Model Risk Management USA 2019

Reviewing the evolution of model risk management and managing innovation with management and oversight

MODEL RISK MANAGEMENT USA

October 7-8, 2019 | New York City

REGULATION
Regulatory expectations as model risk management continues to evolve across jurisdictions

AI & MACHINE LEARNING
Increasing efficiency, removing bias in output and limiting reputational risks

QUALITATIVE MODELS
Bringing effective validation and governance into the scope of model risk management

VALIDATION
Evaluating and looking beyond conceptual soundness of single use of models

CECL
Early readings and approaches from large vs. small institutions

FUTURE OF MODEL RISK MANAGEMENT
The future state of model risk management: Evolution of model definition, uses and management

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Stephan Meili,
Managing Director, Risk Management,
Citi

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Katie Hysenbegasi,
Managing Director, Head of Credit Risk Modeling Team, Risk and Compliance,
BNY Mellon

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Emre Balta,
Head of Financial, Market, AML Model Validation,
US Bank

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Paul O’Donovan,
Director, US Model Governance,
BMO Financial

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Snehal Kanakia,
Director, Model Risk
Capital One

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Dr. Agus Sudjianto,
Head of Corporate Model Risk,
Wells Fargo

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Deniz Senturk,
Chief Risk Officer, Global Treasury & Head of Integrated Analytics,
State Street Corporation

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Daniel Ward,
Head of RISK IRC, CIB Americas
BNP Paribas

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Kash Agrawal,
Director, Quantitative Analytics,
Barclays

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Jing Zou,
Managing Director, Model Risk Management,
Royal Bank of Canada

October 9 | Managing Machine Learning Model Risk

Intensive and interactive one-day Masterclass led by Wells Fargo

The following topics will be covered in the workshop:

Introduction to machine learning methodology
Examples of advanced machine learning applications in banking
Explainability and interpretation techniques for machine learning
Validation Framework

Due to the interactive nature of the Masterclass, seats are limited and once the quota is reached registration will automatically close.
Click here to find out more

#1
THOUGHT LEADERSHIP

Unparalleled thought-leadership, addressing key issues, such as: Regulation, AI & Machine Learning, qualitative models, validation, CECL, the future of model risk management and more.

#2
INTENSIVE POST-EVENT WORKSHOP

Join us on October 7-8 in New York City for the main event, and October 9 for a 1-day intensive workshop led by Wells Fargo on Managing Machine Learning Model Risk.

#3
SPEAKER LINE-UP

Expert speaker line-up to address the latest updates, challenges and emerging technology within the space.

#4
NETWORKING

Bringing together industry professionals and peers to provide a platform for networking and idea sharing.

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PRIME LOCATION

The Congress will take place in the heart of New York City at the Millennium Times Square Hotel.

08:00 Registration and breakfast

08:50 Chair’s opening remarks

REGULATION – PANEL DISCUSSION
9:00 Reviewing regulatory expectations as model risk management continues to evolve and management of requirements across jurisdictions

  • SR11-7 changes and relation to governance of machine learning
  • Evolving model risk guidance towards more structured machine learning frameworks
  • Defining framework for management of machine learning models

Wei Ma, Head of Model Risk Management, Sumitomo Mitsui Banking Corporation
Emre Balta, Head of Financial, Market, AML Model Validation, US Bank
Roderick Powell, Head of Model Risk Management, Ameris Bank
Manish Chakrabarti, US Head of Model Risk, BNP Paribas   

AI & MACHINE LEARNING
9:50 Development, validation and governance of AI and machine learning models to increase efficiency

  • Determining the most efficient way to validate and control machine learning models
  • Managing risk associated with algorithm models
  • Cost pressures to increase efficiency
  • New types of algorithms: understanding effective design and execution
  • Ensuring effective review when validations are outdated before complete
  • Use of tools that have embedded AI
    • Ensuring oversight from model risk management or building an enhanced governance framework
  • Algorithmic accountability act: Transparency and interpretability of AI
    • Bringing model risk management to the next level
  • Statistical models, automatic decision, AI and machine learning impact to companies
    • Assessing fairness, discriminatory bias, security and privacy
  • 2020 examination of AI models

Paul O’Donovan, Director, US Model Governance, BMO Financial

10:30 Morning refreshment break and networking

11:00 Removing bias in output from AI and machine learning models and limiting reputational risks

  • Risk to firm’s reputation and conduct
    • Managing within validation
  • Testing and validating for the purpose of fairness and bias
  • Understanding decisions made by algorithms and machines
  • Binary outputs of models
  • Unintended consequences of bias in backward data
  • Validating models intended use to avoid data and output bias
  • Testing models before implementation to work as intended

Lourenco Miranda, Regional Head of Model Risk Management, Société Générale

DATA
11:40 Managing increased emphasis on data and identifying quality issues with increased reliance for technology initiatives

  • Balancing modeling need and data available
  • Enterprise view and plan for data management
  • Governance and accountability: Role of the chief data officer
  • Reporting of validations and model risk across the organisation
  • Using independent data for challenger and back testing models
  • Understanding where model is pulling data from
  • Alternate data: Using all sources of data
    • Social media, pay day loans, utility payments etc…

David Palmer, Division of Banking Supervision and Regulation, Federal Reserve Board

12:20 Lunch break and networking

AUTOMATION
1:20 Automation of validation activities to enhance processes and increasing efficiency

  • Practicality of automation
  • Scope of proposed automation
  • Usefulness for modeling types

PERFORMANCE MONITORING – PANEL DISCUSSION
2:00 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

Toks Adekoya, Director Model Risk Management, CIT
Barbora Meunier, Head of Model Risk Governance, Société Générale
Julia Litvinova, Head of Model Validation, Managing Director, State Street
Richard Cooperstein, Director of Model Risk Management, Andrew Davidson & Co., Inc.

