RAI Program and Exam

Dr. Breeden has been designing and deploying risk management systems for loan portfolios since 1996. He founded Deep Future Analytics in 2011, which focuses on portfolio and loan-level forecasting solutions for pricing, account management, stress testing, and CECL,  serving banks, credit unions, and finance companies. He is also the owner of auctionforecast.com, which predicts the values of fine wines using a proprietary database with over 2.5 million auction prices.

He is member of the board of directors of Upgrade, a San Francisco-based FinTech; an Associate Editor for the Journal of Credit Risk, the Journal of Risk Model Validation, and the Journal of Risk and Financial Management; and President of the Model Risk Managers’ International Association (mrmia.org).

Dr. Breeden invented vintage analytics for lending in 1997 and created credit risk models through the 1995 Mexican Peso Crisis, the 1997 Asian Economic Crisis, the 2001 Global Recession, the 2003 Hong Kong SARS Recession, the 2007-2009 US Mortgage Crisis and Global Financial Crisis, and the COVID-19 Pandemic. These crises have provided Dr. Breeden with a rare perspective on crisis management and the analytics needs of executives for strategic decision-making. In 2018, Dr. Breeden invented multihorizon survival modeling, combining vintage analytics with behavior scoring using logistic regression or machine learning.

Dr. Breeden earned a Ph.D in physics, and has published over 90 academic articles, 8 patents, and 5 books.

Charles Currat is the Head of the Quantitative Modeling Development Center for Wealth and Investment Management (WIM) at Wells Fargo. His team provides innovative model development and quantitative solutions to broad business needs as well as governance support in accordance with supervisory guidance. Most recently his team led the research and development of advanced analytics in retail investor portfolio management, from construction to adoption for the Wells Fargo Investment Institute (WFII).

Currat has held risk management positions in different lines of defense at Wells Fargo since 2006 and previously served as Head of Methodology on the WIM Investment Risk team providing quantitative oversight and support for investment related processes. Prior to joining Wells Fargo, he was a postdoctoral researcher at the Lawrence Berkeley National Laboratory (LBNL).

Charles holds a doctorate in high energy physics from the University of Lausanne and a master’s in engineering physics from the Swiss Federal Institute of Technology Lausanne (EPFL). He is a Certified FRM® and serves as a member of GARP’s FRM Advisory Committee.

Agostino Capponi is a Professor in the Department of Industrial Engineering and Operations Research at Columbia University, where he is also the founding director of the Columbia Center for Digital Finance and Technology. Capponi earned his Ph.D in Computer Science and Applied Mathematics from the California Institute of Technology.

His current research interests are AI and machine learning in finance, financial technology, market microstructure, systemic and liquidity risk, and economic networks. His research has been recognized with the 2018 NSF CAREER award and with a JP Morgan AI Research Faculty award, and funded by major agencies, including NSF, DARPA, DOE, IBM, Ripple, and the Ethereum foundation. His research has also been covered by various media outlets, including Bloomberg, the Financial Times, VoX, and Politico. Capponi is a fellow of the crypto and blockchain economics research forum and an academic fellow of Alibaba's Luohan academy. He serves as an editor of Management Science in the Finance Department, editor of Operations Research in the Financial Engineering Department, and co-editor of Mathematics and Financial Economics. Agostino served as Chair of the SIAG/FME Activity Group and of the INFORMS Finance Section, and currently serves as a council member of the Bachelier Finance Society.

He is co-editor of the book "Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices", published in 2023 by the Cambridge University press and listed as one of the Amazon best sellers in banking and finance.

Rama Cont is Professor of Mathematical Finance at the University of Oxford, and Head of the Oxford Mathematical and Computational Finance Group.

He has authored several books and more than 100 research papers on mathematical modelling in finance, quantitative risk management, liquidity risk modeling, algorithmic finance, and applications of machine learning in finance.

Cont has worked for numerous financial institutions, CCPs, exchanges and regulatory bodies on a range of topics including pricing models for derivative securities, high-frequency market making algorithms, liquidity stress testing and risk management systems for CCPs.

He received the Louis Bachelier Prize from the French Academy of Sciences in 2010 and the Royal Society Award for Excellence in Interdisciplinary Research in 2017 for his work on systemic risk modelling.

Lucy da Piedade is a Risk Management leader with almost 30 years of experience spanning global financial services, risk advisory consulting and legal professional practice. She is currently the Chief Controls Officer for Consumer Banking and Payments at Barclays Bank responsible for first line of defence risk management for a portfolio of businesses including the Global Corporate and Transaction Bank, Private Bank and Wealth business, as well as the International Consumer Bank. Her focus is on identifying and addressing all non-financial risks in the business including Data, Privacy and Resilience Risk.

