T/ZFIDA 0001-2022 Merchant Anti-fraud Security Defense System Design Guide
Main technical content: The standard applies to industries such as banking, third-party payment institutions, and Internet finance, covering the design and development of enterprise-level anti-fraud intelligent risk control and security defense systems for merchants, as well as evaluation work that can be referenced to guide financial institutions in implementing digital automatic detection applications for merchant risk identification and anti-fraud risk control technologies. The standard proposes standardized recommendations for the construction of anti-fraud security defense systems for merchants based on big data risk control technologies and AI intelligent decision analysis during the digital transformation process of the financial industry, as well as technical, development, deployment, and application solutions for automatic detection of various merchant risks. It also outlines methods for designing a full-lifecycle risk prevention and control strategy system for merchants. The main content of the standard includes covering multiple transaction, payment, and settlement channels for merchants in industries such as banking, payments, and the Internet under risk scenarios such as new types of telecom fraud, cross-border online gambling, money laundering, cashback, and illegal transactions. It utilizes AI models, fund networks, knowledge graphs, and content security analysis to conduct accurate risk profiling of merchants, explore and analyze related groups, and expand risk identification, locate merchant fraud risks, and propose anti-fraud risk prevention and control strategies for the entire business process of merchant acceptance and collection, payment and settlement, and fund transfer transactions. It also outlines requirements for building a seven-layered protection application architecture for full-lifecycle risk management of merchants and establishes requirements for implementing comprehensive pre-event, in-event, and post-event risk management and visua
Publish Date: 2022-12-28