Model risk management: effective implementation
View AgendaKey reasons to attend
- Implement impactful ways to maximise data and analytical abilities
- Identify current trends and regulatory perspective on artificial intelligence (AI) and model risk management (MRM)
- Understand the impact of environmental, social and governance (ESG) factors in the financial model lifecycle
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About the course
This interactive learning experience, led by subject matter experts, explores the current outlook for MRM.
The course offers insight into model risk optimisation, including ways to improve model robustness to withstand market volatility.
Participants will also gain a deeper understanding of the impact of ESG elements on the financial model lifecycle, including model governance and validation in the AI and technology session, providing organisations with the tools to identify and disclose their exposure to various ESG risks.
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
- Evaluate model risk principles, including capturing model interconnectivity
- Understand the optimisation of model risk through ongoing transformation of models
- Implement MRM on derivate and security pricing models
- Identify model validation techniques and approaches in MRM
- Conduct impactful AI applications to typical MRM frameworks
- Implement the impact of ESG factors in the financial model lifecycle including model governance and validation
Who should attend
Relevant departments may include but are not limited to:
- Model risk management
- Model risk
- Pricing models
- Credit models
- Risk management
- Artificial intelligence (AI)
- Technology
- Regulation
Agenda
June 25–27, 2024
Live online. Timezones: Emea/Americas
Sessions:
- Model risk regulatory landscape and framework
- Optimisation of model risk
- MRM for pricing models
- Credit risk model management
- Artificial intelligence (AI) and MRM technology
- Climate and ESG modelling
Tutors
Grigoris Karakoulas
President
InfoAgora Inc
Grigoris has over 26 years of experience in predictive modelling and risk management. He is the president and founder of InfoAgora that provides risk management consulting and more to financial services organisations. He is an adjunct professor in the department of computer science at the University of Toronto.
Prior to founding InfoAgora, Grigoris was working at CIBC as vice president of customer behavior analytics, responsible for customer decisioning and credit risk measurement solutions for adjudicating new customers and proactively managing existing ones. He has been a postdoctoral fellow in the Institute of Information Technology at the National Research Council. He is on the PRIMA subject matter boards for stress-testing and enterprise risk management and has published more than 40 papers in journals and conference proceedings. He holds a PhD in computer science.
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:
- Leveraging a hybrid cloud for better decision‑making - Read article | Risk.net
- Rethinking the model lifecycle: from quick fixes to long-term gain - Read article | Risk.net
- Model risk management: building trust and governance - Read article | Risk.net
A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two news articles a month.
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