Vicky Rathee

Credit Risk and Data Analytics professional with 4+ years of experience in SAS, SQL, Python, Power BI, and Excel, supporting credit risk assessment, IFRS-9 ECL analysis, PD modeling, and financial modeling. Experienced in data preparation, model support activities and skilled in translating complex financial and risk data into actionable business insights.

IFRS-9 ECL & Credit Risk Analytics Project

• Supported IFRS-9 Expected Credit Loss (ECL) analysis by assisting in PD estimation, staging logic, and portfolio-level loss calculation using SAS and SQL.
• Performed WOE-based variable analysis, fine and coarse classing, and logistic regression to support Probability of Default (PD) modeling.
• Conducted vintage and roll-rate analysis to assess delinquency migration and monitor credit portfolio performance.
• Applied macro-economic overlays to convert TTC PD to PIT PD in line with IFRS-9 requirements.
• Built Power BI dashboards and management reports to track ECL trends, delinquency buckets, and portfolio risk metrics.

Python Data Preparation & Modeling Project

• Performed data cleaning and preprocessing using Python (pandas, NumPy), including missing value treatment, data validation, and consistency checks on financial datasets.
• Conducted outlier detection and treatment using statistical techniques such as IQR and percentile capping to improve data stability.
• Applied dummy variable encoding for categorical features and performed correlation analysis to identify multicollinearity and reduce redundant variables.
• Executed feature engineering by creating derived risk indicators and normalized variables to enhance model interpretability and performance.
• Split data into training and testing sets and developed baseline predictive models using scikit-learn.