Risk model validation: implementation tools and techniques
View AgendaKey reasons to attend
- Acquire the skills and tools required for effective risk model validation
- Focus on the design, implementation and validation of models
- Build a road map for validation and explore the next steps in the journey
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About the course
Build your knowledge of risk model validation through understanding key elements of risk models and best practices for creating a validation framework in your institution.
Participants will gain insight into the stages of risk model validation including the roles, expectations and general rules of a validation framework. Combined with a deeper understanding of risk models and the role of statistics in risk model validation, participants will acquire the skills needed for successful implementation.
Case studies and examples will solidify the concepts presented by subject matter experts regarding risk model validation for different areas of risk, such as market risk, credit portfolio models and credit risk. Participants will also explore model governance, inventory and next steps in their risk model validation journeys.
Pricing options*:
- Early-bird rate: save up to $800 per person by booking in advance
- 3-for-2 rate: save over $3,000 by booking a group of three attendees
- Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber
- Season tickets: cost-effective option for groups of 10 or more. Learn more
*T&Cs apply
Learning objectives
- Apply the tools required for the successful design and implementation of risk models
- Utilise statistical methods to validate model results
- Perform scenario analysis for credit portfolio models
- Identify model risk governance and model inventory strategies
- Proactively use machine learning techniques to benchmark market risk models
Who should attend
Relevant departments may include but are not limited to:
- Risk model validation
- Model risk
- Risk management
- Market / credit risk management
- Stress testing
- Model review
Agenda
May 13–15, 2025
Live online. Timezones: Emea/Americas
Sessions:
- The origin of risk models
- Elements of risk models and risk model failures
- Building a roadmap for validation
- Toolbox one: machine learning/market risk
- Toolbox two: credit portfolio models
- Toolbox three: credit risk
- Looking back and looking ahead
Tutors:
- Dr Peter Quell, Head of portfolio analytics, DZ Bank
- Dr Christian Meyer, Quantitative analyst, DZ Bank
Tutors
Peter Quell
Head of the Portfolio Analytics Team for Market and Credit Risk in the Risk Controlling Unit
DZ Bank
Peter Quell is head of the portfolio analytics team for market and credit risk in the risk controlling unit of DZ Bank in Frankfurt. He is responsible for methodological aspects of economic capital and model risk.
Prior to joining DZ Bank, Quell was manager at d-fine, where he dealt with various aspects of risk management systems in the banking industry. He holds a MSc in mathematical finance from Oxford University and a PhD in mathematics. Peter is member of the editorial board of The Journal of Risk Model Validation.
Christian Meyer
Quantitative Analyst in the Portfolio Analytics Team for Market and Credit Risk in the Risk Controlling Unit
DZ Bank
Christian Meyer is a quantitative analyst in the portfolio analytics team for market and credit risk in the risk controlling unit of DZ Bank in Frankfurt, where he is responsible for the development of portfolio models for credit risk and spread risk in the banking book and incremental risk in the trading book.
Before joining DZ Bank, he worked at KPMG, where he dealt with various audit and consulting aspects of market risk, credit risk and economic capital models in the banking industry. Meyer holds a diploma and PhD in mathematics, and is on the editorial board of The Journal of Risk Model Validation.
Accreditation
This course is CPD (Continued Professional Development) accredited. One credit is awarded for every hour of learning at the event.
Pre-reading materials
The Risk.net resources below have been selected to enhance your learning experience:
- Risk Model Validation (3rd edition)
- The post-Archegos risk model rebuild begins… slowly
- Europe’s new AI Act threatens supervisory ‘chaos’ for banks
- Rate risk modellers relieved as EU deposits stay sticky
A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two articles.
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