She trained as a lawyer in South Africa and the UK and began her career in commercial legal practice. She was an International Trade Remedies consultant with Deloitte & Touche later joining KPMG in their Taxation as well as Risk Advisory practices in London. She served as a Business negotiator in the tripartite team responsible for concluding the trade agreement between South Africa and the European Union in her capacity as International Trade Manager at the South African Chamber of Business.

Lucy holds an Master of Law degree from Exeter University in the UK and a MBA from the University of the Witwatersrand and Cranfield University in the UK. Fluent in five languages, she is a passionate advocate for diversity of thought and the importance of culture in effective risk management, regularly presenting on these topics to industry audiences.

Alexander Denev is the co-founder, CEO and Head of R&D at Turnleaf Analytics. With over two decades of experience in the area, he specializes in designing and implementing forecasting models and trading strategies based on Alternative Data.

His work at Turnleaf Analytics explores the complexities of market and economic variables and is facilitated by the innovative use of machine learning to model these intricate relationships cohesively. He has been a driving force behind the creation of big data driven financial models in the domain of inflation forecasting, leveraging his experience and expertise in quantitative methodologies and AI.

Denev is also a regular contributor in academia, having served for many years as a visiting lecturer at the University of Oxford. He has co-authored books such as "The Book of Alternative Data," "Portfolio Management under Stress," and "Probabilistic Graphical Models – a New Thinking in Financial Modelling”, where he focuses on how alternative data and machine learning can disrupt the very traditional field of financial and macroeconomic forecasting.

Prior to his role at Turnleaf, Denev held several key positions, including Head of Artificial Intelligence at Deloitte LLP, Financial Services, and Head of Quantitative Research & Advanced Analytics at IHS Markit.

Christopher Donohue is the Managing Director of the GARP Benchmarking Initiative (GBI), a data utility for financial services companies to compare sensitive data. Previously, he led GARP’s Educational and Research Programs, with oversight including the Financial Risk Manager (FRM^®) and Energy Risk Professional (ERP^®).

Prior to joining GARP, Donohue’s roles included hedge fund partner responsible for the development of asset allocation tools for pension funds and automated trading systems; director in the Global Research Center at Deutsche Asset Management, leading product research and development; and Director of Optimization Technology at Alphatech, a technology and research defense contractor, where he led algorithm development for intelligence aircraft path planning and sensor scheduling systems.

Kenneth Doucet is Vice President of Content, Information and Continuing Education (CICE) at GARP, and oversees the development and ongoing enhancement of the educational content underlying GARP’s certification and certificate programs. Prior to joining GARP, Kenneth managed ACT’s Global Assessment Certificate (GAC) program, and prior to that spent 15 years overseeing business development for ProExam, a credentialing advisory services firm. He holds the MBA from the NYU Stern School of Business.

Raghurami Etukuru is an originator of the concept of "Complexity-Conscious Prediction," a novel approach that recognizes and integrates the inherent complexity of data by quantifying the complexity of input data and designing AI models tailored to this complexity.

He is an AI Scientist with over 25 years of industry experience, excelling in Data Science and AI, with a track record of impactful AI research and model development and is the author of the book "AI-Driven Time Series Forecasting: Complexity-Conscious Prediction and Decision-Making."

Kay Firth-Butterfield is the CEO of Good Tech Advisory and TIME's 100 Impact Awardee 2024.

She is the former Head of Artificial Intelligence and member of the Executive Committee at the World Economic 
Forum and is one of the foremost experts in the world on the governance of AI. She is a Barrister, former Judge and Professor, technologist and entrepreneur who has an abiding interest in how humanity can equitably benefit from new technologies, especially AI. She was the world’s first Chief AI Ethics officer.

Firth-Butterfield is author of books on Human Rights, AI and Modern Slavery and is a board member of many renowned organizations like the IEEE Global Initiative for Ethical Considerations in AI and Autonomous Systems, the Polaris Council for the Government Accountability Office (USA), the Advisory Board for UNESCO International Research Centre on AI, the Advisory Board for international company ADI, EarthSpecies and AI4All. She has been consistently recognized as a leading woman in AI.

Dr. Lukas Kölbl is Senior Manager at Accenture Applied Intelligence and Head of Data Science ASG (Austria, Switzerland, Germany). The focus of his daily work lies on the German, Swiss and Austrian markets where he focuses on E2E implementation of AI algorithms.

