiondeep learning

0 likes · 5 min read

IEEE ICDM 2023 Graph Learning Challenge: Community Detection and Fraud Group Mining

Zhuanzhuan Tech

Nov 15, 2023 · Information Security

Association Graph for Fraud Detection: Theory, Architecture, and Applications

This article explains the concept of association graphs, their foundation in graph theory, storage architectures, noise‑reduction techniques, and practical applications such as feature mining, coloring, backend visualization, data analysis, and monitoring for fraud detection in risk control systems.

Data Modelingassociation graphfraud detection

0 likes · 14 min read

Association Graph for Fraud Detection: Theory, Architecture, and Applications

DataFunSummit

Aug 22, 2023 · Artificial Intelligence

Applying Artificial Intelligence to Cross‑Border Risk Control: Practices and Insights

This article presents how artificial intelligence is applied to cross‑border risk control, covering the company background, intelligent risk‑prevention architecture, transaction and marketing fraud scenarios, model design, data challenges, and practical Q&A insights for overseas fraud mitigation.

AIcross-borderfraud detection

0 likes · 18 min read

Applying Artificial Intelligence to Cross‑Border Risk Control: Practices and Insights

DataFunSummit

Aug 12, 2023 · Information Security

Design and Exploration of Mobile Game Anti‑Fraud Systems

This article examines the mobile game black‑market ecosystem, outlines common fraud patterns such as script cheats, account trading, and illegal recharge, and presents a comprehensive anti‑fraud architecture that combines real‑time risk assessment, offline analysis, and adaptive mitigation strategies for game developers and operators.

Algorithmanti-cheatfraud detection

0 likes · 21 min read

Design and Exploration of Mobile Game Anti‑Fraud Systems

DataFunSummit

Aug 11, 2023 · Artificial Intelligence

Application of Knowledge Graphs in Risk Control at Wing Payment

This presentation details how Wing Payment leverages a large‑scale, multimodal knowledge graph and AI techniques—including computer vision, unsupervised and supervised learning, federated learning, and graph neural networks—to detect and mitigate fraud across payment, e‑commerce, and credit scenarios, while outlining system architecture, algorithmic approaches, case studies, and future research directions.

Artificial Intelligencefinancial servicesfraud detection

0 likes · 17 min read

Application of Knowledge Graphs in Risk Control at Wing Payment

DataFunTalk

Jul 28, 2023 · Artificial Intelligence

Insurance Anti‑Fraud Risk Control System: Architecture, Core Capabilities, and Case Studies

This article presents Taiping Jinke's end‑to‑end insurance anti‑fraud risk control framework, detailing industry pain points, core AI‑driven capabilities, platform blueprint, specific car and health insurance fraud engines, and real‑world case studies that illustrate how big‑data, machine‑learning and knowledge‑graph techniques are integrated into business processes.

Artificial IntelligenceInsurancefraud detection

0 likes · 16 min read

Insurance Anti‑Fraud Risk Control System: Architecture, Core Capabilities, and Case Studies

AntTech

Jun 27, 2023 · Artificial Intelligence

Fanglue: An Interactive System for Decision Rule Crafting in Fraud Detection

Fanglue is an interactive, web‑based rule‑development platform that integrates expert domain knowledge with distributed AI algorithms to efficiently generate and evaluate decision rules for anti‑fraud scenarios, leveraging Ray for real‑time processing and achieving VLDB‑2023 acceptance.

AIRayVLDB2023

0 likes · 10 min read

Fanglue: An Interactive System for Decision Rule Crafting in Fraud Detection

Efficient Ops

Jun 26, 2023 · Artificial Intelligence

How Multimodal AI Is Revolutionizing Credit Card Fraud Detection

Amid tightening financial regulations, ICBC's software team proposes a multimodal AI anti‑fraud framework that combines image, video, and structured data to detect deep‑fake, mask, and forged‑document attacks, enriches verification with cross‑modal cues, and outlines future expansion to text and speech modalities.

AIcomputer visioncredit card

0 likes · 7 min read

How Multimodal AI Is Revolutionizing Credit Card Fraud Detection

Architect

May 31, 2023 · Artificial Intelligence

Applying Graph Neural Networks for Anti‑Cheat in Activity Scenarios

This article presents how graph neural network models such as GCN and SCGCN are employed to detect and recall cheating groups in user‑invitation (master‑apprentice) activity scenarios, addressing the lack of relational features and low sample purity, and demonstrates significant recall improvements through multi‑graph fusion techniques.

GCNSCGCNactivity modeling

0 likes · 12 min read

Applying Graph Neural Networks for Anti‑Cheat in Activity Scenarios