Farhad Tahirov

Climate Risk Modeling per EU Taxonomy.

• Performed Macroeconomic-scenario analysis for PiT PD conversion of TTC PDs, mainly through multiplier approach.
• Cross-validated time-lag between DFR and Macro parameters; Developed a regression model to see the interchange in between DFR and Macros.
• Predicted and adjusted forward looking PDs.

• Took a dedicated period for self-learning and upskilling in data analytics.
• Learned and applied web scraping techniques for automated data collection.
• Currently analyzing time-series data from publicly available sources, focusing on real estate market trends and macro-environmental indicators.
• Enhanced skills in Python (Pandas, BeautifulSoup/Scrapy), data visualization, and exploratory data analysis.

Developed AI model for apartment pricing.

Validated Early Warning system model.

• Collected Loss Data for Loss Given Default.
• Calculated LGD components.
• Calculated Loss Given Default - Economic Loss approach.
• Calculated Loss Given Default - Delta Outstanding approach.
• Performed Calibration Accuracy (PiT, LRA), Discriminatory Power(AUC, GAUC), Stability Tests.
• IFRS9 Staging Calculations.
• IFRS9 PiT LGD/PD calculations.
• Building frameworks for Multiyear Backtests.
• Implemented MoC(Margin of Conservatism) framework on SAS.
• Developed Macros for Contingency Table calculation.
• Designed pipelines, Automated tests in SAS macros.
• Performed RWA tests on Portfolios: Large Corporate( 6 billion impact), Commercial Property Finance, Trade & Commodity Finance.

• Worked in Agile Environment.
• Involved in Data Quality management for Risk Data Mart.
• Performed investigation over code in production using Teradata SQL.
• Tracked down and resolved bugs in fast-paced production environment.
• Performed Tests given Business Requirements.
• Performed system testing and troubleshooting, documenting issues and resolutions.
• Collaborated with stakeholders to identify and resolve issues.
• Contact : -Aet Peterson aet.peterson@swedbank.ee

• Communicated with Business Stakeholders to identify changes in business conditions.
• Conducted research over EBA Guidelines to identify requirements for Credit Risk Models.
• Collected Data applicable for LGD (Loss Given Default) and CCF (Credit Conversion Factors) methodology under Advanced IRB Approach.
• Cooperated building Credit Scoring (Probability of Default) Models.
• Developed Decision Tree Model for estimation of CCF values.
• Deciphered the effect of NDOD on CCF values.
• Calibrated Model estimates.
• Applied Bootstrap Methodology to extract Confidence Intervals for each segment.
• Applied Margin of Conservatism over calibrated Estimates.
• Evaluated the Model by Applying MAD, PSI as well as Spearmann's Rank Correlation tests.
• Estimated the Impact to the overall Portfolio's Risk Weighted Assets as well as Expected Loss.
• Developed monitoring mechanism for Model in production.
• Forwarded the model for ECB and SFSA's approval.
• Contact : - Modi Lovenvall Crafoord modi.lovenvall.crafoord@swedbank.se