2:50 Afternoon refreshment break and networking

ALTERNATIVE METHODOLOGY
3:20 Preparing and implementing alternative methodology adoption and evaluating conceptual soundness

  • Engaging machine learning algorithms
  • Adoption of models in non-traditional areas
  • Expectation from regulators
  • Moving away from traditional statistics and econometrics
  • Understanding how to evaluate conceptual soundness
  • Skill set requirements compared to traditional modelers and validators
  • Moving into a new frontier of modeling
  • Evaluating and ensuring conceptual soundness of models

Juan Salafranca, Head of Retail Credit Risk Models, BBVA Compass

RISK SENSITIVITY
4:00 Developing risk sensitive model risk management practices tailored to individual model requirements

  • Cookie cutter approach to model risk management
  • Scheduling validation frequency to determine risk sensitivity

Chris Smigielski, Director, Model Risk Management, Arvest Bank

MATERIALITY THRESHOLD
4:40 Determining materiality thresholds and ensuring dynamic monitoring

  • Triggering periodic revaluation
  • Consistent data from formalization of MRM through SR11-7
  • Determining risk posed to institution and proportionate controls for risk
  • Allocation of effective risk oversight
  • Future adaptations to standard: Idiosyncratic reflection of processes

Petr Chovanec, Director, Business Modeling and Forecasting, UBS

5:20 Chair’s closing remarks

5:30 End of day one and drinks reception

08:15 Registration and breakfast

08:50 – Chair’s opening remarks

QUALITATIVE MODELS – INTRODUCTION
9:00 The what and why to qualitative models

Ximena Zambrano, Head of Qualitative Model Validation, Wells Fargo

PANEL DISCUSSION
9:20 Effective validation and governance of qualitative models and bringing into the scope of model risk management

  • Expanded model definition from regulators
  • Managing assumptions and standard testing requirements
  • Tiering qualitative models
  • Scale required to bring in qualitative models
  • Reviewing, validating and monitoring complete inventory of qualitative models
  • Regulatory feedback on development and validation techniques

Ximena Zambrano, Head of Qualitative Model Validation, Wells Fargo
Deniz Senturk, Chief Risk Officer, Global Treasury & Head of Integrated Analytics, State Street Corporation
Kash Agrawal, Director, Quantitative Analytics, Barclays
Chris Smigielski, Director, Model Risk Management, Arvest Bank

10:20 Morning refreshment breaks and networking

VALIDATION
10:50 Evaluating model use and ensuring validation looks beyond conceptual soundness of single use

  • Validating for specific uses of models used for multiple purposes
  • Performance and monitoring across use
  • Making model risk management a value adding partner
  • Strategic planning for model risk management to fully plug into enterprise risk
  • Comprehensive monitoring to understand model uses
  • Aligning model development and user’s terminology

Albert Chin, Head of Model Risk Management, Signature Bank

CHANGE CONTROL
11:30 Managing change control to ensure visibility and tracking across models

  • Restricting access to model output to users
  • Managing models in a controlled IT system
  • Independent validation unit visibility to changes made
  • Tracking changes made to model
  • Identifying full impact on a business
  • Regulatory expectation for access and change control
    • Tracking exposure to an individual model

Snehal Kanakia, Director, Model Risk, Capital One

12:10 Lunch break and networking

STANDARDIZATION
1:10 Developing an enterprise standardization of development and documentation standards across model population

  • Model teams spread out – ensuring all are following the same standards and templates
  • Getting all models to one standard
    • Varying maturity of teams
  • Global regulatory agendas and varying expectations
  • Standardize across regions or bespoke across jurisdictions

CECL – PANEL DISCUSSION
1:50 Getting ready for CECL live: modeling, implementation and impact

  • Use of qualitative overlays and judgements
    • Impact on the reserved
  • Use of stress test models
    • Implementing one model to do both
  • Building a model that captures macro-economic variables and loss
  • Approaches from large vs. small institutions
  • Early readings of reserve impacts
  • Views on volatility evolution
  • Impact on profitability on product offerings
  • Compensating controls and use of conservatism
  • Reasonable and supportable forecast period

Katie Hysenbeasi, Manging Director, Head of Credit Risk Modeling Team, Risk and Compliance, BNY Mellon

2:40 Afternoon refreshment break and networking

QUANTIFYING MODEL RISK
3:10 Quantification of model risk: Defining and identifying model risk limitations in performance

  • Aggregate basis individually and across model risk types
  • Regulatory framework for continuous model monitoring
  • Defining and monitoring metrics
  • Quantifying model risk related to a breach of thresholds
  • Definition of model risk appetite statement
  • Decisions on usage and redevelopment of models

