Mounir Shal

• Orchestrated the successful deployment of SAS Regulatory Capital Management (SAS RCM) within the University and the Department of Finance, playing a pivotal role in ensuring compliance with regulatory standards and enhancing risk management capabilities.

• Led the implementation of SAS Regulatory Capital Management (SAS RCM) in the Azure environment at the university, demonstrating a keen understanding of cloud technologies and leveraging the Azure platform to optimize performance, scalability, and security for regulatory compliance processes.

• Experienced in efficiently managing SAS IRM (SAS Infrastructure for Risk Management) instances

• Experience on Agile methodology.

• End-to-End implementation of SAS

• Customized and integrated code in SAS.

• Identifies and manages interfaces, service levels, standards, and configurations

• Hands-on experience in identifying and resolving bugs

• Performed functional tests on different environments.

• Hands-on experience in Product Management.

• Maintain, Integrate and enhance the source code and process flow for the department's SAS production environment.

• Providing and managing data for many financial publications.

• Expert in Orchestration updates and configuration upgrades.

• Providing and managing data for many financial publications. 2022 "Investing in infrastructure as an asset class." 2015 Dash for Cash: Month-End Liquidity Needs and the Predictability of Stock Returns 2015 Applying Benford's Law to detect fraudulent practices in the banking industry. 2015 Essays on Credit Risk: European studies in the context of the global financial crime 2013 Forecasting distress in European SME portfolios 2013 An R-package for finite mixture models

• Responsible for deploying SAS in the university and the Department of Finance.

• Implementation of SAS in the Azure environment in the university.

• Responsible for Bloomberg, WR, skills=[]

• Credit Risk Modelling & Forecasting: Designed, developed, and maintained statistical models for credit risk forecasting using SAS (Base, Enterprise Guide), with a focus on Probability of Default (PD), Loss Given Default (LGD), and Loss per Default (LPD). Ensured models were compliant with Basel II/III regulations and aligned with internal risk policies.

• Key Project – Logistic Regression Model for Credit Card Risk: accuracy of risk forecasts and was successfully integrated into the bank's SAS-based credit risk platform, enabling dynamic, data-driven credit line management.

• Business Analysis & System Integration: Acted as a liaison between risk management, IT, and data teams to gather business requirements, validate data sources, and translate needs into technical specifications. Supported the integration and automation of risk models into operational systems, ensuring scalability and consistency.

• Risk Reporting & Regulatory Compliance: Maintained and improved the fund and credit risk reporting systems, producing reports for internal risk committees and regulatory bodies (e.g., CSSF). Participated in monthly and quarterly closings with a focus on portfolio risk evolution and regulatory alignment.

• Reporting Data Warehouse for the KPI project Cognos and Oracle 9i bases tools Billing project for Amadeus