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

RaficFahs

Rafic Fahs,
Chief Model Risk Officer,
Fifth Third Bank

OlgaCollins

Olga Collins,
ED, Global Head of Model Risk Infrastructure and Reporting,
Morgan Stanley

AlexM

Alexandre Maurel,
Head of US CIB Model Validation Team,
BNP Paribas

KerriAnderson

Kerri Anderson,
Assistant Director of Model Risk Management,
Northwestern Mutual

GeorgeSOulellis

George Soulellis,
Chief Enterprise Model Risk Officer,
Freddie Mac

Steve_Zhou

Steve Zhou,
MD, Model Risk Management,
Webster Bank

Agus

Agus Sudjianto,
EVP, Head of Corporate Model Risk,
Wells Fargo

Mazin_Joumaa_20220719_0141

Mazin Joumaa,
VP, Head of Model Risk Management,
Navy Federal Credit Union

Photo

Jing Zou,
MD, Model Risk Management,
Royal Bank of Canada

Shawn_Tumanov_-_BMO1

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.

.

8:00 Registration and breakfast

8:50 Chair’s opening remarks

REGULATION

9:00 Reviewing the global regulatory agenda and future updates to include additional scope

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

9:35 Managing evolution of inventory and expanded definition of model beyond traditional concepts

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

10:50 Enhancing and optimizing model risk management programs in line with internal business objectives

Session details 

      • 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

Mazin Joumaa, VP, Head of Model Risk Management,  Navy Federal Credit Union

NFR

11:25 Inclusion of operational risks under model risk including cyber risk and fraud models

Session details 

    • 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

Chris Smigielski, Model Risk Director,  Arvest Bank

AI/ML

12:00 Implementing a dynamic model risk management framework for oversight of AI and machine learning

Session details 

    • 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

1:35 Reviewing expectations and management of vendor/black box models with limited control and visibility

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

2:20 Enhancing methods for explainability of AI and machine learning models

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

2:45 Understanding ethics and fairness considerations and approaches for effective measurement

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

4:00 Understanding new methodologies and trends in the fundamentals of 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

4:35 Updating governance practices in line with evolution of model risk management scope

Session details 

        • 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

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

9:00 A deep dive into 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

9:35 Reviewing model input and understanding output to better monitor and capture 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

10:40 Developing frameworks to for climate risk data and model requirements

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

11:25 Modeling the macro economy: Model risk challenges in a volatile environment

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

1:20 Managing models in a recession environment and proactive identification of changes

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

1:55 Development and effective validation techniques for 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

2:30 Reviewing lessons learned from Covid-19 and impact to model outputs with extreme data

Session details 

    • 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

3:35 Collaboration of three lines of defense for effective oversight and validation of model risk

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  

4:20 Enhancing resilience and robustness of models to manage changes

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

KerriAnderson

Kerri Anderson,
Assistant Director of Model Risk Management,
Northwestern Mutual

OlgaCollins

Olga Collins,
ED, Global Head of Model Risk Infrastructure and Reporting,
Morgan Stanley

RaficFahs

Rafic Fahs,
Chief Model Risk Officer,
Fifth Third Bank

Biography

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.

Biography

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

Biography coming soon.

Seyhun Hepdogan

Seyhun Hepdogan,
Director of Model Risk Management,
Discover financial services

Mazin_Joumaa_20220719_0141

Mazin Joumaa,
VP, Head of Model Risk Management,
Navy Federal Credit Union

Speaker HS

Raghu Kulkarni,
Head of Model Development,
Discover FInancial

Biography

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.

Biography

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

Biography coming soon.

AlexM

Alexandre Maurel,
Head of US CIB Model Validation Team,
BNP Paribas

RodericK Powell

Roderick Powell,
Senior Vice President – Head of Model Risk Management,
Ameris Bank

Alex Shenkar

Alex Shenkar,
SVP, Senior Model Validation Officer, Model Risk Oversight, Team Lead for Credit & Loss Forecasting,
Truist

Biography

Biography coming soon.

Biography

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.

Biography

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

Chris Smigielski,
Director of Model Risk Management,
Arvest Bank

GeorgeSOulellis

George Soulellis,
Chief Enterprise Model Risk Officer,
Freddie Mac

Agus

Agus Sudjianto,
EVP, Head of Corporate Model Risk,
Wells Fargo

Biography

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

Biography coming soon.

