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Model Risk Management: Regulatory Landscape, Industry Challenges and Moving Forward

Speaker: Ram Ananthapadmanban 

CQF Institute is proud to bring you a free talk with Ram Ananthapadmanban on Model Risk Management: Regulatory landscape, industry challenges and moving forward. 


Model risk arises from errors in the design, development and implementation of models, leading to significant economic or reputational losses for financial institutions, if left unchecked. There has been heightened scrutiny from regulators on model risk in the aftermath of the global financial crisis. Furthermore, with the advent of AI and machine learning, a multitude of modelling approaches are being used in areas such as algorithmic trading, credit scoring, traded risk management, anti money laundering and fraud detection.  This has created its own set of challenges for the industry as they come to grips with how best to manage model risk in the future. During this talk we will cover:

  • What is model risk and why is it important?
  • The regulatory landscape for model risk management
  • The model lifecycle and model risk management framework
  • Model risk management for traditional models vs. machine learning models
  • The key challenges facing financial institutions


Ram Ananthapadmanban Bio

Ram is a Senior Quantitative Lead within the Risk & Analytics practice at CRISIL, focusing on model risk management, regulatory interpretation/assessment and algorithmic trading. He previously worked at Avantage Reply, where he was Head of the Quantitative Practice across Europe. He has over 15 years’ experience working on critical risk and regulatory initiatives within Global financial institutions covering model risk, market risk, counterparty credit risk, derivatives pricing, wholesale credit risk, algorithmic trading, stress testing, ICAAP, Recovery planning and liquidity risk.

Ram holds an Economics degree from the London School of Economics, a Master’s degree in Economics from New York University, a Master's degree in Risk Management and Financial Engineering from Imperial College London, he is a PRMIA certified Professional Risk Manager (PRM) and has completed the Certificate in Quantitative Finance (CQF) qualification.