William May is Managing Director and Global Head of Certifications and Educational Programs at GARP. Prior to joining GARP, William had over 20 years of market experience including serving as a Senior Director in Fitch Ratings’ credit market research group and as a Senior Research Officer at UBS Wealth Management. He has worked for several buy-side and sell-side firms including Bank of America and Federated Investors as well as specialty firms like Andrew Kalotay Associates and Law and Economic Consulting Group. He began his career in the research function of the Federal Reserve Bank of New York and has worked on the Open Market Trading Desk and as a bank examiner. William holds a BS in applied mathematics and economics from Stony Brook University; an MBA and an MA in economics from Fordham University; an MS in financial engineering from the NYU Tandon School of Engineering; and an MS in applied statistics and MEd in applied psychology from Columbia University’s Teachers College. He is currently studying engineering, artificial intelligence, and engineering education at Penn State University.

Peter Millican has taught and researched across a broad range, from AI, philosophy of mind and language, to moral philosophy and philosophy of religion. Over 50 of his published papers have been on the interpretation, analysis, and assessment of classic philosophical arguments, deriving especially from the work of David Hume, but also Anselm, Locke, Russell, and Turing.

Peter has also – for nearly forty years – been working on the intersection between Philosophy and Computer Science, teaching and developing educational resources across this increasingly important intersection. Before moving to Oxford in 2005, he spent 20 years lecturing in Computing and Philosophy at the University of Leeds, and at Oxford, he created and oversees the elite degree program in Computer Science and Philosophy.

Yogesh Mudgal is currently the Head of Risk for Runtime Compute at JP Morgan Chase. His focus has been proactive risk management, developing strategic vision to uplift Technology Risk and Controls, risk reduction, and measurement. He believes that strong risk controls help reduce uncertainty and improve the quality of the products delivered.

Previously, Mugdal was Global Head of Enterprise Tech/Cyber Risk at Citi. At Citi, he established Emerging Technology Risk function, AI/ML and DLT Risk, and influenced establishing building blocks for AI risk and controls and firmwide AI Center of Excellence. Prior, he was at various financial institutions including Bloomberg where he established various security programs including Threat and Vulnerability Management. 

Mugdal was the founder and curator of AIRS (AI/ML Risk and Security), which was an industry group organically created with around 50 professionals from 20+ institutions. 

He is actively engaged in public speaking/ talks in various conferences on topics such as Operational Risk, Emerging Technology Risk, AI/ML risk and controls.

Carina Prunkl is Assistant Professor for Ethics of Technology at Utrecht University. Previously she worked as Research Fellow at the Institute for Ethics in AI, University of Oxford, and as Senior Research Scholar at the Future of Humanity Institute, University of Oxford. Prunkl works on the ethics and governance of artificial intelligence with a focus on algorithmic fairness, autonomy, and community governance. She advises governments, international organizations, and private firms on risks associated with AI technologies. Prunkl also worked as Ethics Advisor for Digital Catapult, the UK's innovation agency for advanced digital technology, as well as for the Artificial Intelligence Lab Brussels.

Anand Rao is Adjunct Professor in BITS Pilani’s APPCAIR AI Center. He also serves on the Advisory Board of Oxford University’s Institute for Ethics in AI, World Economic Forum’s Global AI Council, OECD’s Network of Experts on AI, OECD’s AI Compute initiative, Advisory Board of Northwestern’s MBAi program, Responsible AI Institute, Nordic AI Institute, and International Congress for the Governance of AI.

Rao focuses on research, innovation, applications, and adoption of data, analytics, and AI. He was Global Artificial Intelligence Leader for PwC. Before consulting Anand was Chief Research Scientist at the Australian Artificial Intelligence Institute.

He earned his Ph.D from University of Sydney and an MBA from Melbourne Business School. Anand has co-edited four books on Intelligent Agents and has published over fifty papers on Computer Science and Artificial Intelligence in major journals, conferences, and workshops. In addition, he has authored over 100 articles in the business and trade press. Among Anand’s awards include Most Influential Paper Award for the Decade in 2007 from the Autonomous Agents & Multi-Agent Systems organization. He was listed among the Top 50 Data & Analytics professionals in USA and Canada, Top 50 professionals in InsureTech, and Top 25 Technology Leaders in Consulting.

Alberto Rossi is the Hachigian Family Professor of Finance at the McDonough School of Business, Georgetown University. He is also the Director of the AI, Analytics, and Future of Work Initiative at Georgetown, a Visiting Fellow at Brookings, and a member of the Economic Advisory Committee (EAC) at FINRA. His research interests include FinTech, Household Finance, Machine Learning, and Asset Pricing. His recent work studies how robo-advisors can help individuals make better financial decisions and how to predict stock market returns using machine learning algorithms. He has worked extensively in analyzing big data and has collaborated with major brokerage houses, FinTech firms, and asset managers around the world.

