risk control | BestHub

Alimama Tech

May 14, 2025 · Artificial Intelligence

Deep Research‑Driven Risk Root‑Cause Analysis with Domain Graph Constraints for Large‑Scale Advertising Traffic

This article presents a large‑scale advertising risk‑control solution that combines deep‑research paradigms, domain‑graph constraints, and large language models to enable explainable, responsible, and high‑precision fraud detection, detailing system architecture, challenges, demo workflow, and future directions.

AIDeep Researchadvertising fraud

0 likes · 11 min read

Deep Research‑Driven Risk Root‑Cause Analysis with Domain Graph Constraints for Large‑Scale Advertising Traffic

Sohu Tech Products

May 7, 2025 · Backend Development

Design and Implementation of a Scalable Lottery Activity Platform

The article describes how the FoxFriend team built a scalable, configurable lottery‑activity platform that replaces manual feed‑based draws with a modular micro‑service architecture, featuring a flexible prize‑tier data model, pre‑occupied inventory buckets, multi‑tenant isolation, high‑concurrency stock deduction, user risk controls, accurate probability handling, and a roadmap toward AI‑driven optimization.

Backend DevelopmentDistributed Locklottery system

0 likes · 25 min read

Design and Implementation of a Scalable Lottery Activity Platform

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

Jan 30, 2025 · Databases

Mature Practices for Building Risk‑Control Knowledge Graphs on NebulaGraph and Leveraging Large Language Models

This article explains how NebulaGraph’s large‑scale graph database can be used to construct real‑time risk‑control knowledge graphs, describes practical applications such as community detection and path analysis, and explores how large language models enhance graph queries through Text‑to‑GQL, agents, exploration chains, and semi‑structured knowledge extraction.

AILLMNebulaGraph

0 likes · 11 min read

Mature Practices for Building Risk‑Control Knowledge Graphs on NebulaGraph and Leveraging Large Language Models

DataFunSummit

Jan 17, 2025 · Databases

Graph Database Applications and Architectures in DataFun Knowledge Map 3.0

The DataFun Knowledge Map 3.0’s graph database module, presented by Ant Group expert Cui Anqi, outlines how graph databases enhance complex analysis through risk‑control architectures, user‑relationship recommendation, data‑governance, a new graph‑based data management system, and the GraphRAG framework, while also offering a free download link.

AIBig DataData Governance

0 likes · 3 min read

Graph Database Applications and Architectures in DataFun Knowledge Map 3.0

Tencent Cloud Developer

Jan 14, 2025 · Information Security

Can Database Signatures Prevent Tampering? An Analysis of Financial Risk Controls

The article revisits the debate on tampering with WeChat balances, explaining that joint database signatures can detect but not stop alterations, that risk‑control checks and code safeguards block unauthorized withdrawals, that identity verification prevents cross‑account transfers, and that a layered, real‑time monitoring system is essential for robust fund protection.

SignatureWeChatdatabase security

0 likes · 6 min read

Can Database Signatures Prevent Tampering? An Analysis of Financial Risk Controls

DataFunSummit

Nov 27, 2024 · Artificial Intelligence

Applying Large Language Models in Data Management and Risk Control at Ping An One Wallet

This presentation details how Ping An One Wallet leverages large language models across five key areas—current application status, data management, risk control, technical architecture, and a Q&A session—highlighting strategies such as vectorized rule storage, prompt engineering, RAG enhancements, and workflow agents to improve efficiency and accuracy in data governance and fraud detection.

AI architectureData Governancelarge language models

0 likes · 16 min read

Applying Large Language Models in Data Management and Risk Control at Ping An One Wallet

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.

anti-cheatfeature engineeringfraud detection

0 likes · 7 min read

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

DataFunSummit

Jul 25, 2024 · Artificial Intelligence

LOGIN: Large‑Model‑Assisted Graph Neural Networks for User Behavior Risk Control

This article presents the latest advances from the Chinese Academy of Sciences in graph machine learning for user behavior risk control, introducing the LOGIN framework that leverages large language models as consultants to iteratively enhance GNN training, and demonstrates its effectiveness through extensive experiments on homogeneous and heterogeneous graph benchmarks.

Graph Neural Networkslarge language modelsmachine learning

0 likes · 14 min read

LOGIN: Large‑Model‑Assisted Graph Neural Networks for User Behavior Risk Control

iQIYI Technical Product Team

Jul 5, 2024 · Big Data

RiskFactor: An Integrated Real‑Time and Offline Feature Platform for Risk Control

RiskFactor unifies iQIYI’s legacy real‑time and offline feature platforms onto Opal’s DAG‑plus‑SQL engine, accelerating feature production fifteen‑fold, cutting latency from hours to minutes, streamlining development, lowering costs, and delivering more reliable, versioned risk‑control capabilities against sophisticated online threats.

