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Financial Security

10 articles · Page 1 of 1
BanTech Think Tank
BanTech Think Tank
Aug 28, 2026 · Information Security

LLM-Enhanced Penetration Testing for Finance: Multi-Agent Architecture & Practice

The article details a large language model-enhanced penetration testing framework for financial services, combining a four-layer architecture, multi-agent collaboration, financial business semantic knowledge base, and reusable skill library to improve testing efficiency, business logic risk detection, and process standardization, validated through deployment at China Postal Savings Bank.

Business Logic VulnerabilitiesChina Postal Savings BankFinancial Security
0 likes · 21 min read
LLM-Enhanced Penetration Testing for Finance: Multi-Agent Architecture & Practice
AntTech
AntTech
Oct 16, 2025 · Information Security

How Alipay’s Trusted Deep Defense System Secures Financial Transactions

Alipay’s trusted deep defense architecture, built on security parallel slices and trusted computing, was selected as a flagship case for the 2025 Important Industry Security Protection list, demonstrating zero‑false‑positive, zero‑miss, and zero‑business‑disruption protection against advanced threats such as 0‑day and APT attacks during high‑traffic events like Double 11.

Deep DefenseFinancial SecurityTrusted Computing
0 likes · 5 min read
How Alipay’s Trusted Deep Defense System Secures Financial Transactions
Tencent Cloud Developer
Tencent Cloud Developer
Jan 9, 2025 · Information Security

Why You Can’t Hack WeChat Balance: 5 Layers of Financial Safeguards

The article breaks down five technical defenses—database storage, transaction logs, double‑entry checks, account‑aging monitoring, and external reconciliation—that prevent anyone from arbitrarily changing a WeChat user's balance, illustrating why such tampering is practically impossible.

Financial SecurityWeChataccounting controls
0 likes · 6 min read
Why You Can’t Hack WeChat Balance: 5 Layers of Financial Safeguards
DeWu Technology
DeWu Technology
Jul 29, 2024 · Artificial Intelligence

AI-Driven Loss Prevention: A Comprehensive Field-Level Risk Control System

The paper introduces an AI‑driven loss‑prevention platform that augments manual risk analysis with automated field recognition to map database and code models, generate loss‑related methods and interfaces, and deliver pre‑emptive avoidance, real‑time detection, and post‑incident response, achieving over 1,200% growth in identified loss methods and near‑full field coverage.

AIBusiness IntelligenceFinancial Security
0 likes · 8 min read
AI-Driven Loss Prevention: A Comprehensive Field-Level Risk Control System
Tencent Cloud Developer
Tencent Cloud Developer
Jul 17, 2024 · Databases

Design and Implementation of a Payment Fund Account System

The article outlines the design and implementation of a secure, highly available payment fund account system, explaining core concepts of accounts and double‑entry bookkeeping, detailing architecture using TDSQL sharding, and describing security measures such as STRIDE analysis, HMAC‑SHA256, idempotency, distributed transactions, and comprehensive auditing to ensure fund integrity under high concurrency.

Financial SecuritySystem DesignTDSQL
0 likes · 34 min read
Design and Implementation of a Payment Fund Account System
AntTech
AntTech
Dec 13, 2023 · Information Security

Graph-Based Intelligent Risk Control: Technologies, Infrastructure, and Real‑World Cases

The article reviews the rise of graph‑based intelligent risk control in the digital economy, outlining its technological evolution, key algorithmic capabilities, underlying infrastructure requirements, and practical case studies that demonstrate its impact on financial security and high‑concurrency scenarios.

Financial SecurityGraph Neural Networksbig data analytics
0 likes · 9 min read
Graph-Based Intelligent Risk Control: Technologies, Infrastructure, and Real‑World Cases
DataFunSummit
DataFunSummit
Dec 15, 2022 · Information Security

Multi‑Party Secure Risk Control: Challenges, Architecture, and Practice

This article examines the growing complexity of financial risk scenarios, outlines global privacy regulations, describes Ant Group's three‑layer multi‑party secure risk‑control architecture, showcases anti‑fraud and external client use cases, and discusses current challenges and future directions for secure, privacy‑preserving risk management.

Financial Securityprivacy protectionregulatory compliance
0 likes · 14 min read
Multi‑Party Secure Risk Control: Challenges, Architecture, and Practice
ByteDance SE Lab
ByteDance SE Lab
Jun 28, 2022 · Backend Development

Douyin's Video Red Packet System: Architecture, Scaling Challenges & Solutions

During the Chinese New Year campaign, Douyin integrated video creation with red packet gifting, supporting both B2C and C2C flows; this article details the system’s core operations, modular design, high‑traffic subsidy handling, concurrency strategies, fault tolerance, security measures, and comprehensive performance testing.

Financial SecurityHigh ConcurrencySystem Design
0 likes · 24 min read
Douyin's Video Red Packet System: Architecture, Scaling Challenges & Solutions
Cloud Native Technology Community
Cloud Native Technology Community
Jun 2, 2022 · Cloud Native

Cloud‑Native Networking: Trends, Application Scenarios, and Solutions

This article analyzes the rapid evolution of cloud‑native networking, identifies key trends such as the limits of a single CNI, the rise of auxiliary components, emerging technologies and hardware‑software integration, and examines six major application scenarios—from traditional workloads to edge, multi‑cluster, financial‑grade security, and telecom—offering open‑source and commercial solutions for each.

Financial Securityedge computingnetworking
0 likes · 15 min read
Cloud‑Native Networking: Trends, Application Scenarios, and Solutions
DataFunTalk
DataFunTalk
Feb 11, 2019 · Artificial Intelligence

Machine Learning Applications in Credit Anti‑Fraud

This article explains how machine learning, deep learning, and graph‑based techniques are applied to credit anti‑fraud in finance, covering fraud risk characteristics, the anti‑fraud lifecycle, rule limitations, supervised models, common algorithms, neural networks, time‑series models, and graph analytics for detecting individual and group fraud.

AIFinancial Securitycredit risk
0 likes · 11 min read
Machine Learning Applications in Credit Anti‑Fraud