Jing Zou, Managing Director, Model Risk Management, Royal Bank of Canada

FUTURE OF MODEL RISK MANAGEMENT – PANEL DISCUSSION
3:50 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

Daniel Ward, Head of RISK IRC, CIB Americas, BNP Paribas
Stephan Meili, Manging Director, Risk Management, Citi
Nikolai Kukharkin,
Head of Model Risk Management, Managing Director, TIAA

4:40 Chair’s closing remarks

4:50 End of Congress

Toks Adekoya
Toks Adekoya, Director Model Risk Management, CIT

Toks Adekoya currently leads the Quantitative Strategies Team at CIT. The team is responsible for Model development of commercial credit models, Capital Planning and CECL forecasting models. Prior to this role, she led the ongoing monitoring team at CIT where she was responsible for quarterly monitoring of all active models in the CIT model inventory. Prior to CIT, Toks was at Citi Cards where she led an ongoing monitoring team for non-scoring model. Toks has a PhD in Chemical Engineering from The University of Manchester, United Kingdom.

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Kash Agrawal, Director, Quantitative Analytics, Barclays Capital

Kaushal Agrawal is a Director in the Quantitative Analytics team at Barclays. Currently, Kaushal leads a team of quantitative modelers focused on developing PPNR models for Markets (Sales & Trading) and Investment Banking businesses. Kaushal has spent most of his professional career in financial services risk management. Prior to joining Barclays, Kaushal worked at Citibank and HSBC focusing mainly on quantitative risk management. Kaushal has also worked as a Senior Consultant at Ernst & Young (EY).  At EY, Kaushal worked with multiple US banks and FBOs focusing primarily on model development and model validation ; He led a team of quantitative professionals working on projects related to Economic Capital, Basel, Stress Testing, CCAR, and ALLL. Kaushal holds a Masters degree in Quantitative Finance from Columbia University and has a Bachelors degree from Indian Institute of Technology (IIT) Bombay.

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Emre Balta, Head of Financial, Market, AML Model Validation, US Bank

Emre is responsible for leading the teams validating PPNR, market risk, operational risk, AML models and a wide variety of risk tools used by the Bank.

Emre has over 15 years of experience in credit, market and operational risk modeling across full spectrum of asset classes (retail, corporate, capital markets) and model risk management, including governance, framework design and implementation, model development, validation, regulatory strategy and remediation plans. Prior to his role at U.S. Bank, Emre was a principal in the Finance & Risk practice of Oliver Wyman and a senior financial economist at the Risk Analysis Division of OCC.

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Manish Chakrabarti, US Head of Model Risk, BNP Paribas

Manish will be presenting at Model Risk Management USA 2019.

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Albert Chin, Head of Model Risk Management, Signature Bank

As the Head of Model Risk Management for Signature Bank, Albert is responsible for ensuring that all models used by Signature follow FIL 22-2017 (i.e. SR 11-7 and OCC 2011-2012). These model types include ALM, Liquidity, CECL, Stress Testing, DFAST and AML/BSA. Prior to entering the model risk management space, Albert held various roles which gave him the opportunity to perform research and present his work during outreach engagements. Albert holds graduate degrees in both economics and statistics.

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Petr Chovanec, Director, Business Modeling and Forecasting, UBS

Petr Chovanec is a Director of Business Modeling and Forecasting at UBS Americas Inc. where he leads a team focusing on wealth management banking models. In his position, he is involved in business forecasting and various stress testing exercises (CCAR, CECL, LPA). Before the position with UBS, he spent four years in model validation in Citizens Bank (formerly RBS Citizens) and State Street Bank and Trust. Before the validation world, he was a front office quant in fixed income, currency and commodities trading and origination.

Richard Cooperstein
Richard Cooperstein, Director of Model Risk Management, Andrew Davidson &Co., Inc.

Richard Cooperstein, Ph.D. leads Model Risk Management at Andrew Davidson & Co., Inc. bringing decades of experience from various risk and policy roles in the mortgage market. His experience includes senior positions at Freddie Mac, Ocwen, HSBC Securities and Ranieri Partners. At the US Office of Management and Budget, he applied option pricing theory to value Federal guarantees and was one of the chief architects of Credit Reform. Richard is a published author and experienced speaker on applied option pricing and the economics of financial policy.

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Katie Hysenbegasi, Managing Director, Head of Credit Risk Modeling Team, Risk and Compliance, BNY Mellon

Katie Hysenbegasi is a Managing Director and Head of Credit Risk Modelling group at the Bank of NY Mellon. In the current position, Katie is leading a team of 20 modellers/economists for Stress testing, CECL/IFSR9, and Basel III covering credit risk. In addition, she is responsible for the scenario design and macroeconomic factors forecasting. Katie joined BNY Mellon in January 2006 as a head of the credit risk modelling group.

During her career, she has served as Citigroup Vice President developing statistical models to support marketing and risk management. Katie also has taught for the Department of Economics at Baruch College, CUNY, as an adjunct assistant professor and lecturer.

Katie obtained an MFE from Baruch College of CUNY; an M.A. degree in Economics and a Ph.D. in Applied Economics from WMU 2001.

