Associate Recruitment Manager at WEN
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Lead Expert/Manager - Market Risk Model (7-11 yrs)
The mission of a Model Risk Manager is varied and hinge upon the strengthening of regulatory and accounting requirements related to the supervision and monitoring of risk models. In this context, you
will be responsible for conducting internal model reviews (validation of the modeling, backtesting, etc.) that have been developed by the Group's modeling entities.
Your main missions will be:-
1. End to end responsibility of modeling validation missions, based on the planning and framework
2. Interact with the modeling entities
3. Analyze and test methods by using both technical knowledge and critical thinking.
4. Conduct quantitative reviews (statistics).
5. Be vigilant in the analysis of the regulatory compliance, robustness and performance of these models.
6. Contribute to the composition of a validation report in order to communicate the conclusions of the review mission.
7. Contribute and present the results of the review at the Models Committee
8. Ensure adequate documentation and archiving of the analysis carried out.
9. Mentoring Junior team members.
10. The Manager works on many different topics such as: retail or wholesale credit risk (PD models, CCF models, LGD models, stress tests.), market risk models (VaR/SVaR/FRTB, EEPE, CVA, SIMM, IRC/CRM...), models developed under the IFRS 9 framework, models developed to comply with US regulatory requirements.
11. Strong Project Management skills
12. Excellent Communication Skills.
Ideal candidate should be well versed in credit risk model development, validation and maintenance of models (PD, LGD and EAD) for wholesale and retail credit portfolio of the bank as per regulatory guidelines.
Exposure to banking book and understanding of trading book products and knowledge on BASEL/IFRS guidelines is highly desirable. Candidate should have excellent business communication skills.
Post-graduation degree in quantitative discipline (Statistics, Economics, Mathematics & engineering) from Tier I/II colleges. Additional certification in machine learning techniques or estimation of credit risk parameters will be preferred.
Role & Responsibility:
The ongoing monitoring of the model is a task that must be done in all phases of the model lifecycle (development, implementation, use). In order to track and measure the efficiency and adequacy of models, the model monitor conducts continuous analysis and controls as an early warning both initially at implementation (for new models) and regularly as a part of the model's ongoing monitoring.
For the purpose of these tests, the model monitor is responsible to:
1. Backtest & re-calibrate each model designed and developed by the business, hence a thorough understanding of model development under Basel & IFRS norms is critical.
2. Choose adequate model outcome analysis techniques such as:
a. Model estimates vs realized values (e.g. back-testing for some models);
b. Stability of model outcomes;
c. Benchmarking: model output vs output generated by comparable models or applications
d. Sensitivity analysis to test robustness
3. Analyze the model output and the related components (if applicable);
4. Model assumptions and limitations validity;
5. Results of benchmarking and sensitivity analysis;
6. Accuracy of model's characteristics;(ROC/AUC, KS statistics, accuracy ratio, Gini coefficient etc.)
7. Monitor over time in order to follow up trends and detect deviations;
8. Establish thresholds and action plan for major deviations;
9. Report this analysis to the different model stakeholders.
10. Implement a governance to monitor the corrective actions.
Furthermore, as part of the model ongoing monitoring phase, the model monitor should abide by the group standards on ongoing monitoring that establish guidelines on performance assessment processes including type, scope and range of tests and appropriateness of responses to any problems that may appear.
Regulatory risk model (IRB, IFRS9) model validation, monitoring, development (good to have) using SAS,
R. Initiation to machine learning model validation.
- Knowledge of Global regulatory Topics BASEL II/III & IFRS 9
- Understanding of risk management and risk quantification processes
- Understanding of forms of risk, viz. credit, market, operational, model etc.
- Result Orientation
- Client Focus
- Contribution to Strategy
- Team Player
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