soukaina tazrouti

Experience in the Risk Department: Expert in developing risk models (CCF, LGD, PD, RWA, EL) to ensure regulatory compliance and adherence to international standards. Proficient in utilizing advanced data analytics to evaluate portfolio risk and deliver actionable insights for informed decision-making. Highly skilled in Python, SAS, statistical modeling, and reporting tools to provide regulator-compliant, high-quality solutions.

Experience in the Risk Department: Responsibilities across various credit risk management topics, particularly LGD and CCF, include: Designing and calibrating models to assess economic capital requirements (Basel II standards). Applying statistical methodologies and mathematical tools to calculate differentiation and quantification risks. Effectively communicating with diverse teams, including Audit, Business, and IT. Addressing recommendations from internal audit services and the European Central Bank (ECB). Ensuring comprehensive knowledge of applicable regulations. Preparing and maintaining accurate and thorough documentation.

Organized analytics workshops with business stakeholders to identify and prioritize key business needs. Designed and implemented data pipelines using SQL and SAS for seamless integration into calculation tables. Built Datamarts to support the development of statistical models leveraging data from internal systems (SISP). Conducted statistical analyses (descriptive and predictive) to generate actionable insights. Performed segmentation analysis to group individuals into homogeneous clusters based on key characteristics. Selected and optimized relevant variables and modalities using internal and external datasets (e.g., INSEE). Developed predictive models to analyze and forecast re-registration behavior as a target variable.

Experience in Wealth Management: Extracted and transformed data from study databases (Business Objects) and calculated key indicators using SAS. Automated and formatted reports using VBA scripts in Excel to support wealth management decision-making. Designed and deployed reporting solutions, including testing, production rollout, and publication, tailored to the patrimonial sector. Authored comprehensive technical documentation detailing reporting generation steps and functional specifications.

Data Science Experience - Risky Customer Targeting & Ad Hoc Analysis: Conducted ad hoc analyses on customer datasets to identify churn risks and analyze customer behavior. Developed predictive models to assess the probability of churn using classification techniques and advanced statistical analysis (e.g., logistic regression, decision trees). Segmented the customer base into homogeneous groups based on their risk (churn, solvency, etc.) to better target retention and acquisition efforts.

Actuarial Experience - Insurance & Provident Responded to client requests (Malakoff Médéric, Mutex, MMA) on actuarial issues related to provident and collective health insurance. Ensured accessibility, availability, and quality of data required by all team members in the department. Calculated technical provisions in construction insurance using the Chain Leader method (MMA), ensuring compliance with actuarial standards. Analyzed premium/loss databases and developed dashboards to effectively manage risks and performance (MMA). Analyzed UCCANS benefits and contributions databases, identifying anomalies for better risk management. Processed Groupama’s dependency database and developed key indicators for risk evaluation and claims management.

Within the Actuarial Department: Segmented the insured population into homogeneous risk groups based on both frequency and claims experience (including recurring and atypical claims). Cross-checked the zonal data and performed analysis at a common level of granularity. Selected and cross-referenced the most relevant variables/modalities, utilizing both internal data and external sources (such as INSEE databases and geomarketing data). Analyzed and modeled claims experience by type of coverage (theft, damage, bodily injury/material liability, and glass breakage). Presented results using MAPINFO and applied commercial smoothing techniques.