Evolution of model risk management and use of technology
MODEL RISK MANAGEMENT EUROPE
2nd Annual | 25-26 November, 2020 | London
GLOBAL REGULATION
Interpretation, application and impact of global regulatory changes
MODEL DEFINITION
Defining a model and incorporating qualitative aspects
QUANTIFICATION
Measuring and quantifying model risk and gaining a holistic view
CONTROLS AND GOVERNANCE
Enterprise wide model governance frameworks and adapting to change
AI AND MACHINE LEARNING
Using capabilities for AI and machine learning for model risk management
FUTURE OF MRM
Future state of model risk management and uses of technology
Slava Obraztsov
Global Head of Model Risk
Nomura
Grazia Rapisarda
Head of Model Risk
Fidelity International
Andreas G. Anastasiou
Audit Director – Model Risk Management
Citi
Azar Khurshid
Director – Global Risk Management
Mizuho
Apurva Anand
Director – Model Risk Management
Barclays
Jens Jakob Rasmussen
Head of Model Validation
Nordea
Giles Spungin
Global Head of Risk Analytics
HSBC
Fabien Choujaa
Global Head of Algorithmic Trading Model Risk Management
Morgan Stanley
Diederik Fokkema
Head of Model Risk Oversight
ING
Jelle Groeneveld
Head of Model Validation
Rabobank
CAN YOUR ORGANISATION CONTRIBUTE?
Please contact the Center for Financial Professionals today to discuss how we can deliver your thought-leadership at the event, help you generate leads, and provide you with unique networking and branding opportunities. For more information on what we can offer, please contact sales@cefpro.com or call us on +44 (0) 20 7164 6582 where a member of the team will be happy to tailor the right package for you.
08:00 registration and breakfast
08:50 Chair’s opening remarks
GLOBAL REGULATION – PANEL DISCUSSION
09:00 Reviewing the global regulatory landscape, interpretation of rules and demonstrating compliance
- Applying regulation and demonstrating effective challenge
- Satisfying regulators with limited resources
- New sets of model requirements across regulatory guidelines
- Assessing the impact on model risk
- Standardising requirements and identifying minimum and common ground
- EBA roadmap: Revamping model suites to fit definition of default
- Basel 3 changes
- End to end process developing, validating and building internal controls
- Deviations across jurisdictions
- SR 11-7: Modeling UK frameworks on US best practice
Slava Obraztsov, Global Head of Model Risk, Nomura
Naz Jhalli, Deputy Head of Balance Sheet Risk Control, Nordea
IMPACT OF REGULATION
09:50 Impact of regulatory changes to model risk management and validation of model usage within the framework
- FRTB validation challenges
- Impact of LIBOR changes to FRTB timelines
- Observable data requirements
- Establishing boundaries between trading and banking book
- Migration to new reference rates from LIBOR
- Standard vs. multiple curves across portfolios
- Validation challenges with transition
- Capturing historical market data
- Offsetting volatility in transition period
- Implementation and validation of updated models
- Recalibration of models to reflect new benchmarking curves
Naz Jhalli, Deputy Head of Balance Sheet Risk Control, Nordea
10:30 Morning refreshment break and networking
DEFINING A MODEL
11:00 Definition and classification of a model under global guidelines and treatments across the institution
- Identifying automated processes as models
- Uniform definition of a model
- When to adopt model risk principles
- Use of US definition of anything with input and output processing element
- Underlying risks classifying as a model
- Emphasis on risk captured when defining
Daniel Hoyt, Head of Model Validation, Euroclear
11:40 What is a model? Is there a need for a standard definition?
- How to classify analytics that carry model risk and assess their materiality
- What is a tool or a calculator and how do we manage the inevitable ‘grey areas’ in model discovery?
- How do we classify models embedded in AI solutions?
- How do we ensure completeness of the model inventory?
- The importance of applying proportionality in control design
- Do we need to independently validate expert judgement models?
- What controls are appropriate for managing risks attached to tools that do not carry model risk?
