论文标题
了解客户的行为：金融交易的集群分析
Know Your Clients' behaviours: a cluster analysis of financial transactions
论文作者
论文摘要
在加拿大，省证券委员会和自我监管组织要求财务顾问和经销商对投资经销商和共同基金经销商的直接监管，分别收集和维护知道您的客户（KYC）信息，例如其年龄或风险承受能力，投资者帐户。有了这些信息，投资者在其顾问的指导下，就其投资做出决定，这些投资被认为对他们的投资目标有利。我们的独特数据集由金融投资经销商提供，拥有超过23,000个客户的帐户超过50,000个帐户。我们使用修改的行为财务新近度，频率，货币模型，用于量化投资者行为的工程特征，以及机器学习聚类算法来查找行为相似的投资者组。我们表明，收集到的KYC信息不能解释客户的行为，而贸易和交易频率和数量最有用。我们认为，此处显示的结果鼓励金融监管机构和顾问使用更先进的指标来更好地理解和预测投资者的行为。
In Canada, financial advisors and dealers are required by provincial securities commissions and self-regulatory organizations--charged with direct regulation over investment dealers and mutual fund dealers--to respectively collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts. With this information, investors, under their advisor's guidance, make decisions on their investments which are presumed to be beneficial to their investment goals. Our unique dataset is provided by a financial investment dealer with over 50,000 accounts for over 23,000 clients. We use a modified behavioural finance recency, frequency, monetary model for engineering features that quantify investor behaviours, and machine learning clustering algorithms to find groups of investors that behave similarly. We show that the KYC information collected does not explain client behaviours, whereas trade and transaction frequency and volume are most informative. We believe the results shown herein encourage financial regulators and advisors to use more advanced metrics to better understand and predict investor behaviours.
