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CIMB Singapore

Business Data Analyst SG

CIMB Singapore · Singapore, Singapore

Banking · 1,001-5,000 employees

6 h ago
Senior (5-10 yrs) Full-time Singapore
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About the role

The Business Data Analyst will develop analytical models to identify fraud and money mule activities while optimizing collection strategies for delinquent accounts. They will also maintain dashboards and automate reporting processes to support lending products and cross-functional business teams.

What they look for

SQL Python R Tableau Power BI SAS Data Analytics Fraud Analytics Collection Analytics Credit Risk Consumer Banking Statistical Modeling Dashboarding Data Linkage Clustering Techniques Reporting

Requirements

Candidates must hold a Bachelor's degree in a quantitative field and possess at least 5 years of experience in data analytics. Proficiency in SQL, Python, R, and visualization tools like Tableau is required, along with domain knowledge in consumer banking and fraud or collection analytics.

Full description

Responsibilities:

Fraud Risk Management Analytics

  • Develop analytical models to identify potential card fraud and money mules activities, analyze patterns related to card misuse, chargebacks, identify networks of accounts involved in money mule activities using data linkage and clustering techniques, analyze unusual cashflow patterns and assets the risk of potential mule networks
  • Conduct data analytics to detect suspicious transaction patterns and fraudulent behaviour.
  • Perform post-transaction analysis to uncover trends and identify risk indicators
  • Collaborate with the fraud management team to support case analysis and reporting
  • Generate insights and reports on fraud trends, highlighting risk areas and mitigation effectiveness

Collection Analytics

  • Assess customer repayment behavior to refine collection strategies
  • Develop models to segment delinquent accounts based on risk levels
  • Provide insights on recovery rates and optimize prioritization for collection efforts
  • Provide business recommendations on collection effectiveness, portfolio segmentation, and customer repayment behavior
  • Develop collection productivity dashboard to support collection team, identify areas for productivity improvement

Support CBS related matters

  • Perform monthly CBS submission for cards and support CBS queries

Modelling, Analytics and Dashboarding for Lending Products

  • Build, maintain models and perform analytics to support lending products’ analytics use cases
  • Create and maintain dashboards for lending products
  • Automate reporting processes to improve efficiency and accuracy
  • Prepare management reports that highlight performance trends and business outcomes

Cross-Functional Collaboration

  • Partner with collection operation, credit risk, fraud management and product teams to ensure alignment of business strategies with risk appetite
  • Work with tech teams for any tech enhancement for collection and risk related data project
  • Support compliance and regulatory reporting as needed
  • Work closely with IT for any project related to CBS and Credit Risk related project from SG Consumer banking

Innovation and Best Practices

  • Stay updated on industry trends, best practices, and regulatory changes in the banking and wealth management sectors to identify opportunities for innovation and competitive advantage

Requirements:

Qualifications

  • Bachelor’s degree in Data Science, Data Analytics, Business Analytics, Statistics or related field; Master’s degree preferred
  • 5+ years of experience in data analytics
  • Proven expertise in analytics tools (e.g., SQL, Python, R) and visualization platforms (e.g., Tableau, Power BI)

Relevant Work Experience

  • Experience in Fraud analytics, Collection analytics or CBS related data
  • Familiarity with Consumer Banking products including Loan, Credit card, Mortgage
  • Ability to work collaboratively in cross-functional teams and manage multiple priorities in a dynamic environment
  • Knowledge of regulatory requirements and industry compliance standards in the banking sector
  • Excellent communication and presentation skills to effectively convey complex data insights to non-technical stakeholders

Competencies/Skills

  • Proficient in SAS, SQL, Python, R Programming and MS Excel
  • Proficient in Business Intelligence tools (Tableau)
  • Must be able to solve problem quickly and efficiently
  • Strong analytical and communication skills