Tanmay Sanjeev

• Advanced methodologies were developed to detect and diagnose anomalies within large-scale operational systems, enhancing efficiency and reducing risks. Extensive datasets were analyzed using machine learning techniques such as Variational Autoencoders and Gaussian Mixture Models to uncover unusual patterns that could signify potential issues. This led to anomalies detection rate by 60% reducing downtime for maintenance.

Relevance to Financial Analysis:

My thesis work enhanced my ability to analyze large datasets and detect anomalies using statistical models and machine learning—skills directly applicable to financial data analysis and risk assessment. This expertise aligns with the growing use of AI in financial analytics for predictive modeling and algorithmic trading, preparing me to contribute effectively as a financial analyst.

• Developed automation scripts for data analysis, enhancing the accuracy of results.
• Implemented and deployed three robotic process automation (RPA) solutions operating in unattended mode, collectively saving 150 man-hours per month (50 hours per solution).Conducted thorough testing of automation systems, ensuring optimal performance and reliability.
• Worked closely with project managers to ensure timely delivery of all assigned tasks related to automation initiatives.

• Analyzed financial data and prepared comprehensive reports utilizing advanced MS Excel functions such as Pivot Tables and VLOOKUP.
• Conducted risk analysis by evaluating loan eligibility, credit history, debt coverage ratios, and amortization schedules to inform lending decisions.
• Performed comprehensive risk assessments for individuals and corporations before sanctioning mortgage loans, enhancing portfolio quality.
• Leveraged Power BI for data visualization, generating reports on disbursed loan products and monitoring their current status.
• Participated actively in periodic reviews of account exposures against established limits, ensuring prompt corrective actions where necessary.
• Improved credit risk assessment processes by implementing advanced data analysis techniques and tools.
• Reduced portfolio delinquency rates through stringent monitoring of credit policies and procedures.

Key Achievements:

• Significantly grew the Non-Resident Indian loan portfolio from 120 to 200 applications per month, resulting in a monthly revenue increase of $2 million.
• Received the Best Underwriter award consecutively in 2019 and 2020 for excellence in financial analysis and risk management.