Yuvraj Singh Jadon

Responsible for model validation and development within the Unsecured Credit Risk, Secured MPOL, Mules Fraud, and Application Scorecard models across various asset classes, including PD, EAD, LGD, and other credit risk models.

Projects:

• Macroeconomic Risk Driver Analysis Tool
  Led a team of 3 analysts in developing a Python-based tool to analyze and quantify macroeconomic risk drivers using multiple advanced algorithms such as Z-score, correlation analysis, lag analysis, regression analysis, and Monte Carlo simulation.
  Developed a Python library, including an API to extract data from the Office of National Statistics (ONS), now widely used by the Model Risk Office (MRO) for the validation of various models.
• Unsecured Cards EAD Challenger Model
  Developed a challenger model for the transactor/revolver split within Unsecured Cards EAD, achieving a 10% improvement in R-squared over the 1LOD model by implementing Hyper Parameter Tuning (HPT) in linear regression and analyzing L2 alpha regression for better outcomes.
• Downturn RDS Model
  Overcame data limitations by creating a proxy flag for the transactor/revolver split in downturn periods, using available variables and applying Logistic Regression, Decision Trees, Random Forest, and Gradient Boosting Machine (GBM) algorithms.
  Achieved an accuracy of 91.15% with the GBM model, significantly improving the bank's predictive capability in downturn scenarios.
• Model Validation
  Validated a variety of models across the bank’s portfolio, including Cards RSP, Cards PD, Loans Downturn, Mules Fraud, and Secured MPOL IFRS9, ensuring compliance with internal and regulatory risk management frameworks.

Gained hands-on experience in statistical analysis, data visualization, and data quality assessment using Python, SQL, and Tableau, contributing to the improvement of data analysis processes and ensuring high data reliability.

• Acquired proficiency in using Python, SQL, and Tableau for statistical analysis, data visualization, and reporting.
• Conducted comprehensive data quality assessments and implemented effective data cleansing strategies to improve the reliability and accuracy of datasets.
• Actively participated in team meetings and brainstorming sessions, offering insights and ideas to enhance data analysis methodologies and optimize workflows.
• Developed strong communication skills by preparing and delivering clear, concise, and insightful reports and presentations to stakeholders, ensuring alignment with business objectives.
• Continuously expanded knowledge in data analysis by engaging in self-directed learning, staying up-to-date with industry trends, best practices, and emerging tools.

• Developed a comparative rating system to streamline the quoting and comparison of question problems.
• Produced Quantitative Aptitude content and analyzed user data from 100,000+ individuals using Excel and Power BI to generate dashboards for senior management.
• Provided insights that contributed to a 170% increase in user engagement.