Job Description

Overall Job Purpose:

• 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

• Machine learning, statistical modeling, visualization

Communication & Soft Skills:

• Good team player

• Good written and oral communication skills and ability to interact effectively with people at different levels

• Positive and progressive behavioral traits

*LI-WS

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