Grazia Rapisarda, Head of Model Risk, Fidelity International
12:20 Lunch break and networking
GLOBAL FRAMEWORK – PANEL DISCUSSION
13:20 Building out model risk management and alignment of global model risk management frameworks
- Specialising by type of underlying risk
- Effectiveness of managing the model risk of a global institution
- Supervision of global framework
- Managing diversity of models from HR to capital requirements
- Model risk as a global discipline
- European vs. US requirements
- Understanding model risk as a discipline
- Holistic oversight of model risk
- Applying principles across model inventory
- Embedding a risk mitigation mindset
Andreas G. Anastasiou, Audit Director – Model Risk Management, CITIGROUP
Steve Hatton, Head of Finance Model Control Office, Barclays
Azar Khurshid, Director – Global Risk Management, Mizuho
MEASUREMENT AND QUANTIFICATION
14:10 Measurement and quantification of model risk: Aggregating model risk for a holistic view
- Identification and measurement of risks after validation
- Reporting and monitoring of key metrics
- Setting and articulating risk tolerance
- Identifying metrics to monitor
- Measuring model risk and what to do with the information
- Articulating model risk rating
- Model risk quantification and communication to the board
- Understanding and measuring uncertainty
Apurva Anand, Director – Model Risk Management, Barclays
14:50 Model risk tiering
- Importance of risk sensitive MRM
- Fundamental questions (judgmental vs quantitative assessment, ranking vs measurement)
- What inputs: model risk factor candidates
- What outputs: model risk score and metrics
- Model risk tiering methodologies
- Current and future challenges
Fares Triki, Head of Model Risk Management, MUFG Securities
15:30 Afternoon refreshment break and networking
MODEL LIFECYCLE
16:00 Understanding sources of model risk and effective oversight across the model lifecycle and lines of defence
- Defining policies for mitigation of model risk
- Understanding model risk and its sources
- Understanding accountability across the cycle
- End to end workflow/lines of defence
- Approaches to minimise duplication of work
- Setting risk tolerances
Jens Rasmussen, Head of Model Validation, Nordea
MODEL RISK AND AI
16:40 Model risk and AI: An internal audit perspective
- Role of audit
- Use of AI in audit
- Does AI need special governance?
- Understand when AI can be used
- Challenges of AI from an audit perspective
Christopher Hall, Head of Model Risk Audit, HSBC
17:20 Chair’s closing remarks
17:30 End of day one and drinks reception
08:15 Registration and breakfast
08:50 Chair’s opening remarks
PERFORMANCE MONITORING
09:00 Developing robust performance monitoring plans and tracking reliability of models over time
- Documentation and review of conceptual soundness
- Ensuring model is performing to standard in between validations
- Metrics on a live basis: Move to actionable signals to provide a live view
- Tools and technology requirements
- Ongoing performance analysis
Suman Datta, Head of Portfolio Quantitative Research, Lloyds Banking Group
CONTROLS AND GOVERNANCE – PANEL DISCUSSION
09:40 Incorporating control standards and policies for effective and enterprise wide model governance
- Creating and understanding business requirements of changes
- Technical functional requirements
- Risk assumption issues
- Meeting model developments when developing regulations
- Misalignment with internal governance
- Incorporating control standards and policies from the outset
Tanguy Dehapiot, Head of Valuation Risk, BNP Paribas
Suman Datta, Head, Portfolio Quantitative Research, Lloyds Banking Group
Ashutosh Roy, COO Risk Methodology and Head of Market Risk Model Governance, Deutsche Bank
10:30 Morning refreshment breaks and networking
DATA MANAGEMENT
11:00 Refining data infrastructure and data management processes with advances away from traditional models
- Uses of qualitative and unstructured data
- Ensuring standards of non-traditional data
- Reliance on big data with move to new models
- Leveraging data from internal and external sources
- Validating data users
- Ensuring good data to feed into new models
- Developing database for AI
- Training models on internal data
- Building an integrated data structure
- Collecting data across the business and applying cleaning criteria
AI – PANEL DISCUSSION
11:40 Using AI capabilities for model risk management and understanding changes to risk landscape across the business
- Using and integrating machine learning capabilities
- Understanding black boxes for regulatory reporting
- Technology to deploy models
- Human interaction and intervention to validate outputs
- Controls and validation of algorithm and outputs
- Monetary Authority of Singapore fairness, ethics, accountability and transparency standards
- Implementing regulatory principles into AI solutions
- Testing and monitoring AI models post implementation
- Educating top management and gaining buy in
- Building bespoke models for certain portfolios
Giles Spungin, Global Head of Enterprise Analytics, HSBC
Fabien Choujaa, Global Head of Algorithmic Trading Model Risk Management, Morgan Stanley
Diederik Fokkema, Head of Model Risk Oversight, ING
12:20 Lunch break and networking
MACHINE BIAS
13:20 The royal road to explainability in AI/ML
- What are the risks involved with explainability?
