Advanced Model Risk USA
2nd Annual | March 22-23 | New York City
INVENTORY
Managing the evolution of models and expansion of definition and classification
BLACK BOX MODELS
Managing black box models and understanding expectations for transparency
EXPLAINABILITY
Enhancing explainability capabilities within AI and machine learning models
CLIMATE RISK
Developing an industry standard for climate risk modeling
MACRO ECONOMY
Modeling the macro economy as uncertainty continues to impact models
LINES OF DEFENSE
Driving collaboration across the three lines of defense for oversight and validation
BIAS
Mitigating risks of bias and understanding ethics and fairness considerations
REGULATION
Exploring global requirements and expectations to deliver effective model risk management
Rafic Fahs,
Chief Model Risk Officer,
Fifth Third Bank
Olga Collins,
ED, Global Head of Model Risk Infrastructure and Reporting,
Morgan Stanley
Alexandre Maurel,
Head of US CIB Model Validation Team,
BNP Paribas
Kerri Anderson,
Assistant Director of Model Risk Management,
Northwestern Mutual
George Soulellis,
Chief Enterprise Model Risk Officer,
Freddie Mac
Steve Zhou,
MD, Model Risk Management,
Webster Bank
Agus Sudjianto,
EVP, Head of Corporate Model Risk,
Wells Fargo
Mazin Joumaa,
VP, Head of Model Risk Management,
Navy Federal Credit Union
Jing Zou,
MD, Model Risk Management,
Royal Bank of Canada
Shawn Tumanov,
Director, Data and Analytics (AI/ML/RPA) Governance,
BMO Financial
CAN YOUR ORGANIZATION 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 +1 888 677 7007 ext. 207 where a member of the team will be happy to tailor the right package for you.
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8:00 Registration and breakfast
8:50 Chair’s opening remarks
REGULATION
Session details
- Reviewing regulatory expectations for model risk teams
- Expectations across different sized organizations
- Uses of automation, AI and machine learning
- Global regulatory requirements and lessons learnt across jurisdictions
- Revisions to model risk guidelines to include AI and machine learning
- Application of SR11-7 to evolving model risk programs
Reserved for, Federal Reserve Board
INVENTORY – PANEL DISCUSSION
Session details
- Explosion of model inventories and new methodologies
- Managing data limitations
- Best practice to manage evolution of inventory
- Methodologies and controls variations across inventory
- Inclusion of non-quantitative models
- Model components across entire risk appetite
- Moving beyond financial models
- Updates and modifications to policies and procedures to accommodate change
Olga Collins, ED, Global Head of Model Risk Infrastructure and Reporting, Morgan Stanley
Alexandre Maurel, Head of US CIB Model Validation Team, BNP Paribas
Irfan Kazi, Managing Director, US Credit Risk Management, CIBC
10:20 Morning refreshment break and networking
OPTIMIZATION
Session details
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- Maturity of model risk function
- Automating model risk practices
- Automating manual tasks and processes
- Ensuring quality control and consistency
- Maintaining standards to do more with less
- Revising model risk frameworks to include AI and machine learning
- Scaling up model risk in a fast-paced deployment environment
- Speed and agility of model risk management
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Mazin Joumaa, VP, Head of Model Risk Management, Navy Federal Credit Union
NFR
Session details
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- Cybersecurity validation requirements
- Threat identification and mitigation
- Categorization criteria for models
- OCC booklet inclusion of cyber security model component
- Expansion of areas leveraging AI and machine learning
- Technical expertise and talent
- Understanding nuances and requirements across domains
- Cybersecurity validation requirements
Chris Smigielski, Model Risk Director, Arvest Bank
AI/ML
Session details
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- Success stories implementing an AI or machine learning approach
- Managing model input and interpreting output
- Transparency of uses of AI and machine learning
- Regulatory appetite and expectations
- Aligning with fair lending requirements
- Understanding model risk requirements using AI and machine learning
- Updating on a continuous and ongoing manner
- Enhancing data governance programs for use of AI
- Increased volume and complexity of data
- Risk mitigants on AI and machine learning
- Managing black box models with no access to data
Rafic Fahs, Chief Model Risk Officer, Fifth Third Bank
12:35 Lunch break and networking
BLACK BOX MODELS – PANEL DISCUSSION
Session details
- Vendor compliance with model risk regulations
- Governance and oversight of vendor models
- Transparency of AI models
- Documentation for effective validation
- Visibility and transparency challenges
- Explainability of black box models
- Determining assurance and control processes
- Identifying use cases for black box models
Steve Zhou, MD, Model Risk Management, Webster Bank
Seyhun Hepdogan, Director, Model Risk Management, Discover Financial
Rafic Fahs, Chief Model Risk Officer, Fifth Third Bank
EXPLAINABILITY
Session details
- Explaining decisions from input to output
- Privacy concerns with excess data collection
- Data requirements with fragmented programs
- Understanding which inputs drive certain outputs
- Development of AI best practice document – PPI/ Policy institute??
