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مطلوب رئيس نماذج المخاطر غير التنظيمية والمعيار الدولي لإعداد التقارير المالية لدى بنك أبوظبي الأول (FAB) في أبوظبي، الإمارات

مطلوب رئيس نماذج المخاطر غير التنظيمية والمعيار الدولي لإعداد التقارير المالية لدى بنك أبوظبي الأول

(FAB) في أبوظبي، الإمارات

Head of Non – CB Regulatory & IFRS9 Risk Models

The key accountabilities, which are currently envisaged, are as below:

 

1. Clear articulation of modelling requirements from business discussions is a key responsibility. Further, designing model development programs and providing functional program management throughout the development lifecycle is a must.

2. The individual should be able to clearly suggest soundness of modelling technique and statistical tests applied to different types of models. Proficiency in AI examinability would be a plus.

3. Engage with validation and other control units in a professional manner, maintaining independence and ensure design and implementation of remedial actions.

4. Assist Head-ERS in external and internal stakeholder engagement with respect to model development, usage of models, strategy finalization and other aspects to promote awareness among business community.

5. Responsible for adherence to compliance including regulatory observations.

6. Provide an expert view to senior management requiring analytical support for decision making

7. Provide regular report on key information/risk/dashboard on model development programs, portfolio coverage, pipelines, expected risks and suggestive actions.

8. Work with data engineering team, business team and Information technology team for model implementation

9. Lead the model education among user groups, advising them of risks/impacts due to incorrect model usage

10. Advise new growth opportunities gaining insights, which result into optimum risk adjusted revenues.

11. Develop a team of technical experts including regular review and performance assessment

Job Context:-

 

FAB is a large diversified bank operating in consumer, corporate, investment, transaction and wealth banking, largest in UAE and second largest in MENA by asset size. The bank’s asset size has been increasing over the year across all business lines. Size, breadth and complexity of the portfolio has increased the model complexity along with increasing regulatory scrutiny.

The regulator has strongly advised to develop a team of skilled and experienced internal resource. Regulator expects internal resources to own the methodology and techniques for model development, usage and associated strategy. The job is hence critical for tracking risk models and ensuring they are fit for purpose, timely escalation of significant model deterioration, keeping close watch on the overall model governance to give confidence to senior management, auditors and regulators.

The job additionally requires review of external environment [economic events, business events and regulatory guidelines] and pro-actively advise corrective action plan.

FRAMEWORKS, BOUNDARIES, & DECISION MAKING AUTHORITY:

 

Functions within the framework and boundaries of Group policies as well as overall organizational and governance frameworks.

Authorized to take decisions as per the approved authorization matrix.

Qualifications

 

Minimum Qualification:-

Master’s degree in quantitative science (statistics, mathematics, economics) from a premier institution, in UAE or abroad.

Minimum Experience

 

13 – 15 years of experience in successfully executing model development lifecycle, associated strategy formulation and implementation is essential for this role. He/she should have worked in models for different business segments, mainly retail and corporate. Having worked in global delivery model [onshore-offshore] is a plus

Should have demonstrated experience in managing a team of experienced modelling professionals particularly in Model Development. Managing cross culture team would be a plus.

Should have hands-on model development & validation experience on decision models (Application, Behavior and Collections) and Regulatory models (IFRS9 – PD, EAD and LGD)

Comprehensive understanding of traditional and new modelling techniques: linear and logistic regression, timeseries, Decision Tree etc. & Random Forest, XGboost, Neural Networks, etc).

Should have experience and strong knowledge SAS, Python and R. Should be willing to learn newer technologies which are open source based and should be comfortable in working in collaborative manner on a cloud based environment.

Excellent interpersonal & communication skills – verbal and written

Proven experience of developing team of high performers and prior experience in managing conflicts would be required.

Additional Information

 

The purpose of the job is to lead model development team for the group [UAE along with applicable international branches/subsidiaries]. The candidate would be required to engage with various stakeholders, internal and external, to understand the requirements and provide analytical solution in a time bound manner of high quality, being fully compliant with relevant regulatory requirements. The person will be responsible for advising/implementation best of the class modelling techniques (traditional and advance machine learning) commensurate with bank business growth aspirations, while aligning with regulatory expectations.

This is a specialized quantitative role and requires candidate with strong statistical background and practical experience of working for comparable bank/financial institution in risk modelling. The candidate should have complete understanding of all major statistical tests used for modelling viz. model stability, accuracy and risk discrimination and their consequent impact on Bank’s risk profile.

The role will be supported by a mix of resources, operating offshore. The Offshore team will be functionally reporting in a matrix structure. The job also requires familiarizing business community with model relevance, usage and associate risks; identify areas of business growth using models/data and achieve optimum risk adjusted revenues.

The role will assist Head of ERS in discharging responsibilities related to model development, implementation, data governance, model risk and compliance matters

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