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Senior Manager, Credit Risk Management

3 weeks ago


กรงเทพมหานคร, Thailand Lazada (Thailand) Co., Ltd. Full time

**Team and Role Introduction**:
Lead and implement credit strategy for retail product including BNPL/Cash Loan and SME product for one or multiple markets and take ownership of portfolio risk performance
Conduct risk assessment on user profile. Monitor and analyze risk indicators to finetune underwriting and portfolio management policy
Prepare and analyze risk reports such as portfolio performance, industry exposure, vendor performance and historical customer trends
Coordinate with modeling team on risk tools development including decision scorecards and responsible for risk model evaluation and continuously monitor its performance to ensure the stability and accuracy of risk strategy
Support conceptualization development for new credit products suitable for retail and SME markets
Track and monitor the full credit cycle performance and risk appetite metrics.
Evaluate and influence to balanced business growth in the form of policy refinement and credit testing
Ensure compliance with regulatory requirements and industry best practices
Support country with portfolio deep-dive analyses and provide insights with recommendations on policy changes to improve portfolio quality.
Collaborate with Business teams, Product teams, Engineering teams and Ops team to balance risk management target with business target and user experience.
Bachelor Degree and above in Finance, Computer Science, Statistics, Economics, or other relevant fields from a worldly recognized university with good academic credentials
Minimum 8 years experience in risk management area in a sound financial institution, with good track record of risk performance of the managed portfolio
Deep understanding of the underwriting policy, limit management policy, portfolio management policy, and modeling
Strong attention to details and ability to notice discrepancies in data, with good experience to process large amounts of data
Excellent problem-solving skills and solid experience in data analytics
Profiency in SQL, Python or Pyspark.