- Ensuring compliance with consumer laws and regulations
- Integrating compliance teams
- Customer requirements for explainable AI
- Countering misconceptions on explainability
- Defining and understanding the difference between interpretable and explainable from an AI and machine learning perspective
- Separating explainability and fairness
Kiran Yalavarthy, EVP, Head of Risk Modeling Group, Wells Fargo
EXPLAINABILITY & FAIRNESS
Session details
- Integrating fairness into credit models
- Model development perspectives to consider fairness from outset
- Managing Headline and reputation risk
- Determining appropriate metrics
- Collecting data for fairness testing
- Managing algorithmic fairness in uncertainty
- Understanding ethics and fairness of AI results
Raghu Kulkarni, Head of Model Development, Discover Financial
Kiran Yalavarthy, Head of Risk and Finance Model Development, Wells Fargo
Harsh Singhal, C3.AI
Moderated by Agus Sudjianto, EVP, Head of Corporate Model Risk, Wells Fargo
3:30 Afternoon refreshment break and networking
DATA
Session details
- Data as the starting point to automation and technology
- Techniques and methodologies for data validation
- Leveraging public source, external and contextual metadata
- Identifying correlations for proactive risk management
- Developing forward looking metrics
- Developing data standards consistent across the firm
- Leveraging analytics for better risk identification
- Oversight and controls to govern data end to end
- Developing frameworks to adhere to privacy regulations
GOVERNANCE
Session details
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- Classification of models
- Defining a model vs a tool for decision making
- Validation to ensure models are fit for purpose
- Model risk for trade surveillance and market abuse
- Managing black box models and risk to compliance
- Accountability of AI decision making
- Automating and streamlining governance processes
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5:10 Chair’s closing remarks
5:20 End of day 1 and networking drinks reception
8:00 Registration and breakfast
8:50 Chair’s opening remarks
LARGE LANGUAGE MODELS
Session details
- Overview of Large Language Models
- Pros and cons of Large Language Models
- Use cases for LLMs in Model Risk Management
Roderick A. Powell, FRM, SVP, Head of Model Risk Management, Ameris Bank
BIAS
Session details
- Analyzing bias in data sets
- Quantifying bias
- Reducing bias in data sets
- Aligning decisioning with ethics of organization
- Qualitative approaches to analyzing data bias
- Regulatory expectations and update on bias
- CFPB and Fed exams
- Standardization to detect bias
Jaya Sil, Senior Director, Validation Team, Model Risk Management, Santander
10:10 Morning refreshment break and networking
CLIMATE RISK MODELING
Session details
- Harmonizing climate risk rules
- Testing requirements
- Model inventory on climate risk
- Availability of talent and skills
- Developing and validating climate risk models
- Updating models and ensuring explainability
- Data limitations for effective modeling
- Incorporating economic capital against climate risks
MACRO ECONOMY – PANEL DISCUSSION
Session details
- Provision techniques to estimate impairments
- Regulatory expectations of management and judgement overlays
- Adjusting models in a fast-changing economic environment
- Mitigations or validations to make business users comfortable with models
- Frequency to update models in a fast-changing environment
- Impact of pandemic data and overlays on outlook
- Recalibrating or rebuilding models post pandemic
- Reactions to significant interest rate changes
- Challenging assumptions of a different environment
- Managing unanticipated and unprecedented outcomes
- Identifying models predicated on low inflation
- Modifying assumptions or deploying alternatives
Jing Zou, MD, Model Risk Management, Royal Bank of Canada
Alex Shenkar, SVP, Senior Model Validation Officer, Truist
12:20 Lunch break and networking
RECESSION
Session details
