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Provide analytic support for developing, tuning, optimizing, and modifying segmentation to improve transaction monitoring systems; and help to coordinate implementation of scenarios that effectively detect potential financial crime.
Responsible for supporting leadership to ensure a globally and regionally consistent effort that enables continuing improvement to transaction monitoring capabilities.
In coordination with the Global Financial Crimes Division (GFCD), this position will:
Support the development of policies and procedures for AML transaction monitoring life cycle, including reviews of scenario validation, segmentation, and optimization tools
Support a strategic optimization and segmentation initiative to enhance and tune Transaction Monitoring Program
Recommend customer segmentation and optimization
Monitoring system across multiple lines of business.
Assist in development of models involving tuning, calibration, segmentation, and optimization.
Perform model validation, memorializing model selection rationales and defined assumptions.
Work collaboratively with Financial Crimes staff in other branches as well as across functional teams w to ensure effective and efficient operations with clearly defined roles and responsibilities.
Bachelor's degree in statistics, mathematics, quantitative analysis, economics or related field
7 years of experience designing, analyzing, testing and/or validating AML models or monitoring systems
Familiarity with implementing, testing or evaluating performance of financial crime and compliance systems.
Prior experience designing compliance program tuning and configuration methodologies
Proven track record of strong quantitative testing and statistical analysis techniques as they pertain to AML models, unsupervised/supervised machine learning, etc.
Familiarity of current financial crimes compliance rules and regulations in the APAC region.
Working knowledge of programming platforms such as R, Python, SQL, VBA, etc.
Familiarity with vendor models such as Actimize SAM, SearchSpace, etc.
Strong knowledge of model risk management and associated regulatory requirements
For interested parties, please send resume to email@example.com We regret that only shortlisted candidates will be notified Capita Pte Ltd | EA Licence No 08C2893 | RCB No. 200701282M Grace Chuah Chia Wen | EA Registration No : R1876066