Risk model validation: implementation tools and techniques

  • Quant and model risk
View Agenda

Key reasons to attend

  • Gain skills and tools for effective risk model validation 
  • Focus on design, implementation and validation of models 
  • Build own roadmap for validation and explore next steps in the journey 

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Customised solutions

Does your team require a tailored learning solution on this or any other topic?

Working with the portfolio of expert tutors and Risk.net’s editorial team, we can develop and deliver a customised learning to make the most impact for your team, from initial assessment to final review. 

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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 have the skills needed for successful implementation. 

A case study and examples will solidify 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 journey.  


Pricing options:

  • Early-bird rate: save up to $800 per person by booking in advance (refer to the booking section for the deadline)
  • 3-for-2 rate: save over $2,000 by booking a group of three attendees (applicable to this course)
  • Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber* (use code SUB30)
  • Season tickets: save over $1,000 per person by booking 10 or more tickets (available on selection of courses)

*The 30% subscriber reward discount is applicable only to current Risk.net subscribers. If this criteria is not met, we reserve the right to cancel the booking and issue an invoice for the correct rate. Discounts cannot be applied to already registered participants.

Learning objectives

  • Apply the tools needed for successful design and implementation of risk models 
  • Validate and utilise model results by statistical methods 
  • Perform scenario analysis for credit portfolio models 
  • Demonstrate statistical methods for validating data 
  • 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 14–16, 2024

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

View detailed agenda


November 5–7, 2024

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

View detailed agenda

Tutors

Peter Quell

Head of the Portfolio Analytics Team for Market and Credit Risk in the Risk Controlling Unit

DZ Bank

View bio

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

View bio

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.

Pre-reading materials

The Risk.net resources below have been selected to enhance your learning experience:

A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two news articles a month.

Registration

May 14–16, 2024

Online, Emea/Americas

Price

$2,999

Early-bird Price

$2,199
Ends April 12

November 5–7, 2024

Online, Emea/Americas

Price

$2,999

Early-bird Price

$2,199
Ends October 4
Book now

Enquire about:

  • Agenda and registration process
  • Group booking rates
  • Customisation of this programme
  • Season tickets options

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