Course Agenda

Agenda

Course Agenda

08:3009:00

Registration and refreshments

08:30 - 09:00

09:0010:30

Model risk management & governance

09:00 - 10:30

  • Definitions of models and model risk
  • Model types and model approaches
  • Sources and key drivers of model risk
  • Evolution of model risk management
  • Regulatory expectations and best practices: SR11-7 and beyond
  • Model governance framework including three lines of defence
  • Coverage of model workflows including model interconnectivity

10:3010:45

Break

10:30 - 10:45

10:4512:00

How to build a model risk management framework

10:45 - 12:00

  • 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

12:0013:00

Lunch

12:00 - 13:00

13:0014:30

Model risk management for stress testing

13:00 - 14:30

  • Interconnectedness of models and network effects
  • Stress testing and the P&L distribution
  • Sensitivity tests
  • Bayesian averaging of the models’ outcomes
  • Technology bottlenecks

14:3014:45

Break

10:30 - 10:45

14:4516:15

Model risk perspective on Libor transition, FRTB and NMRFs

14:45 - 16:15

  • Libor transition and FRTB: impact on the risk modelling
  • Estimating risk factors: the importance of data
  • FRTB: NMRFs and P&L attribution test – case study
  • Libor: alternative RFR – case study
  • Effectively delivering FRTB and Libor in parallel

08:3009:00

Refreshments

08:30 - 09:00

09:0010:30

Model risk management for pricing models

09:00 - 10:30

  • Market of products
  • Applying model risk framework to pricing models
  • Validation approach to pricing models
  • Model performance tracking

10:3010:45

Break

10:30 - 10:45

10:4512:00

Model risk management of credit models

10:45 - 12:00

  • Retail models (credit scoring/marketing)
  • CECL overview & lessons learned 
  • The similarities and differences of CECL compared to other regulatory credit models
  • Sources of model risk in CECL models
  • What new strategies need to be put in place for testing CECL models and assumptions?
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).

12:0013:00

Lunch

12:00 - 13:00

13:0014:30

Auditing model risk management

13:00 - 14:30

  • Role of internal audit
  • Common weaknesses in model risk management
  • What is a good control environment?
  • Should audit duplicate the role of model risk management?

14:3014:45

Break

10:30 - 10:45

14:4516:15

Model risk into the future

14:45 - 16:15

  • Emerging dangers from current practices in model risk
  • The impossible ask – how to increase breadth of coverage, depth of validation, while controlling costs?
  • Operating models for different size banks
  • Using technology – what in model validation can be automated?
  • Model risk management of machine learning tools or AI applications
  • Winning back the original goal – managing model risk