- Different perspectives on explainability
- from a customer perspective
- from a supervisory perspective
- from a business perspective
- Tradeoff between business risk and reputational risk
- Example: explainability in the FEC context
- What if it goes wrong? Prepare actions and communication in adverse circumstances.
Diederik Fokkema, Head of Model Risk Oversight, ING
CHANGE CONTROL
14:00 Implementing change control processes to validate models after any changes
- Defining when something needs to change
- Change in a controlled manner
- Changing AI models
- Determining controls, alerts and triggers for change
- Inadequate change controls for AI models
- Ensuring changes are improving the model
DEEP LEARNING
14:40 Implementation and uses of deep learning in model risk management
- Increased statistics
- Regression approach
- Computational capacity of machines
- Customising to comply with regulatory expectations across jurisdictions
- Replicating pricing of exotic options
- Computational efficiency reducing Monte Carlo time
- Identifying a need to retrain
- Controls for changing and retraining
15:20 Afternoon refreshment break and networking
AUTOMATING VALIDATION
15:50 Framework on effective engagement model of 1st Line and 2nd Line
- Resources for validation of all models
- Model documentation for validation
- Coordination across model lifecycle
- Important factors for model validation
- Providing insight to management for decision making
Ashutosh Roy, COO Risk Methodology and Head of Market Risk Model Governance, Deutsche Bank
FUTURE OF MRM – PANEL DISCUSSION
16:30 The future state of model risk management: Evolution of model definition, uses and management
- Organisational design structure
- Model risk as a true risk management function
- Migration to a holistic risk management and advisory function
- New techniques of the future
- Investment levels to get there
- Adapting frameworks for the future of model risk management
- Monetizing model risk and adding value
Jelle Groeneveld, Head of Model Validation, Rabobank
Mourad Berrahoui, Managing Director – Head of XVA, SIMM, Reg Capital, Counterparty Risk, IRC & Credit Risk Modelling, Lloyds Banking Group
Grazia Rapisarda, Head of Model Risk, Fidelity International
17:10 Chair’s closing remarks
17:20 End of Summit
Apurva Anand
Director – Model Risk Management
Barclays
.
Apurva has 14 years’ banking experience having worked with Barclays and HSBC for most of his career. He has worked in the modelling space since 2006, and within model risk management for the last 7 years.
Apurva is currently a model validation Director within the Model Risk Management function in Barclays; responsible for valdiation of stress testing and scenario generation and expansion models
Andreas G. Anastasiou
Audit Director – Model Risk Management
Citi
.
Andreas is an Audit Director based in London with more than 11 years of experience in Credit (Retail and Wholesale), Counterparty Credit, Market risk modelling and Front Office pricing across all major asset classes. He is currently responsible for developing, implementing, managing and providing Subject Matter Expert (SME) assurance activities over Citi’s Model Risk Management (“MRM”) framework within Corporate and Investment, Consumer and Corporate Functions through a combination of risk-based audits, internal and regulatory issue validation as well as business monitoring across the Group. Finally, he is also acting Head of Audit (HoA) for Citi Greece (including Cyprus and Malta) overseeing the franchise’s activities in the country.
