Automating Post-trade Compliance Supervision through Machine Learning****

加拿大金融机构必须遵守加拿大投资行业监管组织（IIROC）的规定，才能在加拿大开展任何交易业务。根据IIROC的规定，投资顾问应该注册，以确保他们遵守与商业行为、金融运作和交易实践相关的一套规则。因此，投资顾问代表客户进行的每笔交易都必须根据一组特定规则进行验证。该过程由合规主管执行。目前，合规监管人员依靠一种基于风险的方法，利用财富管理软件生成的数据来检测可能违反规则的交易。然而，这种方法并不适用于每天交易的绝对数量。因此，大量的交易没有得到控制。为了进行全面和详尽的贸易验证，需要一种自动化的方法。本研究项目的主要目标是通过基于机器学习的方法实现交易后合规监督过程的自动化。* * * * * *

Canadian financial organizations are required to comply with the regulations specified by the Investment Industry Regulatory Organization of Canada (IIROC) to be able to perform any trading operations in Canada. According to IIROC regulations, investment advisors should be registered in order to make sure they comply with a set of rules related to business conduct, financial operations and trading practices. Consequently, every trade performed by an investment advisor on behalf of a customer must be validated against a set of specific rules. This process is undertaken by a compliance supervisor. Currently, compliance supervisors rely on a risk-based approach using the data generated by a wealth management software in order to detect trades that might violate the rules. However, this approach does not scale with the sheer number of trades made every day. Therefore, a huge number of trades are left unchecked. An automated approach is required in order to perform a comprehensive and exhaustive trade validation. The main objective of this research project is to enable the automation of the post-trade compliance supervision process through a machine learning based approach. ******