Model Risk Management London
A comprehensive overview of the current regulatory landscape of model risk management and best practice approaches for modelling across, risk pricing and credit models.
This model risk management course will take a look at the regulatory guidelines, governance and how to build a model risk management framework for pricing and other model types such as retail. Day two will discuss how machine learning and AI fit in to the picture with valuation models and stress testing credit risk. The training course will close with a session on the third line of defence - the role of audit on model risk management.
The newest regulatory guidelines on model risk management and governance
The impact that libor transition and FRTB has on model risk management
Learn how to gain competitive advantage through artificial intelligence techniques for stress testing credit risk and valuation models
Learn about the processes for building an effective model risk management framework
Gain an insight into the best approaches to the various types of models (pricing, risk, forecasting and compliance)
Learn the role of audit in model risk management and how to create a good control environment
Model Risk Management: Risk, Pricing & Credit Models
The regulatory landscape and governance of model risk
Building a model risk management framework
Model Risk Management for Stress Testing
Model risk perspective on LIBOR transition, FRTB and NMRF’s
Model risk management for pricing models
Model risk management of other modelling types
Machine learning for model validation
Auditing model risk management
Co-Founder and CEO
Jos is the co-founder and CEO of Yields.io. Prior to his current role he has been active in quantitative finance both as a manager and as an analyst. Over the past 15 years he has been working with leading international investment banks as well as with award winning start-up companies. He is the author of multiple patents applying quantitative risk management techniques to imbalance markets. Jos holds a PhD in superstring theory from the University of Leuven (Belgium).
Head of AI - Financial Services | Risk Advisory
Alexander Denev has more than 15 years of experience in finance, financial modelling and machine learning and he is the former lead of the Advanced Analytics & Quantitative Research at IHS Markit. He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation. He is currently writing his third book on Alternative Data in Trading&Investing. Alexander Denev attained his Master of Science degree in Physics with a focus on Artificial Intelligence from the University of Rome, and he holds a degree in Mathematical Finance from the University of Oxford, where he continues as a visiting lecturer.
Masters in Quantitative Finance, Board Member
Rutgers Business School
Tanveer Bhatti advises Ultra-High Net Worth Individuals and has experience at Executive Level at leading banks and have served in a variety of global roles, the most recent being Global Head of Model Risk at Citi. His background is in Model Risk, Market Risk, Counterparty Credit Risk, Valuation, Stress Testing and Treasury Financial Control and he has covered all kinds of risks. Renowned in the risk management community and a frequently sought public speaker, Tanveer is a Mathematical Physicist, Business Administrator and Chartered Accountant by training; he received his undergraduate and postgraduate Degrees in Mathematics from Cambridge University.
Javier Calvo Martin
Javier Calvo Martín is a partner at Management Solutions (MS). He currently leads MS’ office in Germany and is responsible for the relationship with the European Central Bank and the Public Sector industry. During his career, he has led or reviewed a number of projects in global and domestic systemically important financial institutions in the Eurozone and the USA, especially focusing on:
- Model risk management
- Credit risk IRB & IFRS 9 and operational risk (AMA) models development and validation
- Stress testing for internal and regulatory/supervisory processes, such as ICAAP, SREP, CCAR and EBA/ECB exercises
- Economic capital modelling
- Risk organisation and governance, and risk appetite
He also leads Management Solutions’ Research and Development function and co-leads operations in France.
CPD / CPE Accreditation
This course is CPD (Continued Professional Development) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event.
This course is CPE (Continuing Professional Education) accredited and will allow you to earn up to 12 credits. One credit is awarded for every hour of learning at the event in accordance with the standards of the National Registry of CPE Sponsors.
Comprehensive two day training on the current regulatory landscape of model risk management and best practice approaches for modelling across risk, pricing and credit models.
Join us for our Model Risk training course with sessions covering the best approaches to building a model risk framework, model validation & performance analysis, the use of machine learning for model validation and monitoring of valuation models, as well as a look at the future challenges and trend