- Recalibrating or refitting models
- Reduction in model development timelines in an evolving environment
- Rules or triggers requiring a model risk deep dive vs. streamlined review
- Spotting performance deterioration or degradation
- Identifying early indicators or triggers
- Sensitivity of machine learning models to change
- Identification before model is decommissioned
- Credit modeling in a downturn
- Scenario and sensitivity analysis
- Planning ahead and identifying models requiring action
George Soulellis, Chief Enterprise Model Risk Officer, Freddie Mac
QUALITATIVE MODELS
Session details
- Managing lack of data for qualitative models
- Challenges with rules and assumptions
- Reliance of qualitative estimates and forecasts
- Appropriate validation techniques
- Developing standards for qualitative models
- Differentiating types of models
COVID-19
Session details
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- Key lessons learnt as a result of changing environment
- Benefits of connectivity testing ahead of time
- Uses of overlays to challenge extreme data
- Changes to models based on Covid-19 experiences
- Reviewing uses for data collected during pandemic
- Extreme macroeconomic movements with no significant losses
- Preparation as a result for future severe events
- Backup model in event of model failure
- Proactive approaches and overlays to stay ahead
3:05 Afternoon refreshment break and networking
LINES OF DEFENSE – PANEL DISCUSSION
Session details
- Developing transparency across the organization
- Aligning with data, audit and compliance
- Developing a control framework for advancing technology
- Criticality of integration across teams
- Auditing AI, machine learning and automation
- Inclusion of technology audit team
Olga Collins, ED, Global Head of Model Risk Infrastructure and Reporting, Morgan Stanley
Kerri Anderson, Assistant Director of Model Risk Management Northwestern Mutual
Shawn Tumanov, Director, Dara and Analytics (AI/ML/RPA) Governance, BMO Financial
RESILIENCE
Session details
- Ensuring robustness of models exposed to different environments
- Model monitoring practices
- Ensuring robustness and resilience during validation
- Developing a proactive oversight approach
- Integrating at development and validation
Agus Sudjianto, EVP, Head of Corporate Model Risk, Wells Fargo
4:55 Chair’s closing remarks
5:05 End of Congress
Kerri Anderson,
Assistant Director of Model Risk Management,
Northwestern Mutual
Olga Collins,
ED, Global Head of Model Risk Infrastructure and Reporting,
Morgan Stanley
Rafic Fahs,
Chief Model Risk Officer,
Fifth Third Bank
Kerri Anderson, Assistant Director of Analytic Model Risk Management (MRM) at Northwestern Mutual, is focusing on the evolution of MRM through collaboration with business partners across the three lines of defense. She has more than a decade of experience in first-line roles handling data and developing models in insurance and the medical research field. For the past several years, Kerri has applied these learnings as a model risk professional with vision of creating robust, integrated, and impactful MRM frameworks and processes. Kerri is passionate about data, the promise of AI, and their abilities to transform the human experience.
Olga Collins is a senior leader with over 20 years of experience in Liquidity and Model Risk Management. Olga joined Morgan Stanley in 2017 and currently heads Model Risk Reporting and Infrastructure globally. In her current role, Olga is responsible for model risk assessment, executive and regulatory reporting, model validation platform development and process automation. Prior to this, Olga was Head of Model Risk Management at New York Community Bank, Bank Risk Officer at Sterling Bank and Director of Liquidity at PNC. Her background encompasses Enterprise Risk, Asset & Liability Management, Deposit Pricing, Funds Transfer Pricing, Liquidity Management, Stress Testing, and Systems Development & Integration. Olga Collins holds a Master’s degree in Finance from Case Western Reserve University.