Biography

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_-_BMO1

Shawn Tumanov,
Director, Data and Analytics (AI/ML/RPA) Governance,
BMO Financial

Speaker HS

Kiran Yalavarthy,
EVP, Head of Risk Modeling Group,
Wells Fargo

Steve_Zhou

Steve Zhou,,
MD, Model Risk Management,
Webster Bank

Biography

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

Biography coming soon.

Biography

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.

Photo

Jing Zou,
MD, Model Risk Management,
Royal Bank of Canada

Biography

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.

WHY SHOULD YOU ATTEND A CEFPRO CONFERENCE?
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.

March 9, 2023

Top of mind for a CRO: A holistic view of risk

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
March 9, 2023

Collaboration of three lines of defense for effective oversight and validation of model risk

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
February 23, 2023

Collaboration of three lines of defense for effective oversight and validation of model risk

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
February 22, 2023

Adjusting models in a fast changing economic environment

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
February 2, 2023

Inclusion of operational risks under model risk including cyber risk and fraud models

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
August 15, 2022

Developing climate stress testing and forecasting capabilities to accurately assess climate impacts on the organization

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
July 18, 2022

Managing the continuous evolution of model risk with increased digitalization

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
July 15, 2022

Understanding data requirements and other elements to mitigate greenwashing risks

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
July 14, 2022

Leveraging scenario analysis and quantification methods to better identify impact of disruption

The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular […]
June 25, 2022

Implementing a Trade Surveillance Program to increase fraud detection

The views and opinions expressed in this article are those of the thought leaders as individuals, and are not attributed to CeFPro or any particular organization. […]
June 10, 2022

Digitalization: driving a new era in model risk

The views and opinions expressed in this article are those of the thought leaders as individuals, and are not attributed to CeFPro or any particular organization. […]
June 10, 2022

Automating model risk management activities to increase efficiency

The views and opinions expressed in this article are those of the thought leaders as individuals, and are not attributed to CeFPro or any particular organization. […]

Biography

Company biography coming soon.

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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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There is no accommodation available at the venue, however there are plenty
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Can I present at the Advanced Model Risk USA Congress?

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.

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 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.

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*. 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.

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.

Will there be opportunities to network with other attendees?

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
Are there opportunities to share my thought-leadership at the Advanced Model Risk USA Congress?

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

Are media partnerships available for the Advanced Model Risk USA 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 Congress website
  • Place your logo on promotional content where applicable
  • Distribute your media/marketing at the Congress
  • Promote through social media channels

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

What can I do if I can't attend the event due to Covid-19?

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.

Are CPE Credits available?

Yes, CPE Credits are available for the Advanced Model Risk Congress.

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

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$699
Save £300

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$999

after March 3  

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EARLY BIRD
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$1,399*

until January 27 

$1,599*

until March 3 

$1,999*

after March 3  

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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Magazine

iNFRont Magazine is CeFPro’s unique bi-monthly industry publication. Featuring contributions from practitioners around the world as they address the most critical themes and challenges to take over the operational/non-financial risk sector, forward plan your next move with iNFRont.

Free to download, find out more.

Fintech Leaders is one of the most comprehensive industry led analysis on the status and direction of financial technology implementation. The objective of the research aims to gain a greater insight into fintech whilst assessing the key opportunities, investment priorities, main challenges and benefits, and exploring the road ahead.

Fintech Leaders also serves as a guide on the key solutions providers within the industry and the top players to support institution’s fintech needs, as voted for by the industry itself.

Click here to find out more.

As the operational and non-financial risk arena continues to rapidly evolve, expand, and gain significance, Non-Financial Risk (NFR) Leaders strives to provide risk professionals with insights, support, and benchmarks to guide them through the changing risk landscape.

NFR Leaders collates the knowledge of nearly 1,000 non-financial risk professionals to provide a ‘voice of the market’. Critical themes addressed within the report include the top non-financial risks, areas attracting the greatest investment, the extent of the Covid-19 pandemic’s impact, and much more.

Find out more about NFR Leaders.

Infront Magazine
Infront Magazine