Andreas joined Citi Internal Audit (IA) in October 2013 as Vice President (VP) from Barclays IA Quantitative Risk audit team, with experience on reviewing counterparty, credit and market risk capital models (CCR, IMM, AIRB, VaR). In that capacity, Andreas’s responsibilities spanned a broad spectrum of asset classes and included among other things driving the team’s strategy for both the banking and trading books and setting up the IA testing program for all stages of the model lifecycle.
Prior to that, Andreas began his career in December 2007 as a Quantitative Risk Analyst in the Model Validation team for Banco Santander in London focusing on Credit Risk (Retail and Wholesale) as well as Market Risk Models.
Andreas holds an MSc in Economics (Distinction) and PhD in Applied Econometrics-Quantitative Modelling both from University of Reading – UK and a BSc (Distinction) in Chemistry from University of Patras – Greece.
Mourad Berrahoui
MD – Head of XVA, SIMM, Reg Capital, Counterparty risk, IRC & Credit Risk Modelling
Lloyds Banking Group
Mourad Berrahoui will be presenting at Model Risk Management Europe
Fabien Choujaa
Global Head of Algorithmic Trading Model Risk Management
Morgan Stanley
Fabien Choujaa is a senior leader in Algorithmic Trading and Artificial Intelligence with over 15 years of experience across the globe in both areas. Fabien joined the Institutional Equity Division of Morgan Stanley as a Desk Strategist in 2014 and currently heads Algorithmic Trading Model Risk Management for all asset classes globally. Prior to this, Fabien was a Desk Quantitative Analyst at UBS headquarters and held research positions in Artificial Intelligence at IBM and Imperial College London. Fabien Choujaa has a PhD in Machine Learning from Imperial College London for which he received the EPSRC PhD+ Doctoral Prize.
Suman Datta
Head, Portfolio Quantitative Research
Lloyds Banking Group
I head up the Portfolio Quantitative Research function within Lloyds Banking Group Markets division and am
responsible for strategic cross-asset portfolio analytics covering FRTB, Prudential Valuation, Initial Margin, PnL
Attribution and Stress Testing. I am also the business/IT partner for architecting the next-generation risk and
valuation platform to be used by trading, risk and finance functions. My background is in quantitative finance,
technology and business strategy and my key areas of interest are in bank regulation, digitisation and application of
quantitative methods in new areas within finance
Tanguy Dehapiot
Head of Valuation Risk
BNP Paribas
Tanguy has studied at Ecole Polytechnique in Paris and is member of the French Institute of Actuaries. He has been working during his entire career at BNP Paribas, starting as a quantitative analyst on derivatives valuation and risk management measures and then creating the Model Risk Team within the Market Risk department that has defined the model control framework and implemented valuation reserves.
He is the Chief Valuation Risk Officer within the Risk department that is involved in all aspects of valuation governance and more specifically model control including accounting and regulatory aspects. He has been working in industry working groups such as the IASB Expert Advisory panel on Valuation, the Basel Committee Accounting Task Force work, the International Valuation Standard Council (IVSC) as well as the AFME working Group on the Prudent value regulation set by EBA. He has been very active in the XVA debates.
Diederik Fokkema
Head of Model Risk Oversight
ING
After a career in the semiconductor industry, Diederik started his financial services career at ABN AMRO in 2002 leading the Quantitative Consulting and Operations Research Team. This team delivered amongst others all the AIRB validation reports as part of the introduction of Basel II in 2007. After this he moved to Deloitte as a Director to help building the Capital Markets advisory team. He moved to EY in 2010 to lead the Quantitative Advisory Service team for NL as an associated partner. During this time he lead various engagements in the area of credit, market risk, IFRS9 and bank wide stress testing. In 2019 he moved to ING to become Head of Model Risk Oversight, building the team to implement ING’s global model risk management framework. He’s also building the team for validation of AI/ML models as they are used within ING more and more. Diederik studied mathematics at the University of Amsterdam and holds a PhD in numerical mathematics (University of Utrecht). He is a member the committee for innovation of the Dutch Platform for Mathematics. He’s also the founder and president of TopQuants, an association for quants and by quants, organising multiple events for finance professionals. Diederik lives close to Amsterdam with his wife. His three children live and study in Amsterdam.