Professor Rossi’s work has been published in leading academic journals such as the Journal of Finance, the Review of Financial Studies, the Journal of Financial Economics and Management Science. 

Before McDonough, he was an Associate Professor with tenure at the R.H. Smith School of Business, University of Maryland. He also worked as an economist at the Board of Governors of the Federal Reserve System in Washington, DC. He received his Ph.D. in Economics from the University of California, San Diego. 

Rajesh Shekar is a distinguished finance and machine learning professional with more than 25 years of industry experience. He is the founder of Numanic, a consultancy firm renowned for its expertise in AI consulting. Prior to establishing Numanic, he served as the Head of Global Data Science at H2O.ai, a leading company in automated machine learning. During his tenure, he collaborated with a multitude of Fortune 500 companies, addressing diverse use cases.

His extensive career also includes significant roles at prestigious organizations such as Moody's, AIG, Barclays, and Oracle. Rajesh is academically accomplished, holding dual Master's degrees in Mathematics of Finance from Columbia University and in Engineering from Purdue University. Additionally, he has earned a graduate certificate in Quantitative Finance and Risk Management from Stanford University. He is also a certified Financial Risk Manager (FRM) and holds the Chartered Financial Analyst (CFA) designation.

Stephen Slade is currently a senior lecturer in computer science at Yale, where he teaches the core course in artificial intelligence, as well as courses in information security and other topics.

As an undergraduate at Yale, he studied music. He returned to get his MS and PhD in computer science, focusing on artificial intelligence. His research is on cognitive models of decision making. He has written three books on computer programming and artificial intelligence. His recent focus is on computational models of digital ethics. He has been involved in AI for nearly 50 years.

Outside of Yale, he taught at the NYU Stern School of Business and designed information systems for several presidential campaigns, the White House, and Wall Street. He earned the FRM and served as a risk manager with several firms.

Agus Sudjianto is Senior Vice President of Risk and Technology at H2O.ai. He has 20+ years of experience in banking where he was an executive vice president, head of Model Risk Management at Wells Fargo, director of enterprise analytics at Lloyds Banking Group in the United Kingdom. Before joining Lloyds, he was an executive and head of Quantitative Risk at Bank of America.

Prior to his career in banking, he was an engineer and product design manager in the Powertrain Division of Ford Motor Company for more than a decade.

Sudjianto is the creator of PiML (Python Interpretable Machine Learning), a widely used integrated tool for developing and validating high risk machine learning models. He holds numerous U.S. patents in both finance and engineering. He has published extensively technical papers in machine learning and statistics and is a co-author of Design and Modeling for Computer Experiments. His technical expertise and interests include machine learning/AI applications, risk management, and computational statistics.

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

Bo Xu serves as a Principal at Boston Consulting Group (BCG), where he is a core member of the global GenAI expert team. His professional journey at BCG began in 2019, following a four-year tenure at KPMG in the risk consulting practice, concentrating on CCAR/DFAST model development and validation work.

In his role at BCG, Xu leads a multi-disciplinary team focused on AI and GenAI programs. His responsibilities encompass strategy development, AI/GenAI implementation, and change management. He also has expertise in credit risk analysis, model risk management, and data governance from his earlier career.
Bo holds a Bachelor’s degree in Economics from Anhui University (China) and a Master’s degree in Financial Engineering from Rensselaer Polytechnic Institute. 

Qiuyan Xu is the Founder and Managing Director of Gravitate AI, a Boston-based consultancy and development services company focused on AI technology. A firm believer in the democratization of AI, her company advises startups on AI solutions best suited to help their business scale, then leads the design, roadmap and development of AI-powered products and processes. She specializes in solution architectures, detail-oriented model building, and ML operation, and is fluent in the modern AI technical stack, including LLM, NLP, image analysis using deep learning models, and their deployment in scalable systems. In addition to being a C-level AI specialist, data scientist, and business executive with 15+ years’ experience, Xu is also an Angel Investor and LP in multiple venture funds, offering a unique perspective to startup founders on crafting their AI value proposition.

Xu holds a BS in Mathematics, and a Ph.D in Statistics. She got her start as a data practitioner successfully deploying marketing, pricing and risk management models for US Fortune 500 insurance companies, then built up big data analytics capabilities for FinTech startups until she founded Gravitate AI in 2019.