标题： 基于Spark的海量交易网络中新型社区检测的智能反洗钱解决方案 显示英文标题

标题： Intelligent Anti-Money Laundering Solution Based upon Novel Community Detection in Massive Transaction Networks on Spark

摘要： 犯罪分子正在使用一切可用的手段，将非法活动的收益洗白成表面上合法的资产。 同时，大多数商业反洗钱系统仍然是基于规则的，无法适应不断变化的手段。 尽管已经提出了一些机器学习方法，但它们主要集中在单个账户的异常行为角度。 考虑到洗钱活动通常涉及犯罪团伙，这些方法仍然不够智能，无法全面打击犯罪团伙。 在本文中，提出了一种系统性的解决方案来发现可疑的洗钱团伙。 提出了一种时间导向的Louvain算法，根据相关的反洗钱模式来检测社区。 所有过程都在Spark平台上实现并进行了优化。 该解决方案可以大大提高金融监管机构的反洗钱工作效率。 显示英文摘要

摘要： Criminals are using every means available to launder the profits from their illegal activities into ostensibly legitimate assets. Meanwhile, most commercial anti-money laundering systems are still rule-based, which cannot adapt to the ever-changing tricks. Although some machine learning methods have been proposed, they are mainly focused on the perspective of abnormal behavior for single accounts. Considering money laundering activities are often involved in gang criminals, these methods are still not intelligent enough to crack down on criminal gangs all-sidedly. In this paper, a systematic solution is presented to find suspicious money laundering gangs. A temporal-directed Louvain algorithm has been proposed to detect communities according to relevant anti-money laundering patterns. All processes are implemented and optimized on Spark platform. This solution can greatly improve the efficiency of anti-money laundering work for financial regulation agencies.