Model Risk Management Toronto

Join us for our Model Risk training course with sessions covering the best approaches to building a model risk framework, model validation & performance analysis, the use of machine learning for model validation and monitoring of valuation models, as well as a look at the future challenges and trend

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Model Risk Management

Risk, Pricing and Non-Pricing Models 

Toronto, 25 - 26 September 2019

Course guide          Apply now

This Model Risk Management course will take a look at the OSFI guidelines, governance and how to build a model risk management framework for pricing and non-pricing models such as IFRS 9. It will also explore how machine learning and AI fit in to the picture with valuation models. The training course will close with an important discussion on what the future of model risk could look like. 

What Will You Learn?
  • The newest OSFI guidelines on model risk management 

  • An enhanced knowledge of model risk management governance and how best to prepare 

  • How to gain competitive advantage through artificial intelligence techniques for model validation and valuation models 

  • The processes for building an effective model risk management framework 

  • An insight into the best approaches to the various types of models (pricing, risk, forecasting and compliance) 

  • How to define your model risk appetite, quantify and monitor performance 

  • What the future looks like for model risk in relation to data and regulation 

View course guide

Who Should Attend

Relevant departments may include but are not limited to:

  • Model Risk 

  • Model and Pricing Validation 

  • Internal Audit/Model Review

  • Quantitative Analysis 

  • Risk Control 

  • Credit and Market Risk 

View pricing options

Course Highlights
  • Model Risk Management & Governance  

  • How to Build a Model Risk Management Framework 

  • Model Validation & Performance Analysis 

  • Model Risk Management for Pricing Models

  • Model Risk Management of Non-Pricing Models 

  • Utilizing Machine Learning for Model Validation and Monitoring of Valuation models  

  • A Deep Dive into Validation of Natural Language Processing Models 

  • Model Risk into the Future 

View course agenda

Course speakers

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Dr. Yaping Jiang

Managing Director

JW Matrix Inc

Dr. Yaping Jiang is currently a managing director in JW Matrix Inc., a consulting company that provides a wide range of services in financial modeling, derivatives valuation and risk analysis, end-to-end risk management structures and practices including market, credit, operational, and model risk management; model validation, independent price verification, economic capital and regulatory capital calculation, compliance assessment against regulatory requirements including Basel II and III requirements and regulatory guidelines over model risk management.

Dr. Jiang has a Ph.D degree in Mathematics and is a certified financial risk manager (FRM). She has been worked in major Canadian Banks for over 20 years and has in-depth knowledge and intensive experience in the following areas:

  • Model validation and model risk management over the model life-cycle process
  • Valuation of various derivatives products
  • Advanced models for market risk (Value-at-Risk or IMA, FRTB), counterparty credit risk (IMM), operational risk models (AMA), internal risk rating for whole sale and commercial portfolios, non-retail and retail credit risk parameters (PD, LGD, and EAD)
  • Trading market risk management and counterparty credit risk management
  • Independent price verification for trading products
  • Enterprise risk management and operational risk management
  • Back testing and stress testing  
  • Economic capital and regulatory capita calculation and modeling
  • Expected credit loss (ECL) estimation
  • Compliance assessment against various regulatory requirements including Basel II and III, ICAAP, SR 11-7, OSFI E-23
  • Internal Audit processes and practices for all aspects of quantitative areas
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Olga Streltchenko

Director

Export Development Canada

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Grigoris Karakoulas

President & Founder

InfoAgora Inc

Grigoris Karakoulas is the president and founder of InfoAgora Inc. that has provided risk management consulting, prescriptive analytics, RegTech solutions (CECL/ IFRS9/IRRBB/Basel III) and model risk management services to Fortune-500 financial institutions with multi-million dollar benefits. He is also Adjunct Professor in the Department of Computer Science at the University of Toronto. Grigoris has published more than 40 papers in journals and conference proceedings in the areas of machine learning, risk management and predictive modelling in banking. He is on the PRMIA subject matter boards for Stress Testing and Enterprise Risk Management. He holds a PhD in Computer Science (Artificial Intelligence).

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Greg Kirczenow

Senior Director

RBC

Greg is Senior Director in Enterprise Model Risk Management at RBC. He has a decade of experience in market and model risk management, with specialization in enterprise and retail risk. In his present role, Greg is leading efforts related to responsible AI practices, as well as development of validation techniques both for AI and using AI.

Ali Fathi

Senior Manager, AI Research

RBC

Ali is Senior Manager Ai Research at RBC Enterprise Model Risk Management Group. His focus is on ML research and testing methodology development.

CPE Accreditation

CPE Member

CPE Accreditation

This course is CPE (Continuing Professional Education) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event in accordance with the standards of the National Registry of CPE Sponsors.

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