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Snehal Kanakia, Director, Model Risk, Capital One

Snehal Kanakia is a Senior Director in the Model Risk Office at Capital One. He and his team are responsible for model risk activities associated with commercial pricing, valuation, and credit risk models including those using machine learning. Mr. Kanakia was previously a Senior Vice President in the Model Risk Audit team at Bank of America. There, he and his team werer responsible for providing an independent assessment of the development, validation, governance, and usage of derivative pricing, risk, CCAR, and other models. Prior to joining Bank of America, Mr. Kanakia was a Model Risk Senior Manager at Protiviti where he was responsible for leading model validation and model audit teams. His clients included several top 5 U.S. banks with engagements focused on CCAR, asset-liability management, anti-money laundering, market risk, operational risk, probability of default, and counterparty credit risk. Mr. Kanakia also worked at Fannie Mae where he led several audits with interest rate, loss given default, capital markets, and single-family pricing models in scope. He started his career in KPMG’s risk advisory practice where he supported the Citigroup, Wells Fargo, Deutsche Bank, HSBC, and Credit Suisse external audit teams by pricing derivatives, calculating credit valuation adjustments, and reviewing risk models. Mr. Kanakia holds a masters in operations research from Columbia University and a bachelors in economics from U.C. Berkeley.

Nikolai Kukharkin
Nikolai Kukharkin, Head of Model Risk Management, Managing Director, TIAA

Nikolai Kukharkin is Managing Director, Head of Model Risk Management at TIAA. His team is responsible for TIAA’s Model Risk Management program, including model validation, control, and governance activities such as risk rating of models, model performance review, front-to-back model governance and controls, and reporting and oversight of model risk.

Mr. Kukharkin has over 20 years of experience in risk management, focusing on model risk assessment and management. He joined TIAA in 2017 after 14 years with UBS, where he held various roles within Risk Control function. Most recently, Mr. Kukharkin was the Global Head of Model Risk Management & Control at UBS, where he led the design and implementation of a complete Model Risk Management framework. Previously, Mr. Kukharkin served as Vice President, Model Risk Officer at JPMorganChase Model Review Group for 5 years.

Mr. Kukharkin holds PhD in Plasma Physics from Moscow Institute of Physics and Technology (Russia) and started his career in 1990s as a research physicist at the National Research Center “Kurchatov Institute” in Moscow, and later in the Department of Mechanical and Aerospace Engineering at Princeton University.

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Julia Litvinova, Head of Model Validation, MD, State Street

Julia Litvinova is a Managing Director and Head of Model Validation at State Street. In this role Julia is responsible for supervising validation of a broad range of models including models used for credit, market and liquidity risks, regulatory capital, valuation, asset and investment management.

Prior to joining State Street, Julia obtained extensive consulting experience at the Brattle Group, the economic litigation consulting company. She specialized in the application of finance, risk management and taxation to a variety of consulting and litigation settings. She received her Ph.D. in Economics from Duke University, M.A. in Economics from New Economics School and M.S. in Mathematics from Moscow State University.

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Wei Ma, Head of Model Risk Management, Sumitomo Mitsui Banking Corp

Wei Ma is head of model risk management at SMBC, New York, in which capacity he develops model validation framework across SMBC NYB and its subsidiaries in the U.S. as well as leads validation of individual models. Prior to the current role, he was an enterprise risk officer led the development of risk appetite framework.

Before joining SMBC in 2013, Wei worked for five years at AIG where, as an associate director, he managed structured product portfolios composed of CDO, RMBS, and CMBS assets with a notional amount of over $60 billion. He also led the development of structured product risk analytic capabilities at AIG Asset Management and led work streams in stress testing and model risk management initiatives.

Prior to AIG, Wei was a structurer at Merrill Lynch and PriceWaterhouseCoopers with a focus on CLO. He also spent two years working as a risk management consultant at PwC during which period he advised banking clients on market risk management solutions.

Wei received an MBA degree from NYU Stern School of Business. He also holds degrees in computer science from top universities in China. He is a certified financial risk manager by GARP.

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Stephen Meili, Managing Director, Risk Management, Citi

Stephan Meili is a Managing Director at Citi leading the Convergence Risk effort for the investment and corporate bank. Previously, he was Global Head of Market Risk for Securitized Products Trading and Municipal Derivatives at Barclays. Stephan has 20+ years of financial markets experience in Europe, US and Asia ranging from risk management (market, credit and operational risk) and asset management to quantitative modeling and model validation for investment banks, asset managers and consulting firms. Furthermore, he has represented banks at industry forums and conferences on financial regulation and has taught courses on derivatives, regulation and risk management at the Federal Reserve Bank and at Columbia University. He holds a MS in Finance from Northwestern University and a degree in economics and business administration from the University of Basel, Switzerland. He is also a CFA and FRM charterholder.

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Barbora Meunier, Head of Model Risk Governance, Societe Generale

As the Regional Head of Model Risk Governance for Societe Generale, Barbora is responsible for all aspects of model risk governance framework applicable to the models used by Societe Generale at Americas perimeter. These model types include Credit, Pricing, ALM, Stress Testing, Counterparty Credit Risk, Market Risk or AML/BSA. Barbora joined Societe Generale in 2005 and prior to entering the model risk management space, held various roles in the Business, Internal Audit and In-house Consulting. Barbora holds Masters in both economics and management.

