M N Likhith Urs

About M N Likhith Urs

I am a results-driven professional with 1.5 years of experience in credit risk and 2.5 years in data analysis within the banking sector. My expertise lies in developing and validating credit risk models that help financial institutions manage risk and meet regulatory requirements while aligning with business objectives. In my current role, I specialize in creating and refining models such as Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), ensuring robust risk assessment and accurate forecasting. I am well-versed in regulatory frameworks such as Basel and IFRS 9, which guide my approach to building compliant and effective risk management strategies. Leveraging my background in data analysis, I bring strong data manipulation, statistical analysis, and machine learning capabilities using tools like Python, R, and SQL. My experience in stress testing and scenario analysis further supports my ability to prepare institutions for diverse economic conditions, safeguarding against potential credit losses. Key Skills: Credit Risk Modeling (PD, LGD, EAD) Regulatory Compliance (Basel IFRS 9) Data Analysis and Statistical Modeling Machine Learning and Predictive Analytics Stress Testing and Scenario Analysis Programming (Python, SQL) Risk Management and Mitigation Passionate about both data and risk management, I continuously seek to apply innovative techniques and insights to drive effective credit risk decisions that contribute to the institution\'s overall success.

Experience

1. Customer Support Associate

   Karnataka Grameena Bank

   Apr 2022 — Present · Mysore, IN

   Credit Risk and Data Analyst – Banking SectorDevelop and validate credit risk models including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), ensuring robust risk management aligned with business objectives.Ensure compliance with regulatory frameworks such as Basel and IFRS 9, delivering models that meet industry standards.Conduct stress testing and scenario analysis to assess portfolio resilience under varying economic conditions and mitigate potential credit losses.Utilize Python, SQL, and R for advanced data manipulation, statistical analysis, and machine learning to improve forecasting and decision-making.Collaborate with stakeholders across teams to translate business requirements into actionable risk insights, contributing to well-informed financial strategies.Monitor model performance and implement continuous improvements, ensuring models remain accurate, reliable, and aligned with current market trends.Apply innovative approaches in predictive analytics to enhance credit risk management processes and drive institutional success.Key Achievements:Spearheaded the creation of multiple PD, LGD, and EAD models, improving risk forecasting accuracy by [22]%.Enhanced compliance by integrating IFRS 9 standards into existing models, meeting regulatory deadlines ahead of schedule.Identified and mitigated potential risks through stress testing, safeguarding the institution from unforeseen losses during volatile economic periods.Skills & Tools:Credit Risk Modeling (PD, LGD, EAD)Regulatory Compliance (Basel IFRS 9)Data Analysis and Statistical ModelingMachine Learning and Predictive AnalyticsStress Testing and Scenario AnalysisProgramming (Python, SQL, R)Risk Management and Mitigation

Education

• Vijaya Vittal Institute of Technology, BANGALORE

  12

  2012 — 2013

• PES College of Engineering, Mandya

  Mechanical engineering

  2014 — 2018

• Kendriya Vidyalaya

  10

  2011 — 2012