Provide expertise to analyze, recommend, develop and implement data drive solutions to uplift overall Corporate Banking Compliance AML risk surveillance capabilities.
Analyze data to research and enhance Customer Due Diligence (CDD) review process through the linkages and ascertaining predictive risk attributes exhibited by customers.
Collaborating with the relevant stakeholders in understanding the various data points and systems internally and externally for the purpose of identifying, testing, fine-tuning and defining the patterns within data and developing appropriate risk detection statistical models.
Identifying new emerging risks and applying appropriate strategies and techniques to mitigate.
Provide thought leadership to Corporate Banking Compliance team so they can visualize how data led techniques - such as machine learning - could significantly change the way that Compliance Operates.
Improve effectiveness and efficiency of compliance monitoring activities and processes leveraging on data analytics capabilities.
Surveillance to detect and validate suspicious transactions for escalation.
Documentation of workflows and develop regular reports on outputs, metrics measurements and any trend/linkages.
Be the GDO AML expert on regulatory and compliance related data matters.
Ensuring that progress of projects is well managed with timely communication to the relevant stakeholders.
Support any other ad-hoc system/digital improvement related projects assigned
Qualifications Requirements (Knowledge, Skills & Competencies): General Knowledge & Experience:
Be updated on industry risk surveillance trends and capabilities for application consideration within Corporate Banking Compliance
Previous data analytics experience in Risk Surveillance and/or Audit capacity covering at least 2 or more (AML/Sales/Operations/Fraud) categories preferred.
Demonstrated Forward thinking approach and initiatives in risk management via data analytics
Programming & Data:
Exposure to database or analytical marketing functions.
Some prior exposure to analytical software tools of leading analytical software tools (such as Python/SAS/R); leading database environments (Oracle / Teradata / Hadoop / SQL); reporting tools (Power BI/Qlikview / Tableau).
Ability to analyse, identify, visualize and describe key trends within large datasets