Manager

Key Responsibilities
Model Development & Enhancement
o Develop and implement advanced quantitative models for assessing credit risk, including
models for PD, LGD, and EAD.
o Work with large datasets to develop models that estimate credit risk exposure, focusing on
accuracy, robustness, and predictive power.
o Design and refine models to calculate Expected Credit Loss (ECL) under IFRS 9 and CECL
frameworks, ensuring compliance with accounting and regulatory standards.
o Continuously monitor and enhance existing models based on new data, market conditions, and
regulatory changes.

Model Validation & Backtesting
o Validate and backtest credit risk models, ensuring they meet the required standards for
accuracy, consistency, and reliability.
o Develop validation frameworks for assessing model performance and ensuring models
accurately reflect credit risk under different economic conditions.
o Provide documentation of model assumptions, methodologies, and limitations, ensuring
transparency and compliance with internal governance and regulatory requirements.
o Conduct periodic performance reviews and backtesting of models to ensure they continue to
perform well over time and align with actual credit losses.

Expected Credit Loss (ECL) Modeling
o Lead the development of ECL models, calculating the credit loss provisions for financial
instruments in line with IFRS 9 or CECL.
o Develop robust methodologies for estimating PD, LGD, and EAD at a granular level (e.g., loan
type, sector, region), while incorporating macroeconomic factors.
o Collaborate with accounting, finance, and credit risk teams to integrate ECL models into the
firm's risk management and financial reporting processes.
o Ensure that the ECL models reflect appropriate segmentation of portfolios and the application
of relevant adjustments for forward-looking information.

Credit Risk Stress Testing
o Lead the design and execution of credit risk stress testing processes to assess the resilience of
credit portfolios under extreme but plausible scenarios.
o Develop and implement stress testing models for key credit risk metrics such as PD, LGD, and
EAD under different macroeconomic and market scenarios.
o Collaborate with other risk teams to define relevant stress test scenarios, including both
regulatory scenarios (e.g., CCAR, EBA) and internal stress scenarios.
o Analyze stress test results and present findings to senior management, providing actionable
insights on portfolio risk, capital adequacy, and mitigation strategies.

Model Governance & Regulatory Compliance
o Ensure that all credit risk models adhere to regulatory requirements, including Basel III, IFRS 9,
CECL, and other relevant global or local regulations.
o Contribute to internal and external model audits and provide clear documentation on model
assumptions, validation processes, and limitations.
o Stay up-to-date with regulatory changes and industry best practices to ensure models remain
compliant with evolving standards and regulations.
o Assist in the preparation of regulatory reports and disclosures related to credit risk modeling
and stress testing.

Collaboration & Stakeholder Engagement
o Collaborate with other departments (e.g., credit risk, finance, accounting, and IT) to ensure that
models are integrated effectively into day-to-day operations and decision-making.
o Provide support to senior management in understanding model outcomes, advising on risk
mitigation strategies, and supporting strategic decision-making.
o Provide expert advice on the application and interpretation of credit risk models, both to
technical teams and non-technical stakeholders.

Requirements Qualifications

• Education: Master's or PhD in Quantitative Finance, Financial Engineering, Mathematics, Statistics, or a
related field. Professional certifications (e.g., CFA, FRM) are a plus. Candidates with proficiency in VBA,
Python, SAS will be preferred.

• Experience:
o Minimum of 3-5 years of experience in quantitative risk modelling, with a focus on credit risk,
PD, LGD, EAD models, and stress testing.
o Proven experience with the development and validation of ECL models under IFRS 9, CECL, or
similar regulatory frameworks.
o Hands-on experience with credit risk stress testing methodologies and model implementation.
o Strong background in working with large financial datasets and using statistical modeling
techniques to assess and manage risk.

• Technical Skills:
o Proficiency in programming languages such as Python, R, MATLAB, or SAS for model
development and data analysis.
o Strong experience with data analysis tools (e.g., SQL, Excel, Hadoop, Spark) and machine
learning libraries (e.g., scikit-learn, TensorFlow).
o Familiarity with credit risk management platforms (e.g., Moody's, S&P, Bloomberg) and risk
analytics tools.
o Strong understanding of financial statements, credit ratings, and macroeconomic factors
influencing credit risk.
Join us in shaping the future of Financial Risks and making a meaningful impact in industry. Apply now to join our
collaborative and forward-thinking team

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