Biography coming soon.
Seyhun Hepdogan,
Director of Model Risk Management,
Discover financial services
Mazin Joumaa,
VP, Head of Model Risk Management,
Navy Federal Credit Union
Raghu Kulkarni,
Head of Model Development,
Discover FInancial
Seyhun Hepdogan is Senior Director of Model Risk Management for Discover Financial Services. He is responsible for all business-as-usual models including originations, portfolio risk, collections, marketing, fraud and AML models. Under his direction, his team oversees the model risk across the company. He and his team play an integral role in transitioning to machine learning models. Prior tohis Discover Financial Services experience, Seyhun was Senior Director of Model Risk for Santander Holdings USA, responsible for fraud, AML, operational risk, commercial credit risk. Seyhun holds a Ph.D. in Industrial Engineering from University of Central Florida and is certified anti-money laundering specialist.
Mazin has over 20 years of experience in financial services, management consulting, and operations, including 11 years in model risk management. He is currently the Head of Model Risk Management at Navy Federal Credit Union, the world’s largest Credit Union with assets of ~$160B. Prior to Navy Federal, Mazin was Head of Enterprise Model Risk Governance and Operations and the model risk process lead for Capital Planning/Stress Testing at Capital One. He was instrumental in building out Capital One’s enterprise model risk management program during his 9+ year tenure. Mazin holds an MBA from Arizona State University, a BSc in Industrial and Systems Engineering from Virginia Tech, and is a certified Project Management Professional and certified Lean Six Sigma Black Belt.
Biography coming soon.
Alexandre Maurel,
Head of US CIB Model Validation Team,
BNP Paribas
Roderick Powell,
Senior Vice President – Head of Model Risk Management,
Ameris Bank
Alex Shenkar,
SVP, Senior Model Validation Officer, Model Risk Oversight, Team Lead for Credit & Loss Forecasting,
Truist
Biography coming soon.
Roderick Powell is Senior Vice President and Head of Model Risk Management at Ameris Bank in Atlanta, Georgia. Prior to joining Ameris Bank, Powell was a Director at KPMG LLP where he specialized in model development, implementation, and validation for large Financial Institutions, including Banks, Insurance Companies, and Mutual Funds. He also worked at Bank of America where he was Senior Vice President and Head of Market Risk Management for the Mortgage Securities Trading Desk. Powell earned his MBA from Florida State University. He also earned a Certificate in Applied Machine Learning and Data Science with Python from Emory University. In addition, Powell is a Certified Financial Risk Manager (“FRM”). He is a frequent speaker on the use of Artificial Intelligence and Robotic Process Automation in the Financial Services industry.
Alex Shenkar is Senior Vice President, Model Risk Oversight of Truist Bank. He joined SunTrust Bank, predecessor of Truist Bank, more than 9 years ago.
His current team is responsible validation of diverse portfolio of credit and loss forecasting models including underwriting, CCAR and CECL for all lines of business.
Prior to joining Truist, Alex spent almost 11 years at Bank of America. His last position with Bank of America was Senior Vice President, Quantitative Compliance for Consumer and Small Business Banking.
Also, Alex’s experience included management positions with Capital One, DMR/Fujitsu, and FIRSTPLUS Financial. He received M.B.A. and M.S. in Applied Mathematics.
Chris Smigielski,
Director of Model Risk Management,
Arvest Bank
George Soulellis,
Chief Enterprise Model Risk Officer,
Freddie Mac
Agus Sudjianto,
EVP, Head of Corporate Model Risk,
Wells Fargo
With over 30 years of financial services industry experience, Chris has an in-depth knowledge of model risk management, model governance, model validation, financial model development, Asset Liability Management, and team development. Chris is currently the Director of Model Risk Management at Arvest Bank and was previously Vice President, Director of Model Risk Management at TIAA Bank for five years. His experience includes leadership roles at Diebold and Fiserv, where he consulted with financial institutions nationally and internationally to design and implement financial strategies to maximize productivity and growth, as well as Asset/Liability Management and quantitative analysis at HSBC and First Niagara Banks.
