Enrico leads the Modelling team for the Corporate Security department at Banco Bradesco S.A., managing the full model lifecycle for Application Fraud, Transactional Fraud and AML. His duties include Model Risk governance, reporting to senior executives and committees, and engaging with suppliers for external models and solutions.
Past responsibilities include Analytics, MIS, and fraud risk evaluation/mitigation in new product launches. Further past experiences include Credit Risk and the Telecommunication sector.
He earned a Master’s in Mathematics, before specializing in Banking and earning a PhD in Strategic Management. His research themes are Fraud/AML, Innovation and IoT.
His most recent publication is the article “Strategic Management of Credit Card Fraud: Stakeholder mapping of a card issuer” in the Journal of Financial Crime.
Francisco Rivadeneyra in the Director for CBDC & FinTech Policy and Research at the Bank of Canada. In this role he leads a team developing policy advice in areas of central bank digital currency, electronic money and payments, and the implications for central banks of broader financial innovations. He also is an active researcher working in the intersection of technology, payments infrastructures and finance. His current research studies the security and convenience trade-off of digital currencies and the use of artificial intelligence in the liquidity management problem of commercial banks. His previous work has been on the management of domestic debt and foreign reserves for the Government of Canada.
Mr. Rivadeneyra holds a PhD in Economics from the University of Chicago.
PhD in Computer Science by Federal University of São Carlos (UFSCar) with projects in Data Science and Artificial Intelligence, Gustavo Botelho is currently Senior Advisor in Artificial Intelligence at Banco do Brasil, one of the major public Brazilian banks and also Graduate Professor in Artificial Intelligence at IESB. He has also an MBA degree in People Management and was a Short-Term Scholar at Michigan State University (MSU).
Currently working out the exciting puzzle of industrializing AI (artificial intelligence) software. I have previously worked extensively in data driven roles in finance and health care, both at technical and strategic levels. As a scientist in large corporations, I have experienced the challenges of innovating through highly regulated industries where cybersecurity is paramount. As a senior manager, I’m now discovering the fascinating world of software engineering, DevOps and the Cloud in order to solve how to best embed AI in financial business processes – starting with chatbots and credit risk decision machine learning models. As professional, I am doing my best to positively influence important cultural and digital transformations.
Stuart Cook is a senior business leader based in Austin, via Silicon Valley and London. He has over 15 years of experience in global financial services, both in start-up and enterprise companies. He joined Valley in 2019 as the Bank’s Chief Digital Product Officer. In this role, he is focused on creating great customer experiences, building growth and leading teams through product discovery and delivery.
He is responsible for overseeing the creation and development of Valley’s digital product and propositions as
well as transforming to more agile ways of working, leveraging cloud native and automated
infrastructure to help make the customer experience more seamless and streamlined.
Quantitative Finance Expert with a demonstrated history of working in the banking industry. Skilled in financial risk management, digital banking, security and integrity protection techniques in the digital era, statistical modeling, machine learning, regulatory stress testing among others with a Doctor of Philosophy (PhD) focused in Financial Mathematics from Université de Montréal (UdeM).
My current research interests lie primarily in emerging technologies, FinTech, and their applications in the banking industry. Working and staying on top of the current trends in digital banking, Internet of Things (IoT), and cryptocurrencies.
My other research interest has focused on:
1: Credit risk modelling as well as studying machine learning (ML) models, in particular Neural Networks (NN), and their applications in the banking/insurance industry; and
2: Fraud detection techniques leveraging AI approaches in the age of digital banking.
The Vice President in Citi Bank’s Model Risk Management Division. He was invited as a Keynote speaker to present on Fraud Analytics using Machine Learning at the International Automation in Banking Summit in New York in November 2019. Vishal has experiences in quantitative risk modeling using advanced engineering, statistical and machine learning technologies. His academic qualifications in combination with a PhD in Chemical Engineering and an MBA in Finance have enabled him to challenge quantitative risk models with a scientific rigor. Vishal’s doctoral thesis included the development of statistical and machine learning based risk models—some of which are currently being used commercially. Vishal has 120+ peer-reviewed citations in areas such as risk management, quantitative modeling, machine learning and predictive analytics.
Quantitative Risk Modeling of Hydrate Bedding using Mechanistic, Statistical, and Artificial Neural Network Frameworks
Nitesh Soni is a Director at Scotiabank where he is leading end-to-end advanced analytics and AI projects for Business Functions areas. His career spans over 15 years across top tier banks, consulting firm and world leading research institutes with a core expertise in Predictive modeling, Machine Learning, AI and Big Data. He is a regular speaker at the various national and international conferences. While as a researcher, he has been a part of a couple of major discovery experiments and has won few prestigious awards. He holds a PhD degree in Experimental Particle Physics.
Manuela M. Veloso is the Head of J.P. Morgan AI Research, which pursues fundamental research in areas of core relevance to financial services, including data mining and cryptography, machine learning, explainability, and human-AI interaction. J.P. Morgan AI Research partners with applied
data analytics teams across the firm as well as with leading academic institutions globally.
Professor Veloso is on leave from Carnegie Mellon University as the Herbert A. Simon University Professor in the School of Computer Science, and the past Head of the Machine Learning Department. With her students, she had led research in AI, with a focus on robotics and machine learning, having concretely researched and developed a variety of autonomous robots, including teams of soccer robots, and mobile service robots. Her robot soccer teams have been RoboCup world champions several times, and the CoBot mobile robots have autonomously navigated for more than 1,000km in university buildings.
Professor Veloso is the Past President of AAAI, (the Association for the Advancement of Artificial Intelligence), and the co-founder, Trustee, and Past President of RoboCup. Professor Veloso has been recognized with a multiple honors, including being a Fellow of the ACM, IEEE, AAAS, and AAAI. She is the recipient of several best paper awards, the Einstein Chair of the Chinese Academy of Science, the ACM/SIGART Autonomous Agents Research Award, an NSF Career Award, and the Allen Newell Medal for Excellence in Research.
Professor Veloso earned a Bachelor and Master of Science degrees in Electrical and Computer Engineering from Instituto Superior Tecnico in Lisbon, Portugal, a Master of Arts in Computer Science from Boston University, and Master of Science and PhD in Computer Science from Carnegie Mellon University. See www.cs.cmu.edu/~mmv/Veloso.html for her scientific publications.