Jelle Groeneveld
Head of Model Validation
Rabobank
Jelle Groeneveld is an experienced banker with more than 25 years experience in banking. In October 2016, he became Head of Model Validation at Rabobank. Prior to joining Rabobank in 2015, he spent 21 years at ABN AMRO in various roles in risk management, with roles in market risk management, structured finance, sales in Markets ALM and market risk modelling both in Asia and in Europe.
Christopher Hall
Head of Model Risk Audit
HSBC
Christopher Hall has been working in all areas of risk management since 1992. He is a Head of Model Risk, Internal Audit at HSBC.
He has run many projects covering all aspects of risk management in financial institutions, including stress testing, ICAAP development, economic capital and performance measures, liquidity development and the integration into strategic planning & scenario analysis.
Prior to HSBC, Christopher was Head of Market Risk Methodology, Stress Testing and IT Architecture, Risk Consulting and Training at Risk Advisors, CFO of a start up hedge fund and Head of Economic Capital at Barclays Bank.
Christopher has a first class degree in Computing and Statistics, is a Chartered Accountant and has a Masters in Finance from London Business School.
Steve Hatton
Head of Finance Model Control Office
Barclays
Steve’s roles at Barclays have included running Valuation Control for Barclays’ NonCore unit; heading-up the firm’s Solvent Wind Down project; and running Planning & Stress Testing for the Investment Bank. Most recently, he set up the Finance Model Control Office, to assist the Finance function in complying with internal and external model governance requirements. He joined Barclays in 2008, following a first career in academia and seven years in financial services roles spanning credit risk, fixed income analytics, and credit structuring.
Daniel Hoyt
Head of Model Validation
Euroclear
Daniel started his financial services career with Deloitte tax, first in tax and then their quantitative advisory team. After leading this team, Daniel moved to Barclays market risk. In 2012, he was asked to help establish a group-wide validation function for the bank. After a brief stint back in the US, Daniel became head of risk model validation for the securities arm of MUFG in London. In 2018, Daniel relocated again to rebuild and head up Euroclear’s model validation function. Daniel now lives just outside Brussels, with his wife, four children and a cat.
Jens Jakob Rasmussen
Head of Model Validation
Nordea
Jens Jakob Baltzer Rasmussen, Director and Head of Model Validation at Nordea, holds a MSc in Mathematics and Economics from Aarhus University, Denmark and has 20+ years’ experience within the baking sector. Have held various positions across all three lines of defence in Nordic banks. Joined Nordea’s Wholesale Banking division in 2004 working primarily with credit, rates and inflation pricing models and product structuring. In 2016 moved to a role as head of Pricing Model Validation in Nordea’s 2nd line Group Risk function. Currently head of Model Validation, covering modelling areas such as traded and non-traded market risk, counterparty credit risk, liquidity risk and pricing models.
Naz Jhalli
Deputy Head of Balance Sheet Risk Control
Nordea
Naz has been working as a senior leader with experience of Executive, Board level and ECB regulator stakeholder management in a variety of roles in Nordea based in Copenhagen. Naz’s most recent focus has been in supporting Nordea in the transition into the ECB SSM, establishing a Model Risk Management function and as previously head of Group Valuation Control, establishing a Valuation control function.
Before Nordea Naz has worked in London at Morgan Stanley within Valuation Control for interest rate hybrids and with PwC focussing on advisory and assurance for Energy clients. Naz has educational foundations in Physics, which is complimented with almost 20 years of work experience within finance and banking, more specifically within risk and finance, governance, fair value accounting, market and credit risk and model risk.
Azar Khurshid
Director – Global Risk Management
Mizuho
Azar has over 11 years of experience in Financial Risk Management. Currently he is the Global Business director for the FRTB and related Regulatory projects at Mizuho. He also manages the current Internal model for Market Risk. Previously he was at Barclays capital for 7.5 years, where he worked with Equity derivatives risk management and risk reporting and also in counterparty credit risk.
