Course Agenda

Agenda

Course Agenda

Day One

09:00

Registration and refreshments

09:30

Model risk management & governance

  • History of model risk management
  • Definitions of models/what are the starting points?
  • OSFI guidelines
  • Capturing model interconnectivity
  • Governance – lines of defence
  • Coverage of model workflows – gaining a competitive advantage

Yaping Jiang, Managing Director, JW Matrix

11:00

Morning break

11:30

How to build a model risk management framework

  • Development, quantification, integration, implementation
  • Setting risk appetite, policy & standards for model risk
  • Model inventory process
  • Model lifecycle management (development, validation, implementation, use, periodic review)
  • Estimating capacity for risk
  • Application to stress testing models

Dennis Bennett, CEO, Model Risk Manager’s International Association 

1:00

Lunch

2:00

Model validation, performance monitoring and analysis

  • What is validation?
  • Improving the models
  • Validation tools
  • Performance analysis reviews
  • How to quantify model limitations
  • Vendor and third-party model validation
  • Model Performance monitoring
  • Challenges managing performance monitoring activities
  • Best practices
  • Opportunities moving forward

Basil Singer, Founder/ Consultant, Juhuo Tech Inc.

3:30

Afternoon Break

4:00

Model risk management for pricing models

  • Best approach to pricing models
  • Products in balance sheet
  • Market of products vs. pricing and hedging
  • Source of valuation adjustments in pricing
  • Identification and mitigation of model and input risk
  • Establishing pricing and validation framework

5:30

End of day one

Day Two

09:00

Refreshments

09:30

Model risk management of non-pricing models

  • Compliance models (AML)
  • Retail models (credit scoping/marketing)
  • IFRS 17 models
  • IFRS 9 overview & progress since implementation
  • The similarities and differences of CECL compared to IFRS 9 and other regulatory credit models?
  • Sources of model risk in IFRS 9 models
  • What new strategies need to be put in place for testing IFRS 9 models and assumptions?

Dr. Ridha Mahfoudhi, Partner, PwC

11:00

Morning break

11:30

Utilizing machine learning for model validation and monitoring of valuation models

  • Why banks need larger validation throughput and how to use AI to speed up
  • Measuring data quality with ML
  • Building AI challenger models for model risk uncertainty measurement
  • Generating test scenarios with ML
  • Solving PDE's with deep reinforcement learning
  • Validation with AI of market data generation algorithms (IR curve building, volatility surface construction)
  • Monitoring valuation models with ML (PnL & XVA)

Jos Gheerardyn, CEO, Yields.io

1:00

Lunch

2:00

The Validation of Machine Learning Models for the Stress Testing of Credit Risk

  • Introduction and motivation
  • Recent advancements
  • The modeling validation function and issues in ML / AI modeling methodologies
  • Model validation common challenges and potential solutions in ML / AI modeling methodologies
  • Challenges in ML / AI model management
  • Emerging trends: quantification of model risk in ML / AI modeling methodologies
  • ML / AI model validation for stressed credit loss

Dr Michael Jacobs, Senior Quantitative Analytics & Modelling Expert, PNC

3:30

Afternoon Break

4:00

Model risk into the future

  • Applying models to new challenges
  • Data challenges
  • Automation vs. human judgment
  • Big data and advanced analytics
  • Treatment and governance of near-models and non-models
  • Future of regulation; possible futures
  • Further evolution of models

Dr Alex Shipilov, Managing Director, Risk and Regulatory Compliance Practice Leader, Canada Protiviti

5:30

End of Course