Big DataDAGReal-time Streaming

0 likes · 14 min read

RiskFactor: An Integrated Real‑Time and Offline Feature Platform for Risk Control

Architecture Digest

Jun 18, 2024 · Backend Development

Design and Implementation of a Business Risk‑Control Component Using Redis, Lua, and Kotlin

This article explains why a custom business risk‑control module is needed, outlines the required features, and provides a complete Kotlin‑based implementation that uses Redis + Lua scripts for daily and hourly counting, as well as a Spring annotation for seamless integration.

AnnotationKotlinRedis

0 likes · 9 min read

Design and Implementation of a Business Risk‑Control Component Using Redis, Lua, and Kotlin

DataFunTalk

Jun 13, 2024 · Artificial Intelligence

A/B Testing and Model Grayscale in Credit Risk Control: Concepts, Requirements, and Integrated Solutions

This article explains how A/B testing and model grayscale are applied in credit risk control, discusses the specific requirements for effective testing, compares upstream and risk‑system traffic splitting methods, and proposes an integrated all‑in‑one solution to simplify feature engineering, model evaluation, and deployment.

A/B testingcredit riskfeature engineering

0 likes · 5 min read

A/B Testing and Model Grayscale in Credit Risk Control: Concepts, Requirements, and Integrated Solutions

DataFunTalk

Jun 11, 2024 · Artificial Intelligence

Intelligent Risk Control: Concepts, Challenges, and Integrated Operational Architecture for Banking

This article explores the concept of intelligent risk control in banking, detailing its AI‑driven architecture, current challenges such as external data costs and model‑deployment friction, and proposes an integrated operational framework that leverages big data, knowledge graphs, and MLOps to enhance risk detection and decision‑making.

Artificial IntelligenceBig DataMLOps

0 likes · 14 min read

Intelligent Risk Control: Concepts, Challenges, and Integrated Operational Architecture for Banking

DataFunSummit

Jun 7, 2024 · Artificial Intelligence

Understanding Feature Engineering for Risk Control Systems and Building an Easy-to-Use Feature Platform

Feature engineering, the process of creating input variables for machine learning models, is crucial for banking risk control; this article explains the concepts of features, variables, and metrics, outlines challenges in real‑time feature pipelines, and proposes a practical architecture and best practices for building an efficient, low‑code feature platform.

feature engineeringmachine learningplatform design

0 likes · 10 min read

Understanding Feature Engineering for Risk Control Systems and Building an Easy-to-Use Feature Platform

DataFunTalk

Jun 4, 2024 · Artificial Intelligence

Building an Integrated Intelligent Risk Control System for Banking

The article explores the concept, challenges, and future directions of intelligent banking risk control, emphasizing data integration, AI-driven modeling, feature engineering, MLOps, knowledge graphs, and large‑model applications to create a unified, automated risk management platform.

AIBig DataMLOps

0 likes · 10 min read

Building an Integrated Intelligent Risk Control System for Banking

DataFunSummit

May 11, 2024 · Artificial Intelligence

Why Causal Inference Matters in Machine Learning and Its Banking Applications

The article explains the necessity of incorporating causal relationships into machine learning, outlines the development of causal science, and details how uplift modeling and causal‑regularized stable learning are applied to marketing and risk control in the banking sector, while also discussing practical challenges and experimental results.

Uplift Modelingbankingcausal inference

0 likes · 14 min read

Why Causal Inference Matters in Machine Learning and Its Banking Applications

DataFunSummit

Apr 16, 2024 · Artificial Intelligence

Intelligent Risk Control: Definitions, Expert Systems, Algorithmic Systems, and Emerging AI Techniques

This article explains intelligent risk control as a synergy of expert experience and algorithmic decision‑making, outlines its definition, expert human systems, digital algorithmic systems, and explores advanced AI methods such as reinforcement learning, large language models with knowledge graphs, adversarial learning, graph neural networks, and a practical supply‑chain case study.

Artificial Intelligenceadversarial learninggraph neural network

0 likes · 11 min read

Intelligent Risk Control: Definitions, Expert Systems, Algorithmic Systems, and Emerging AI Techniques

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

DataFunSummit

Jan 30, 2024 · Artificial Intelligence

Intelligent Risk Control Ecosystem: Building a Closed‑Loop System with Data, Models, Strategies, and Experiments

This article explains why and how to build an intelligent risk‑control ecosystem that forms a closed loop across data, model, strategy and experiment stages, illustrating the approach with QiFu Technology’s Yushu platform and detailing the architecture, components, and operational benefits for financial services.

AIBig DataFinTech

0 likes · 11 min read

Intelligent Risk Control Ecosystem: Building a Closed‑Loop System with Data, Models, Strategies, and Experiments