We are seeking a highly skilled and motivated Credit Risk Analyst to join our dynamic Risk Management team. The ideal candidate will play a critical role in developing, executing, and refining credit risk stress testing models and frameworks to ensure that the organization is well-positioned to manage and mitigate credit risk under various economic and financial scenarios.
Key Responsibilities:
- Credit Risk Stress Testing: Develop and execute stress testing frameworks to assess credit portfolio vulnerabilities under adverse scenarios. This includes scenario design, data collection, model execution, and result interpretation.
- Model Development: Collaborate with risk modeling teams to enhance stress testing models, including probability of default (PD), loss given default (LGD), and exposure at default (EAD) models.
- Regulatory Compliance: Ensure compliance with regulatory requirements for stress testing, including those prescribed by the Federal Reserve, HKMA, Basel guidelines, and other regulatory bodies.
- Data Analysis & Reporting: Analyze large datasets to identify trends, risks, and performance gaps. Provide insights through detailed reports to senior management and other stakeholders.
- Scenario Analysis: Create customized stress scenarios for specific market and credit risk factors such as changes in interest rates, unemployment, or housing market conditions.
- Documentation & Validation: Maintain thorough documentation of stress testing methodologies and validation efforts for both internal and regulatory audits.
Qualifications:
- Educational Background:
- Bachelor’s degree in Finance, Economics, Mathematics, Statistics, or a related field. Master’s degree or professional certifications such as CFA, FRM, or PRM are preferred.
- Experience:
- 1-4 years of experience in credit risk management, stress testing, or financial modeling, preferably in the banking or financial services sector.
- Hands-on experience with regulatory stress testing frameworks (CCAR, DFAST, CECL) is highly desirable.
- Technical Skills:
- Proficiency in statistical and data analysis software (e.g., SAS, SQL).
- Strong knowledge of credit risk modeling, including PD, LGD, and EAD frameworks.
- Experience with SQL and other data querying tools is a plus.
- Regulatory Knowledge:
- Familiarity with global regulatory requirements (e.g., Basel III, IFRS 9, HKMA, MAS, CCAR, CECL ) related to credit risk stress testing.