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 Lourenco Miranda, Managing Director, Regional Head of Model Risk Management (Americas), Societe Generale

Prof. Dr. Lourenco Miranda is the Regional Head of Model Risk Management for the Americas in Société Genérale. He joined the Bank in New York in February 2016 as Managing Director Head of Capital Planning, Assessment and Review (CCAR) in New York. Prior to that, within his 20+ years of financial industry experience, Lourenco has held multiple leadership roles in Risk Management and Finance at internationally active Financial Institutions in multiple regions and more than 70 countries and regulatory jurisdictions in 5 regions. On the academic world, for the past 25 years, Lourenco has held faculty positions in multiple academic centers worldwide in the field of Risk Management and Financial Mathematics and has been in the board of international professional institutions and a regular speaker at major international risk conferences. Currently, he is Adjunct Professor of Risk Management, Stress Testing, Machine Learning and Data Science at Fordham University in NYC. Besides that, Lourenco is a published author of academic and professional articles in peer-reviewed journals. He is also a reviewer of professional and academic Journals in Risk and Finance. Lourenco holds a PhD in Statistical Physics with a link to Financial Risk Measurement.

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Paul O’Donovan, Director, US Model Governance, BMO Financial

I am a Director in the Model Risk team for BMO with responsibility for oversight of Model Risk requirements within the 1st and 2nd Line, model risk reporting, issue management, and evolution of the Model Risk Framework including changes for Artificial Intelligence and Machine Learning. Prior to BMO, I have held various Model Risk roles including Model Validation for DFAST and Basel models, stress testing and capital analytics, and as a regulator for large US Banks focusing on SR 11-7 implementation and CCAR. I hold an MBA from the University of Chicago, Booth School of Business, a BSc in Mathematics & Financial Mathematics from University College Cork, and am a certified FRM.

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David Palmer, Division of Banking Supervision and Regulation, Federal Reserve Board

David Palmer is a senior supervisory financial analyst in the Division of Banking Supervision and Regulation at the Federal Reserve Board. He focuses on several primary topic areas, including banks’ capital planning practices, banks’ model risk management practices, banks’ and supervisors’ stress testing activities, validation of supervisory stress testing models, and banks’ credit risk capital models. He engages in both policy-related projects as well as on-site examinations. David was a primary author of the Federal Reserve’s Supervisory Guidance on Model Risk Management (SR 11-7), issued in April 2011 jointly with the OCC (and more recently with FDIC), and continues to lead the implementation of that guidance within the Federal Reserve. He was also a key contributor to the Federal Reserve’s supervisory guidance on capital planning for large firms issued in December 2015 (SR Letters 15-18 and 15-19), as well as to the Federal Reserve’s final rules to implement Dodd-Frank stress testing requirements and the Federal Reserve’s Capital Plan Rule. More recently, David has been involved in evaluating supervised firms’ use of fintech, including artificial intelligence/machine learning.

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Roderick Powell, Head of Model Risk Management, Ameris Bank

Roderick Powell is the Head of Model Risk Management at Ameris Bank in Atlanta, Georgia. Prior to joining Ameris, Powell was a Director at KPMG LLP where he specialized in model development, implementation, and validation for financial institutions. He also worked for ten years at Bank of America primarily in Quantitative Finance and Market Risk Management. Powell earned his MBA at Florida State University and is a Certified Financial Risk Manager (“FRM”).

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Juan Salafranca, Head of Retail Credit Risk Models, BBVA Compass

Dr. Juan Salafranca is a Quantitative Leader (Quant) at BBVA, a global financial services group with over $700 Bn in assets. He started his career as theoretical physicist, obtaining a PhD in 2008 in Madrid (Spain) after specializing in computer simulation of the properties of electrons in solids. He then developed his scientific career at University of Tennessee Knoxville and Oak Ridge National Laboratory. In 2014, he began working as a Quant in the financial industry, using data and analytics to predict credit risk and to optimize business decisions. After holding different positions in the Risk Analytics world, he has been leading the Retail Risk analytics team at BBVA USA for the past three years. Dr Salafranca’s team oversees the development of models for Origination, Account Management and Collection activities for all products in the Retail portfolio. He has authored numerous scientific articles, cited over 400 times, and he has participated as an invited speaker in conferences in the Americas and in Europe.

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 Deniz Senturk, Head of Model Risk Management, State Street

Deniz is a Senior Vice President in State Street Corporation, and the head of Model Risk Management since March 2015. Prior to joining SSC, she has been heading Model Risk Management in GE Capital for 3+ years. She has been with GE for 15 years where she led marketing analytics teams and also research teams in GE Global Research Center (where she has published 15+ patents and 20+ research papers on advanced statistical techniques used in risk and finance.) Her areas of functional expertise include compliance and control functions (Model Governance), credit and model risk management (Consumer and Commercial Credit Risk, Stress Testing, Allowance/Reserve, and Capital modeling) as well as risk analytics, marketing analytics and business strategy management. Deniz also served as an adjunct professor at Graduate School of Business, Fordham University for three years. She has a Ph.D. in Applied Statistics from University of California, Santa Barbara and a B.S. in Physics from Bogazici University (Turkey)

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Chris Smigielski, Director, Model Risk Management, Arvest Bank

Chris is currently the Director of Model Risk Management at Arvest Bank in Northwest Arkansas.  Previously, Chris was Model Risk Director 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. Chris was actively involved with TIAA Bank’s diversity and inclusive initiatives, serving as Co-Chairman for the Veterans-based group, Our Corps.

