Job Description
– Support end-to-end review, refresh, and enhancement of IFRS 9 Expected Credit Loss (ECL) models, including PD, LGD, and EAD components, ensuring proper followed development document and accuracy outputs;
– Oversee monthly ECL calculation and reporting processes, ensuring accuracy, automation integrity, and timely delivery;
– Provide clear and insightful analysis on ECL movements and drivers for management understanding;
– Ensure accurate and timely submission of ECL reports and data to internal stakeholders, regulators, and parent company, meeting all compliance and audit requirements;
– Support development and implementation of Application Scorecard models, coordinating with stakeholders to ensure successful system
deployment and integration;
– Monitor and report scorecard performance metrics, identifying opportunities to optimize loan application processes and improve riskbased decision-making;
– Collaborate with operational teams to gather feedback and resolve issues related to score usage in loan underwriting and delegation, ensuring
smooth adoption and effectiveness;
– Conduct analysis of loan portfolio quality, providing reports, insights, and
actionable recommendations to management for strategic decisionmaking;
– Develop and maintain analytical tools to track portfolio trends and risk indicators, ensuring timely updates to meet management requirements and respond to market changes;
– Support preparation of ECL projections and budget plans, leveraging portfolio quality forecasts and scenario analysis to inform strategic
planning.
Job Requirements
- Bachelor degrees of Financial and Banking, Mathematics, Data Science or related field;
- Minimum 3 years’ experience in data analytics credit management and data analytics in financial and banking sector;
- Knowledge in advance excel, Power query, R, Python or other statistical tools;
- Experience in model governance or machine learning is a plus/preferable;
- Good in critical thinking and problem solving skill;
- Ability to handle challenging situation;
- Computer Literacy;
- Good verbal and written communication both Khmer and English.