Assistant Manager - Model Monitoring (UAE National)

Job Description

In line with the UAE Government’s strategy in empowering and developing nationals, Emirates NBD is committed to welcoming the young generation into an innovative, modern and supportive work environment to contribute to the nation's success.

We are looking to find the best UAEN talent to join our ENBD family.

Organization Unit Purpose

The purpose of Group Risk Management unit is to ensure sound risk management practices in the organization and meet regulatory requirements. The unit has several deliverables that include Basel II compliance, Central bank reporting, IFRS 9 loss provisioning, Internal ratings and embedding them in business processes, AML & compliance, operational loss reporting, risk reviews etc.

Job Purpose

The prime responsibilities of Assistant Manager –Model Monitoring will be –

Assist the Manager Model Monitoring to manage interim tasks related to monitoring of retail and wholesale credit risk scorecards and models that are developed in-house and/or externally on an ongoing basis

Tasks related to monitor credit risk models across Emirates NBD Group – comprising Emirates NBD Bank, Emirates Islamic, Emirates Money, Emirates NBD Egypt and Emirates NBD KSA

Understand and comply to the established model monitoring best practices and processes within the organization

Prepare and collate monitoring results

Built reputation and collaborative relationships within the monitoring team

Job Content

Comply to model monitoring framework and standards

Work on retail and wholesale models to comply with the accepted monitoring methodology, metrics, benchmarks and guidelines customized to specific requirements of various kind of scorecards and models being leveraged currently in the organization

Understand and comply to the relevant documentation on model monitoring as a part of internal IP

Monitoring tasks related to –

Retail application, behaviour, collection and recovery scorecards.

Wholesale (Large corporate, Sovereign, SME etc.) rating models

Basel II Models – PD, EAD and LGD.

IFRS 9 Models – Expected Loss, Long term and PIT PD.+

Follow the annual model monitoring schedule incorporating models to be monitored and adhere to timelines for sharing data, sharing model specifics and model monitoring results

Perform model monitoring tasks as per the adopted monitoring methodology and prepare the results as per schedule

Self-assessment and growth in building a result-oriented attitude

Keep an active channel of communication within the team to share monitoring results and run self-assessment of shortcomings that suggest observed points of failure

Work on independently handling model monitoring tasks and co-ordinate with internal clients on necessary requirements including – SAS codes for creation of data base, scoring, good/bad tagging etc.; Model development specifics like development period, characteristics, OOT validation period etc.; on regular basis

Education

Bachelor's Degree in Math, Statistics, Physics, Engineering

Experiences

1- 2 years of experience

Knowledge & Skills

Understanding of statistical techniques in general at least.

Python, SAS, VBA, SQL, Maths OR Statistics

Excellent verbal and written communication abilities

Presentation skills

ResponsibilitiesPerformance Measures:Performance Measures:Performance Measures:Performance Measures:

Reliability of risk model outputs through timely execution of scheduled model monitoring activities

Conduct periodic monitoring of IFRS 9 and other risk models using established statistical and business performance metrics.

Compile and validate model performance data to identify deviations from expected outcomes, ensuring early detection of potential issues.

Document findings and observations in accordance with internal audit and regulatory requirements.

Escalate significant anomalies or emerging risks to the manager for further investigation and action.

Consistency and completeness of model monitoring documentation

Accuracy of anomaly detection and escalation

Stakeholder confidence in reliability of model performance reporting

Regulatory compliance in model monitoring processes aligned with internal and external standards

Apply current regulatory guidelines (e.g., MAS, PRA, RBI) to daily model monitoring tasks, ensuring adherence to all relevant standards.

Maintain up-to-date records of model monitoring activities for audit and regulatory review.

Support the preparation of regulatory submissions by providing validated model performance data as required.

Identify and report process gaps or compliance risks to the manager for remediation.

Absence of regulatory findings in model monitoring processes

Quality of records available for audit and regulatory inspection

Timeliness and accuracy of data provided for regulatory submissions

Data integrity and traceability in risk model monitoring datasets

Extract, cleanse, and organise model input and output data from risk systems to support monitoring activities.

Verify data lineage and traceability to ensure all datasets used in monitoring are accurate and complete.

Maintain clear audit trails for all data transformations and calculations performed during monitoring.

Collaborate with IT and data management teams to resolve data quality issues impacting model monitoring.

Completeness and accuracy of data used in model monitoring

Clarity and auditability of data transformation documentation

Resolution rate of data quality issues impacting monitoring

Business insight for risk management decisions enabled by clear and actionable model monitoring reports

Prepare concise monitoring reports summarising model performance, key findings, and recommended actions for direct stakeholders.

Translate technical results into business-relevant insights for risk and finance teams.

Respond to queries from business users regarding model monitoring outputs and methodologies.

Support the continuous improvement of reporting templates and communication channels for model monitoring results.

Clarity and relevance of monitoring reports for business stakeholders

Responsiveness to stakeholder queries and feedback

Demonstrated impact of monitoring insights on risk management actions

Qualifications

Bachelor's degree in Statistics, Mathematics, Finance, Economics, or related field

Relevant certifications in risk management or data analytics (e.g., FRM, CFA, SAS Certification) preferred

Ongoing professional development in regulatory and risk management practices