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Daniel Ward, Head of RISK IRC, CIB Americas, BNP Paribas

Daniel Ward heads the Risk-IRC (Independent Review and Control) function for BNP Paribas North America CIB/IP. This encompasses both Model Independent Review and Model Governance. His responsibilities include establishment of a robust Model Risk Management framework within the region working with the Global and IHC heads of Risk-IRC to ensure global and transversal alignment.

Additionally he is responsible for ensuring all models within scope are independently challenged and validated to appropriate standards, requiring both building out the local Model Independent Review team and ensuring local US needs are met by global validation teams. Prior to this position Daniel spent ten years in positions across Quantitative Research and Trading and Anti-Fraud based both in the US and UK for BNP Paribas. He has been instrumental in devising and developing a number of products which BNP Paribas continues to actively market to clients.

Prior to joining BNP Paribas, Daniel spent time in technology and trading firms, including as a trader at Goldenberg, Hehmeyer and Co. focusing on fixed income derivatives. Daniel received his Masters in Mathematics from Warwick University. He is a member of the ACFE and in this role is actively working to develop the Anti-Fraud community around Investment Banking in New York.

Ximena Zambrano
 Ximena Zambrano, Head of Qualitative Model Validation, Wells Fargo

Ximena has over 20 years of experience in the Banking Industry as a Risk Manager and currently leads the Qualitative Validation function for Wells Fargo. In her role she is responsible define the standards and processes to validate qualitative models across the enterprise and execute on these validations.

Ximena has had extensive experience in her career in leadership roles across consumer credit risk, consumer analytics, credit operations and credit strategy design and implementation.

Before joining Wells Fargo, she worked at Ally Financial where she held roles in analytics, loan review and was Chief Risk Officer for the International Operation and at Citibank where she led functions across the credit spectrum in the US and internationally.

Ximena holds a BSc Industrial Engineering from Los Andes University and MBA from Duke University – Fuqua School of Business. She lives in Charlotte, NC with her husband and daughter.

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 Jing Zou, Managing Director, 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, Retail Credit models, and interest rate derivatives models. She also developed Comprehensive Capital Analysis and Review (CCAR) model fragility analysis, which identifies the impact of model uncertainty on capital ratios. She is an invited speaker for many industry model risk management training courses.

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 and has expanded the scope to cover the validation of 40% of CCAR models. 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.

Post-Congress Masterclass | October 9 | Managing Machine Learning Model Risk
Intensive and interactive one-day Masterclass led by Wells Fargo

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Dr. Jie Chen, Head of Statistics and Machine Learning, Wells Fargo

Jie Chen is Managing Director in the Advanced Technologies for Modeling (AToM) Group of Corporate Model Risk at Wells Fargo. She is leading the Statistics and Machine Learning team, focusing on development of cutting-edge models, algorithms, and a computing platform to advance the Bank’s practice in the areas of credit, operational, and market risk management. She has over ten year experience on machine learning, artificial intelligence and advanced statistics in the banking industry.

Jie holds a Ph.D. in Statistics from the Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, and a bachelor’s degree in Computational Mathematics from Nanjing University.

Bernhard Hientzsch
Dr. Bernhard Hientzsch, Head of Model, Library, and Tools Development, Wells Fargo

Dr. Bernhard Hientzsch will be presenting at the Model Risk Management Masterclass.

harsh
Dr. Harsh Singhal, Head of Decision Science and Artificial Intelligence Validation, Wells Fargo

Harsh Singhal is Head of Decision Science and Artificial Intelligence Validation within the Model Risk group. His team is responsible for validating and approving all retail Credit Decision, Commercial Credit Rating, Financial Crimes & Fair Lending including Fraud and BSA/AML, Operations Risk, Marketing, and other artificial intelligence/machine learning models.

Prior to his current position, Harsh was responsible for new model development for Wholesale Risk in Bank of America. Harsh also led the Retail IRB model qualification at Bank of America and contributed towards the development of first generation of deposit balance models for Asset-Liability management.

Prior to joining the financial industry, he worked on quantitative modeling for pharmaceutical and telecom industries. He is passionate about developing quantitative talent and fostering a culture of responsibility and intellectual curiosity. His technical expertise includes machine-learning, multivariate analysis, commercial and consumer credit.
He has Master’s degree in Electrical Engineering and a Ph.D. in Statistics.

Agus-Sudjianto--120x120
Dr. Agus Sudjianto, Head of Corporate Model Risk, Wells Fargo

Agus Sudjianto is an executive vice president and head of Corporate Model Risk for Wells Fargo, where he is responsible for enterprise model risk management.

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. 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 a product design manager in the Powertrain Division of Ford Motor Company.

Agus holds several U.S. patents in both finance and engineering. He has published numerous technical papers and is a co-author of Design and Modeling for Computer Experiments. His technical expertise and interests include quantitative risk, particularly credit risk modeling, machine learning and computational statistics.

He holds masters and doctorate degrees in engineering and management from Wayne State University and the Massachusetts Institute of Technology.

