Senior Manager - Corporate Risk Analytics

Abu Dhabi Islamic Bank; United Arab Emirates; On-site; AED 300,000 - 450,000; Full time

Job summary

A leading banking institution in the UAE is seeking a Senior Manager - Corporate Risk Analytics. This key role involves developing and maintaining credit risk models and performing advanced analytics. Candidates should have 7-12 years of experience in credit risk modeling and a Master’s degree in a relevant field. Strong communication and project management skills are essential, along with proficiency in statistical software like SAS, R, or Python. This position offers a significant impact on compliance and risk management processes within the bank.

Qualifications

• 7 - 12 years in credit risk modeling, Basel II and IFRS 9 implementation in the banking sector.
• Superior knowledge of Basel II, Basel III, and IFRS 9.
• Experience working with large and complex datasets.

Responsibilities

• Develop and maintain credit risk and profitability models.
• Conduct regular calibration and optimization of deployed models.
• Provide analytical support to the business.

Skills

Credit risk modeling

Analytical skills

Research skills

Communication skills

Project management

Education

Master’s degree in quantitative/finance

Professional Qualification (FRM, PRM or CFA)

Tools

SAS

R

Python

Job description

Role: Senior Manager - Corporate Risk Analytics

Location: Abu Dhabi

Role purpose

• This role is of high importance within Group Risk Management which will have a direct impact on the compliance of the bank with regulatory mandate on model management.
• The impact of this role on the non-retail banking business would be direct and significant as the incumbent is required to develop and maintain credit risk and profitability models.
• The incumbent is expected to independently perform advance analytics on the portfolio and continuously advise the Head of the team on emerging trends.
• The role requires independent thinking, strong communication, initiative, team management, project management interaction with stakeholders within the team.
• The candidate will have specialized exposure and capacity to execute and deliver end-to-end risk analytics project and framework independently.

Main responsibilities

• Quantitative analysis & modelling: Take a lead role in developing non-retail credit rating models, macro-overlay models and LGD models and participate in development of retail banking rating models as and when required by the Head of the team.
• In line with the requirements, participate in the deployment and integration of non-retail credit models in bank’s systems and processes.
• Develop methodologies to ensure effective monitoring of the models.
• Conduct regular PiT and TTC calibration and optimization of the deployed models as regulatory guidance.
• Perform monthly ECL / Provisioning calculation and report as per agreed timelines. Also develop IFRS based provision forecasting model for budgeting purposes.
• Provide required input for ICAAP and Macro Stress Testing for the Non-Retail Portfolios.
• Support the team head in ensuring compliance requirements are fulfilled and assist him in other initiatives.

Key accountabilities of the role

Customer (Internal & External)

• Liaise with the validation team on a regular basis to build and maintain compliant models. Perform model remediation as per recommendation from validation team.
• Fulfill requests from the external and internal auditors and the Compliance functions are fulfilled as and when required.
• Coordinate with team head and validation team for model methodology review and approvals.
• Provide analytical support to the business.
• Co-ordinate with external vendors whenever required in relation to activities within scope.
• Assist in Cost-of-Credit budgeting exercise for non-retail products

Internal (Processes, Products, Regulatory)

• Review existing model development and ECL calculations considering changing market conditions based on regulatory recommendations/ other best practices to ensure that a sound environment for identifying, assessing, measuring, monitoring and controlling risks are in place.
• Ensure correct functionality of the deployed models on the rating platform and institutionalize effective usage by conducting regular verification of inputs & outputs.
• Develop credit models as per requirements from the business, keeping in view the dynamics of credit portfolios and the best risk management practices.
• Lead the development of risk models of Basel / IFRS9 components i.e., PD, LGD, EAD etc., among various asset classes and facility types, ensuring these risk measures comply with regulatory requirements through robust modelling process.
• Address/ facilitate correction of any weaknesses identified during assessments, audits, or examinations by internal/ external audit staff, Group Compliance personnel, regulators examiners or Sharia’ auditors as applicable.
• Conduct monitoring of the deployed models on a regular basis and produce reports with recommendations for improvements to stakeholders.
• Create, maintain and update model / scorecard related documentation.
• Maintain historical datamart for non-retail products, with all the relevant parameter required for risk modeling, to bring efficiency and consistency in data preparation step of model development.
• Learning & Knowledge:
• Develop and lead training programs for team members, stakeholders on different conceptual aspects of quantitative analytics.

Qualification, skills / technical knowledge required for this role

• 7 - 12 years in credit risk modeling, Basel II and IFRS 9 implementation in the banking sector
• Master’s degree in quantitative/finance, professional engineering or any other related field
• Professional Qualification such as FRM, PRM or CFA is highly desired
• Excellent Credit Risk modelling, analytical, and research skills.
• Experience working with large and complex data sets, including alternative data (bureau, open banking etc.) for credit models.
• In-depth knowledge of financial markets and products and abreast with latest analytical techniques including Machine Learning algorithms such as Support Vector Machines, Random Forest and Gradient Boosting etc.
• Possess superior knowledge of credit risk management best practices including but not limited to pertinent Basel II, Basel III and IFRS 9 Framework on expected credit risk loss, credit risk management and capital adequacy requirements.
• Possess strong quantitative skills and solid experience in developing, validating and monitoring risk models. Knowledge of the credit scoring systems available in the market and their use.
• Advanced user of statistical software (such as SAS and R or Python)
• Should have strong knowledge of handling Risk Technologies & its implementation.
• Ability to work independently on multiple tasks and/or projects.
• Excellent oral and written communication skills in English.
• Proficiency in risk concepts, banking products/ operations/ systems, pertinent regulatory requirements,
• Flexible team player and able to work and deliver under pressure.