Azar has a doctorate degree in Neuroscience and Masters in Computational intelligence.
Slava Obraztsov
Global Head of Model Risk
Nomura
Slava Obraztsov has been Global Head of Model Risk / Model Validation at Nomura since 2007. His previous roles include Global Head of Model Validation at Bear Stearns, Senior Quantitative Model Risk Analyst at Commerzbank and Head of Risk Analytics at ANZ. He was awarded a PhD in Mathematics from Moscow State University and has held a number of academic positions at Russian and Australian universities.
Grazia Rapisarda
Head of Model Risk
Fidelity International
Grazia Rapisarda is a senior model risk management professional with almost 20 years of experience in the financial services sector. Grazia joined at Fidelity International in 2018 as Head of Model Risk after spending several years in RBS as Head of Wholesale Credit Risk modelling first and as Head of Model Risk Governance later. Prior to this, she was leading the Wholesale Credit Risk Modelling team at Credit Suisse and worked as an Economist at the Financial Services Authority UK, now PRA. In the early stages of her career – she held research and teaching positions at Oxford University, Catholic University in Milan and Ente Luigi Einaudi (affiliated to the Central Bank of Italy) in Rome. Grazia holds a PhD and an MSc in Economics from Southampton University.
Ashutosh Roy
COO Risk Methodology
Deutsche Bank
Ashutosh is heading the COO function of Risk Methodology department at Deutsche Bank, and he is driving the consistent adoption of model development standards across risk models including process automation and reduction of divergence in model development platforms to achieve efficiency and cost benefits. He has 13 years of deep experience with an equal amount of exposure to 1st LOD (Model Development) and 2nd LOD (Model Governance) spaces. As a 1st LOD model risk manager, he has gained first-hand experience on setting up the key elements of holistic model risk governance framework namely model risk tiering, model change governance control and model uncertainty management framework. He has worked with Morgan Stanley as Market Risk model developer and with BAML as a model governance manager. Ashutosh holds a PhD from Indian Institute of Management (IIM), Ahmedabad, India and Masters from Indian Institute of Technology (IIT) Kharagpur, India. He also holds FRM and ERP Certification by GARP.
Giles Spungin
Global Head of Risk Analytics
HSBC
Giles Spungin will be presenting at Model Risk Management Europe
Fares Triki
Head of Model Risk Management
MUFG
Fares Triki is currently Head of Model Risk Management at MUFG Securities EMEA. He has an extensive risk and pricing quantitative modelling experience. Previously he worked at Credit Suisse, Markit, BNP Paribas, Fitch Ratings, and Banque de France, in quantitative measurement of products and risks, in topics ranging from market, counterparty and credit risks to systemic risks and macroprudential regulations. He holds an MPhil in Economics, an MSc in Finance, and is graduated from a leading French institution in science and technology from Institut Polytechnique de Paris. Fares has multiple contributions in academic journals and industry conferences.
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Video interview with Chris Smigielski, Model Risk Director, Arvest Bank
Webinar led by Royal Bank of Canada, Arvest Bank, Signature Bank and SAS institute
Video Interview with Aruna Joshi, SVP, Model Risk Management, Bank of the West.
By Azar Khurshid, Director, Global Risk Management, Mizuho International
The intersection of technology and model risk
Led by: Deutsche Bank | BNY Mellon | Columbia University | Wells Fargo
Risk Dynamics
Risk Dynamics works closely with banks, insurers, asset managers and CCPs to design, embed and execute best practice Model Risk Management. Our work covers all aspects of MRM from the fundamental governance setup, through detailed policy implementation and regulatory remediation, to the delivery of high-quality independent Model Validation.
Our long-established track record in independent validation includes complex models, new model types and techniques (compliance, AML, AI and machine learning), critical regulatory exercises and large-scale external validation support. We also support a range of non-financial corporates across industry sectors as diverse as energy, pharmaceuticals and telecoms to help them manage the risk from their rapidly expanding portfolios of analytics.
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