Post-Event Masterclass: October 9
Managing Machine Learning Model Risk

Led by:

jie chen

Dr. Jie Chen
Head of Statistics and Machine Learning
Wells Fargo

Bernhard Hientzsch

Dr. Bernhard Hientzsch
Head of Model, Library, and Tools Development
Wells Fargo

harsh

Dr. Harsh Singhal
Head of Decision Science and Artificial Intelligence Validation
Wells Fargo

Agus-Sudjianto--120x120

Dr. Agus Sudjianto
Head of Corporate Model Risk
Wells Fargo

Registration opens at 8:30, Masterclass commences at 9am and will conclude by 5pm. There will be adequate time for refreshment breaks and lunch, to allow for networking with peers. We request that attendees have a full charged laptop, with Excel installed, to fully engage with the Masterclass.

Due to the interactive nature of the Masterclass, seats are limited and once the quota is reached registration will automatically close.

The adoption and ubiquity of machine learning in Financial Institutions pose a set of new model risks. This workshop is intended to provide practitioners in model development, validation, and governance to take advantage the power of machine learning and to understand and manage their model risks.

The following topics will be covered in the workshop:

Introduction

Machine learning applications in banking
Model risk in machine learning
Explainable and trusted machine learning

Introduction to machine learning methodology

Supervised Learning: Random Forest, Gradient Boosting Machine, and Neural Networks
Unsupervised Learning and Reinforcement Learning
Transfer Learning and Generative Adversarial Network

Examples of advanced machine learning applications in banking

Credit Modeling and Stress Testing
Derivative pricing and CVA using deep learning
Value at Risk and Multivariate Time-Series Modeling using Generative Adversarial Network

Explainability and interpretation techniques for machine learning

Diagnostic techniques
Variable/feature importance: local (LIME and SHAP) and global importance (SHAP, Sobol, Permutation Test, ANOVA)
Effects of Input/Outputs (PDP, ICE and Derivative-based approach)
Model distillation (Tree, KLIME. LIME-SUP)
Structured-Interpretable models: Explainable Neural Networks

Validation Framework

Model suitability and conceptual soundness: model bias and explainability
Model robustness and stability
Model implementation and safety: cautious generalization and fail-safe mode
Change control: model retraining and monitoring
Managing vendor models

Testimonials from past attendees of this masterclass:

A comprehensive overview of commonly used ML algorithms was very informative…lot’s of content being covered..the trainers are very knowledgable

Overall Rating: 5/5

– Ally

Agus and his team are very insightful in the Neural Networks in Deep Learning (NNDL) interpretability session…Great Job, thanks!

Overall Rating: 5/5

– Fannie Mae

Quick overview of useful practical information at a fabulous pace.

Overall Rating: 5/5

– BNP Paribas

11th July 2019

Reviewing the evolution of model risk management and managing innovation with management and oversight

By Sophie Bottazzi, Senior Research Executive, CeFPro
8th July 2019

Model risk: Model transparency & ensuring effective validation

10th June 2019

Climate-linked scenarios and credit risk modelling

By Giorgio Baldassarri, Global Head of Analytic Development Group, S&P Global Market Intelligence
31st May 2019

Challenges and opportunities of model risk reporting

By Herman Graaff, Head of Model Validation, de Volksbank
28th May 2019

Effective model risk and incorporating effective controls to guard against model errors and allow for quick response

By Paul Burnett, Global Head of Traded Risk Analytics, HSBC
20th May 2019

Implementation challenges and short comings of the most recent regulations within MRM

By Azar Khurshid, Director, Global Risk Management, Mizuho International
15th April 2019

Challenges and practices of effective existing model landscape maintenance

By Darius Grinvaldas, Head of Credit Risk Modelling 1 (PD Maintenance) / GRM Vilnius Site Leader, Danske Bank A/S
12th April 2019

Expectations for internal audit: What a good control environment looks like

By Gilles Artaud, Group General Inspection – Supervisor, Crédit Agricole SA
5th April 2019

Effective identification and measurement of model risk for a full view of inventory

By Tanguy Dehapiot, Head of Valuation Risk, BNP Paribas
12th March 2019

Credit risk modeling: Leveraging technology advances for enhanced credit risk modelling

By Shannon Kelly, SVP, Director, Model Risk Management, Zions Bancorp
12th March 2019

Collecting and storing quality data for CECL model requirements

By Shannon Kelly, SVP, Director, Model Risk Management, Zions Bancorp
4th March 2019

Assessment of model risk in the aggregate: Contributions of quantification

By Liming Brotcke, Quantitative Manager, Federal Reserve Bank of’ Chicago & Ray Brastow, Senior Financial Economist, Federal Reserve Bank of Richmond
28th February 2019

Defining and managing qualitative models

By Ximena Zambrano, Head of Qualitative Model Validation, Wells Fargo
14th February 2019

Managing model risk governance to maintain accuracy across lifecycle

By Chris Smigielski, VP Model Risk Director, TIAA 
11th December 2018

Center for Financial Professionals announces new FinTech Research and Advisory Board

Senior practitioners across the financial services industry join FinTech Advisory Board for the Global FinTech 250 Report set to be released at the X-Tech 2019 Convention […]
20th September 2018

How to find the remarkable value hiding in CECL compliance data

By John Dalton, Director, Product Strategy Management, Financial & Risk Management Solutions, Fiserv
12th September 2018

Protiviti offers three-part model risk webinar series

12th September 2018

How prepared do you feel financial institutions are for the implementation of CECL?

