AML Monitoring Framework
A practical solution for reviewing suspicious patterns, transaction anomalies, and investigation data to improve compliance risk detection.
I’m Logan Jiang, a business analytics and risk-focused professional with experience in anti-money laundering, investigative analytics, and digital transformation. I combine structured thinking, data analysis, and business insight to help organizations make smarter decisions.
Business Analytics • Risk • Digital Transformation
Analytical mindset with a business lens.
I have hands-on experience in anti-money laundering (AML), economic crime analytics, internal compliance investigations, and digital transformation projects. My work has involved turning large and complex datasets into practical insights for operational teams, risk functions, and strategic decision-making.
Advanced training in analytics and data-driven management.
McGill University · Desautels Faculty of Management
Montréal, Québec, Canada
Tools and capabilities for modern business analysis.
Focused on data, risk, and strategic transformation.
Nanjing Cognitive Intelligence Information & Technology Co., Ltd. · Permanent Full-time
Nanjing, Jiangsu, China · Hybrid
Contributed to large-scale digital transformation and economic big data initiatives across government, public security, discipline inspection, tobacco, banking, finance, insurance, and more.
China Life Insurance Company Limited · Contract Full-time
Jingzhou, Hubei, China · On-site
Conducted comprehensive statistical analysis on various data sets including claims data, incident data, and personnel relationship data to identify trends and patterns.
国泰君安证券股份有限公司 · Internship
Shenzhen, Guangdong, China · On-site
Conducted asset allocation analysis for key clients in the securities and investment banking sector, provided optimization recommendations for asset custody processes, and assisted in operational risk control.
Selected work at the intersection of analysis and decision support.
A bilingual stock analysis tool using historical trading data and technical indicators such as MACD, RSI, Williams %R, and Bollinger Bands for actionable market insight.
A practical solution for reviewing suspicious patterns, transaction anomalies, and investigation data to improve compliance risk detection.
A personal research initiative focused on strategy design, signal testing, and performance evaluation using historical market data.
I enjoy collaborating on business analytics, compliance analytics, and digital transformation projects where data can drive better decisions.
LinkedIn: www.linkedin.com/in/logan-jiangLocation: Montreal, Canada
Focus: Business Analytics, Risk Management, AML, Digital Transformation
Interests: Quantitative analysis, forecasting, operational strategy
Stack: SQL, Python, Neo4j, Excel, Visualization, IBM I2
LinkedIn: linkedin.com/in/logan-jiang