Model Risk Australia

Model Risk Australia

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Stephen Edney

Head of Market Risk Quantitative Support

NATIONAL AUSTRALIA BANK

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David Maher

Associate Director, Market Risk

NATIONAL AUSTRALIA BANK

David is currently the Market Risk Oversight lead for Fixed Income and Interest Rate Derivatives. Prior to this he worked for 10 years as a quantitative analyst in model validation and development. This also included 4 years on NAB’s trading floor in London.  More recently, he has been implementing Machine Learning in the market risk space, including  applications to FRTB.

David holds a PhD in Pure Mathematics from UNSW, and a BSc from Macquarie University, Sydney.

Song Ling Ooi

Senior Manager – Pricing & Modelling

AMP

Song leads the Pricing & Modelling team within the Chief Investment Officer function of the Australian Wealth Management business unit in AMP. She is the Senior Manager responsible for the development of the pricing methodology and pricing recommendations for product developments – in particular for the North Guarantee.

Song is also responsible for overseeing the development and assurance of complex models that support both hedging and pricing activities. Having prior data and modelling experience in business areas including Customer Analytics, Hedging Strategy and Operations,  Song understands that a strong risk culture and risk management framework is essential for teams to be able to safely operate in a fast-moving environment that allows for innovation at the same time.

Song is currently leading the education of the Model Risk Management concepts across the CIO function. Her goal is to encourage everyone to embrace the importance of working within the risk management framework and motivating everyone to engage, practice and get better at managing model risks.

Model Risk Australia 2019

 

Day 1 - Tuesday 13 August 2019

09:00

Registration and refreshments

09:30

Model risk management & governance

  • Model risk management: history and trends
  • Models matter: definitions and the lay of the land
  • Comprehensive MRM framework
  • Setting key governing principles in the model risk policy 
  • Regulatory expectations and best practices: SR11-7 and beyond
  • Challenger and benchmarking models: "scars" from CCAR
  • Model risk assessment and tiering models by risk ratings
  • Managing model risk across the model lifecycle 

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 

13:00

Lunch

14:00

Model validation & performance analysis

  • What is validation? 
  • Improving the models 
  • Validation tools
  • Performance analysis review 
  • How to quantify model limitations 
  • Vendor and third-party model validation 

15:30

Afternoon break

16:00

Pricing models & prudent valuation

  • 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 
  • Prudent valuation 
  • Establishing pricing and validation framework 

17:30

End of day one

 

Day 2 - Wednesday 14 August 2019

09:00

Refreshments

09:30

Model risk management of non-pricing models 

  • Finance models, including treasury models and IFRS 9 
  • Compliance models (AML) 
  • Retail models (credit scoping/marketing) 
  • What does MRM of non-pricing models look like? 

11:00

Morning break

11:30

Model validation for CECL 

  • CECL overview & implementation schedule 
  • Similarities and differences of CECL compared to IFRS 9 and CCAR
  • Sources of model risk in CECL models, from macro forecasting to model design and usage 
  • What new strategies and techniques need to be put in place for testing CECL models and assumptions? 

13:00

Lunch

14:00

Utilizing machine learning for model validation

  • What is Machine Learning (ML) and Artificial Intelligence (AI) and how to embrace it in the context of Model Validation? 
  • How to validate an ML/AI model according to SR11-7 
  • How does ongoing monitoring for ML/AI look like?
  • Regulatory context for ML/AI models (US and EU)

15:30

Afternoon break

16:00

Model risk into the future

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

17:30

End of training course