10th September 2018

Model Risk Management Webinar: The road ahead – Emerging trends in MRM

7th September 2018

Stress Testing USA – Classifying a Model vs Tool for an Effective Model Risk Management Framework

By Elizae Dalvi, VP, Model Risk Management, BankUnited.

2019 Co-Sponsor:

Andrew Davidson & Co., Inc


Andrew Davidson & Co., Inc. (AD&Co) was founded in 1992 by Andy Davidson, an international leader in the development of financial research and analytics, mortgage-backed securities product development, valuation and hedging, housing policy and GSE reform and credit-risk transfer transactions.

Since its inception, the company has provided institutional fixed-income investors and risk managers with high quality models, applications, consulting services, research and thought leadership, aimed at yielding advanced, quantitative solutions to asset management issues. AD&Co’s clients include some of the world’s largest and most successful financial institutions and investment managers.

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 +1 888 677 7007 where a member of the team will be happy to tailor the right package for you.

How can your organization benefit from a CeFPro partnership?

Venue:

Millennium Times Square
145 West 44thStreet
New York
NY 10036
USA

View venue website here

Preferential rates at the Millennium Times Square New York Hotel:

We have secured a preferential rate of $249++ per night at the Millennium Hotel from October 6 to October 10. Please note that we have limited number of rooms available and we advise you to book your accommodation as soon as possible. This rate will expire on September 17 2019 or if our quota is met.

Please click here to book your room

Are there any rules on the dress code?

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.

What is the cost and what is included in the registration fee?

We offer incentives for ‘early bird’ registrants of the Course, as outlined on our pricing structure.

Registration includes breakfast, refreshment breaks, lunches, full access to the Congress sessions and exhibition area. Presentations from sessions are also available, subject to speaker approval.

Where can I find the Congress documentation and speaker presentations?

All registered attendees will receive an email with access to documentation and speaker presentations after 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.

Will breakfast, lunch and refreshment be provided?

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.

This will be provided on both days of the Congress.

Will there be opportunities to network with other attendees?

There are ample opportunities for networking and interaction throughout the Course, such as

  • Breakfast, lunch and refreshment breaks
I have several colleagues that would like to attend, is there a group discount?

Certainly! We are pleased to offer you a 50% discount on the third registration or provide a fifth registration for free.

If you would like to register more than five colleagues please contact us on +1 888 677 7007

Please note:

  • Registrations must be made at the same time
  • Registrations must come from the organization
  • The lowest registration will be discounted
Are media partnerships available for Model Risk Management Congress?

Yes. As part of a media partnership we can offer a variety of options to increase the branding and awareness of your association, company, certificate, publication or media. We are flexible with what we can offer however we usually:

  • Provide a discounted rate to attend
  • Place your logo and profile on the Course website
  • Place your logo on the Course brochure
  • Place your logo on promotional content where applicable
  • Distribute your media/marketing at the Course
  • Promote through social media channels

To discuss this further please contact amy.greene@cefpro.com or call +1 888 677 7007.

Earn up to 21 CPE Credits

Earn up to 14 CPE Credits for the two-day Congress and up to 7 CPE Credits for also attending the Masterclass.

  • Prerequisites: Knowledge of financial risk management
  • Advanced Preparation: No advanced preparation is required
  • Program Level: Intermediate to advanced
  • Delivery Method: Group-live

The Center For Financial Professionals is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.learningmarket.org

Please note these are subject to change as per the agenda and final credits will be available after the event.

Representing a financial institution
(E.g. Bank, Insurance company, Asset Manager, Regulator)

Super Early Bird

Early Bird

Standard Rate

Main Event Only

$999

Until August 30
SAVE $500

$1,199

Until September 20
SAVE $300

$1,499

After September 20

Masterclass Only

$599

Until August 30
SAVE $300

$699

Until September 20
SAVE $200

$899

After September 20

Main Event + Masterclass

$1,598

Until August 30
SAVE $800

$1,898

Until September 20
SAVE $500

$2,398

After September 20

Representing an information/service provider
(E.g. Consultant, Vendor, Executive Search Firm, Law Firm)

Super Early Bird

Early Bird

Standard Rate

Main Event Only

$1,599

Until August 30
SAVE $500

$1,799

Until September 20
SAVE $300

$2,099

After September 20

Masterclass Only

$599

Until August 30
SAVE $300

$699

Until September 20
SAVE $200

$899

After September 20

Main Event + Masterclass

$2,198

Until August 30
SAVE $800

$2,498

Until September 20
SAVE $500

$2,998

After September 20

Group rates are available for 3 or more attendees from the same organisation, when registering at the same time. The current rate allows every third colleague to come along for half price or a fifth colleague to attend for free!

Other ways to register

1. Save Time – Register by Email

Simply email us with your e-signature – and we will do the rest for you!

2. Contact Us Directly

+1 888 677 7007

EARN UP TO
21 CPE CREDITS

Connect With Us
#MRMUSA

2019 Co-Sponsor:

#MRMUSA

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