Biography coming soon.
Agus Sudjianto is an Executive Vice President and Head of Corporate Model Risk for Wells Fargo where he leads a highly technical team to manage model risk across the enterprise.
Prior to his current position, Agus was the Modeling and Analytics Director and Chief Model Risk Officer at Lloyds Banking Group in the United Kingdom where he was responsible for the enterprise development and oversight of all risk management models (Retail and Wholesale Credits, Market, Regulatory Capital, Stress Testing, Asset Liability Mangement, Insurance).
Before joining Lloyds, he was a Senior Credit Risk Executive and Head of Quantitative Risk at Bank of America. Prior to his career in banking, he was product design manager at Ford Motor Company where he led engineering teams designing engine systems and components using complex engineering models.
Agus holds numerous US patents in both Finance and Engineering fields. In addition to publishing numerous technical papers, he is also a co-author of a statistics book in Design and Analysis of Computer Experiment. His technical expertise and interest include Quantative Risk, especially credit risk modeling and statistical finance, statistical methods for fighting financial crimes, and computational statistics.
He holds graduate degrees in Engineering and Management from Wayne State University and Massachusetts Institute of Technology.
Shawn Tumanov,
Director, Data and Analytics (AI/ML/RPA) Governance,
BMO Financial
Kiran Yalavarthy,
EVP, Head of Risk Modeling Group,
Wells Fargo
Steve Zhou,,
MD, Model Risk Management,
Webster Bank
Shawn Tumanov is a Director of Data & Analytics Governance at BMO. In this role, Shawn is advancing the enterprise Artificial Intelligence practices to implement an efficient and effective process for identifying, validating, and implementing AI solutions. One of his key projects is implementing the Enterprise Data & Analytics, working group. Shawn has over 20 years of financial experience, starting as a bank examiner at the OCC. Shawn held several increasing senior roles in risk management throughout his career, including Model Risk compliance and controls. He has an MBA from Northern Illinois University and is a Certified Internal Systems Auditor.
Biography coming soon.
Steve is Head of MRM at Webster Financial Group. His primary responsibility is to execute model validations and model annual review for all models in the banks model inventory including credit (PD/LGD, CECL), treasury (ALM/Liquidity/FTP), BSA/AML and stress testing. Steve manages the 3rd party relationships for any validation performed by external consultant and ensures the deliverable meet regulatory expectations as well as banks own requirements. He is also responsible to maintain company’s MRM policy and procedures, provide update in the operational risk committee, and address regulatory/audit questions related to model risk as required.
Steve previously was SVP at TD Bank N.A. where he was responsible for model risk of all estimation approaches used in the CCAR process covering ~350 Billion of portfolios across different risk domains. He also led the remediation and closure of three model related MRAs. Prior to TD Bank, he was Director of Stress Testing Modelling with GE Capital where he managed the development of stress testing PD/LGD and PPNR models. Prior to GE Capital, his role was VP – Treasury Risk at Barclay’s Capital where he was the model owner for Market Risk, ALM and liquidity models. Steve also has ~10 years of consumer bank experiences prior to Barclays working in various institutions including GE capital Retail Finance and Citibank where he used data analytics to drive risk insights and build statistical scorecards.
Steve earned a M.S in Finance and Accounting from Bentley University, a B.S in Finance from Renmin University. He is a CFA charter holder.
Jing Zou,
MD, Model Risk Management,
Royal Bank of Canada
As Managing Director in Enterprise Model Risk Management (EMRM), Jing Zou is responsible for validating models in Securitized Products, Pre-Provision Net Revenue, interest rate, VaR, retail mortgages, and insurance. She also developed Comprehensive Capital Analysis and Review (CCAR) model fragility analysis, which quantifies the impact of model uncertainty on capital ratios. She is an invited speaker for many industry conferences.
