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Course Agenda
Agenda
Course Agenda
08:30 – 09:00
Registration and refreshments
09:00 – 10:30
Model risk management & governance
- Definitions of models and model risk
- Model types and model approaches
- Sources and key drivers of model risk
- Evolution of model risk management
- OSFI guidelines and other regulations on model risk management
- Model governance framework including three lines of defence
- Coverage of model workflows including model interconnectivity
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
10:30 – 10:45
Break
10:45 – 12:00
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
Olga Streltchenko is a risk management professional who provides strategic, quantitative, and technical expertise. Her focus areas are risk governance, modelling, and data science. She holds a Ph.D. in Computer Science from University of Maryland Baltimore County (UMBC) where her research was focused on exploring trading dynamics in a derivative securities market and resulted in 3 peer reviewed publications. After graduation Olga joined the financial industry where her experience includes Bank of Montreal (BMO), Royal Bank of Canada (RBC), Ontario Teachers’ Pension Plan (OTPP), S&P Capital IQ, and EDC. Most recently Olga built and led a model risk management function which laid the foundations of model governance, and validated credit risk models driven by the international financial reporting requirements (IFRS).
12:00 – 13:00
Lunch
13:00 – 14:30
Model risk management for stress testing
- Interconnectedness of models and network effects
- Stress testing and the P&L distribution
- Sensitivity tests
- Bayesian averaging of the models’ outcomes
- Technology bottlenecks
14:30 – 14:45
Break
14:45 – 16:15
Model risk perspective on Libor transition, FRTB and NMRFs
- 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
08:30 – 09:00
Refreshments
09:00 – 10:30
Model risk management for pricing models
- Market of products
- Applying model risk framework to pricing models
- Validation approach to pricing models
- Model performance tracking
As Managing Director in Enterprise Model Risk Management (EMRM), Jing Zou is responsible for validating models in Securitized Products, Pre-Provision Net Revenue, Retail Credit models, and interest rate derivatives models. She also developed Comprehensive Capital Analysis and Review (CCAR) model fragility analysis, which identifies the impact of model uncertainty on capital ratios. She is an invited speaker for many industry model risk management training courses.
Jing joined RBC in 2014 as a Director in local model risk manager, where she was responsible of engaging the business about model risks. Later on, she was promoted to Senior Director and then Managing Director and has expanded the scope to cover the validation of 40% of CCAR models. Prior to joining RBC, Jing worked at Goldman Sachs, Wells Fargo, and Fannie Mae in various quantitative analytics roles covering front office quant, market risk, and model risk areas.
Jing has a Ph.D. in Applied and Computational Mathematics from Princeton University and a B.S. and M.S. in Computational Mathematics in Xi’an Jiaotong University.
10:30 – 10:45
Break
10:45 – 12:00
Model risk management of credit models
- Retail models (credit scoring/marketing)
- 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/CECL models
- What new strategies need to be put in place for testing IFRS 9/CECL models and assumptions?
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).
12:00 – 13:00
Lunch
13:00 – 14:30
Auditing model risk management
- 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?
14:30 – 14:45
Break
14:45 – 16:15
Model risk into the future
- 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