Complidata
Bilige Wuyun is a Junior Data Scientist at Complidata since December 2022, where significant contributions include identifying critical features for detecting Financial Crimes and developing machine learning models to assess Financial Crime Risks. Prior experience includes a Data Science Internship at Materialise in September 2022, assisting the Marketing Team with a web development project, and serving as a Credit Analyst at Bank of China from June to September 2020, where in-depth data analysis aided in evaluating credit risks and generating reports for senior management. Bilige holds a Master of Science in Statistics and Data Science from KU Leuven and a Bachelor's degree in Econometrics and Quantitative Economics from Northeast Forestry University.
Complidata
Artificial Intelligence driving automation and optimisation in AML Compliance.We increase efficiency and effectiveness in specific domain and processes using advanced analytical techniques:►Trade Based AML: digitising the paper trail and automating manual checks on parties, counter-parties, ports & cities, vessels and ownerships, shippingroutes and goods against Sanctions & Embargoes and dual use goods lists; risk rating the trade and the vessels►Corporate KYC: automating the extraction of company information, directors and UBO’s from registers and documents, optimising company risk scorecards, data remediation, ID&V data extraction, entity resolution►Detection tuning and optimisation: model tuning, segmentation, above & below the line threshold testing, client and payments screening optimisation, 2nd filter►Investigation automisation: alert risk ranking, OSINT robotisation, data exploration, automated narrative generationComplidata positions itself at the crossroads between technology and advisory. It is built on the expertise and domain knowledge of senior AML professionals with hands-on regulatory, operational and technical experience on designing and managing a wide range of medium to large scale AML initiatives globally.