Gartner发布了2018年的关于在线欺诈检测的市场指南:Market Guide for Online Fraud Detection
Increased investment in digital channel fraud prevention drives more fraud to the contact center, with social engineering, sophisticated spoofing and SIM swap schemes evading many legacy strategies, such as validation of static data or reliance on automatic number identification (i.e., caller ID).
Cross-channel behavior analysis is required to identify the most-complex fraud attacks; however, most online fraud detection solutions (including those applying machine learning) are still focused on point solutions for specific channels.
Automated attacks, and the speed with which attackers can modify their techniques to avoid detection, continue to put pressure on rule-based systems. This slows detection of new attacks and increases false positives, as rule libraries expand in breadth and complexity trying to keep up with new fraudulent activity.
挑选出几个重点:
1、模拟合法业务操作的自动化攻击(来自Bots的请求)成为在线业务欺诈非常重要的组成部分;
2、就整个反欺诈模型而言,对于非法用户行为的检测与分析处于高阶层次,如果做不到这一点就没法实现真正的实时拦截,属于后见之明。