Jing joined RBC in 2014 as a Director in local model risk manager, where she was responsible of engaging the business about model risks. Later on, she was promoted to a Senior Director and then a Managing Director. Prior to joining RBC, Jing worked at Goldman Sachs, Wells Fargo, and Fannie Mae in various quantitative analytics roles covering front office quant, market risk, and model risk areas.
Jing has a Ph.D. in Applied and Computational Mathematics from Princeton University and a B.S. and M.S. in Computational Mathematics in Xi’an Jiaotong University.
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HEAR FROM PAST ATTENDEES AND SPEAKERS…
PANEL DISCUSSIONS
Interactive panel discussions are designed to include attendees by running a live Q&A throughout the session
PRESENTATIONS
Hear industry experts provide detailed insights on a range of vendor risk issues, challenges and opportunities
NETWORKING BREAKS
Networking opportunities including breakfast, lunch and refreshment breaks on both days, access to all streams and sessions.
MEET THE SPEAKERS
Continue discussions beyond the auditorium and interact with speakers and attendees after their session.
Company biography coming soon.
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GET YOUR BRAND SEEN
CONNECT WITH SENIOR LEADERS
CAN YOUR ORGANIZATION 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 +1 888 677 7007 ext. 207 where a member of the team will be happy to tailor the right package for you.
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Yes, the Center for Financial Professionals are happy to discuss speaking opportunities at the Advanced Model Risk USA Congress. For further information on this please contact alice.kelly@cefpro.com or call us on +1 888 677 7007.
Business attire is requested. The Congress is a formal opportunity to network with like-minded professionals and to gain knowledge from the industry’s finest risk management experts.
We offer incentives for ‘early bird’ registrants of the Congress, as outlined on our pricing structure. Registration includes breakfast, refreshment breaks, lunches, the cocktail reception at the end of the day, full access to the sessions and exhibition area. Presentations from the sessions are also available, subject to speaker approval.
All registered attendees will receive an email with access to documentation and speaker presentations after the Congress*. We will work with our presenters to include as many presentations as possible on our App during the Congress.
* Please note that our speakers often have to gain permission from their relevant compliance departments to release their presentations. On rare occasions compliance may not allow presentations to be distributed.
Yes. As with all of our events, the Center for Financial Professionals will be providing brilliant coffee, breakfast, lunch, refreshments, and smaller bites during the networking breaks.
There are ample opportunities for networking and interaction throughout the Congress, such as:
- Breakfast, lunch and refreshment breaks
- Cocktail reception at the end of the day (subject to confirmation)
- Q&A, panel discussions and audience participation technology
Yes there are plenty of opportunities for the Center for Financial Professionals to share thought-leadership to the attendees of Advanced Model Risk USA Congress and our wider risk professionals community. At the event we can distribute your material to the attendees, offer you an exhibition booth, and provide speaking opportunities so that you may enjoy a more prominent presence at the Congress. Visit the Sponsor tab for further information or contact sales@cefpro.com / +1 888 677 7007
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To discuss this further please contact marketing@cefpro.com or call +1 888 677 7007.
If you are unable to attend the Congress due to national/Covid restrictions, CeFPro would be more than happy to offer you a refund, credit note or the option to transfer the ticket to a colleague who is able to attend.
Yes, CPE Credits are available for the Advanced Model Risk Congress.
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PLEASE NOTE: To qualify for the preferential ‘early bird’ rates, registration must be received by the close of the ‘early bird’ working day, and payment can be made at the time of registering, or up to a week after registration is made an invoice sent. CeFPro reserves the right to increase rates should payment be delayed significantly. For Group Rates to be valid, the whole group must register at the same time, though names can be changed at any time up to the event at no additional cost. Should a delegate register at a rate that is inaccurate, CeFPro reserves the right to issue an additional invoice for the outstanding amount.
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