Storm50
Join us at STORM50, an event delving into the revolution of algorithmic engineering in finance. Explore key research areas, and leading-edge tech, and meet industry experts across 3 days from May 9-11, 2023

STORM50 Rankings
Recognizing the top technology vendors in the field
of algorithmic engineering in finance.
About the event
Join us May 9-11, 2023, for Chartis’ STORM event, dedicated to the rapidly evolving landscape of algorithmic engineering in finance. Over three days of illuminating discussions, a group of leading international subject matter experts will explore the diverse analytical innovations and the challenges institutions are facing in three areas: QuantTech, insurance and retail finance.
Chartis’ STORM research focuses on the computational infrastructure and algorithmic efficiency of technology tools used across the financial services industry. Structural transformations in the past few years have produced novel statistical modeling approaches (such as machine/deep learning and a range of heuristics) that are now foundational elements of the computing and modeling landscape.
The STORM event will feature presentations by prominent quantitative and computational specialists, who will delve into how to manage and solve practical challenges in the computing landscape. Attendees will have an opportunity to engage with speakers covering such topics as adjoint algorithmic differentiation (AAD), MLOps, price optimization and economic scenario generation. Don’t miss this opportunity to join these pioneering experts ‒ and Chartis’ veteran research analysts ‒as they discuss the state-of-the-art technologies in finance. At the end of each day of the event, Chartis will announce its vendor rankings in the following three categories:
• Day 1: The QuantTech50
• Day 2: Insurance Analytics25
• Day 3: Retail Finance Analytics25
Register today!

Advisory Board

Wim Schoutens
Professor
University of Leuven
Wim Schoutens is a quantitative finance professor at the University of Leuven, Belgium.
He has extensive practical experience of model implementation and validation. He is well known for his consulting work with the banking industry and national and supra-national institutions. He is an independent expert advisor to the European Commission, has worked for the IMF and is the author of several books on quantitative finance.
His latest books, co-authored with Dilip Madan, are about the brand new theory of conic finance.
He is also a member of different editorial Boards of international finance journals. Wim is also a founding partner of RiskConcile, a fintech company with roots within the University of Leuven.
He likes arbitrages, politically incorrect statements and making jam.

Andrew Green
Managing Director and Lead GFI Quant
Scotiabank
Andrew Green is a Managing Director and lead XVA Quant at Scotiabank in London. He is the author of XVA: Credit, Funding and Capital Valuation Adjustments which is published by Wiley, co-editor of Landmarks in XVA which is published by Risk Books and co-author of a number of technical articles on XVA in recent years.

Uwe Naumann
Professor for Computer Science
RWTH Aachen University
Uwe Naumann is the author of the popular text book on (Adjoint) Algorithmic Differentiation (AAD) titled "The Art of Differentiating Computer Programs" and published by SIAM in 2012. He holds a Ph.D. in Applied Mathematics / Scientific Computing from the Technical University Dresden, Germany. Following post-doctoral appointments in France, the UK and the US, he has been a professor for Computer Science at RWTH Aachen University, Germany, since 2004. As a Technical Consultant for the Numerical Algorithms Group (NAG) Ltd. Uwe has been playing a leading role in the delivery of AAD software and services to a growing number of tier-1 investment banks since 2008.

Luca Capriotti
Managing Director - Global Head Quantitative Strategies, Credit
Credit Suisse
Luca Capriotti is a Managing Director at Credit Suisse, based in London, where he works in Quantitative Strategies and he is responsible for Credit Products in Europe, and globally for Corporate Bank and Treasury. Previous to this role, he was US head of Quantitative Strategies Global Credit Products, he has worked in Credit and Commodities Exotics in New York and London and in the cross-asset modeling R&D group of GMAG in the London office.
Luca is also visiting professor at the Department of Mathematics at University College London. His current research interests are in the fields of Machine Learning, Algorithmic Trading, Credit Models and Computational Finance, with a focus on applications of Adjoint Algorithmic Differentiation (AAD) for which he holds a US Patent.
Luca gives regularly gives seminars and courses worldwide. He has served as supervisor and external examiner for Master and PhD programs and as referee for several scientific publications .
Prior to working in Finance, Luca was a researcher at the Kavli Institute for Theoretical Physics, Santa Barbara, California, working in the field of High Temperature Superconductivity and Quantum Monte Carlo methods for Condensed Matter systems.
Luca holds a M.S. cum laude in General Physics from University of Florence (1996), and an M.Phil. and Ph.D. cum laude in Condensed Matter Theory, from the International School for Advanced Studies, Trieste (2000).

Petter Kolm
Clinical professor & director of the mathematics in finance
Courant Institute of Mathematical Sciences, New York University
Petter Kolm is the Director of the Mathematics in Finance Master’s Program and Clinical Professor at the Courant Institute of Mathematical Sciences, New York University and Partner at CorePoint-Partners.com. Previously, Petter worked in the Quantitative Strategies Group at Goldman Sachs Asset Management. Petter has coauthored four books: Financial Modeling of the Equity Market: From CAPM to Cointegration (Wiley, 2006), Trends in Quantitative Finance (CFA Research Institute, 2006), Robust Portfolio Management and Optimization (Wiley, 2007), and Quantitative Equity Investing: Techniques and Strategies (Wiley, 2010). He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich.
Petter is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Financial Data Science (JFDS), Journal of Investment Strategies (JoIS), and Journal of Portfolio Management (JPM). He is an Advisory Board Member of Alternative Data Group (AltDG), AISignals and Operations in Trading (Aisot), Betterment (one of the largest robo-advisors) and Volatility and Risk Institute at NYU Stern (VRI). Petter is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and Scientific Advisory Board Member of Artificial Intelligence Finance Institute (AIFI).
As a consultant and expert witness, Petter provides services in areas including alternative data, data science, econometrics, forecasting models, high-frequency trading, machine learning, portfolio optimization with transaction costs and taxes, quantitative and systematic trading, risk management, robo-advisory, smart beta strategies, tax-aware investing, and transaction costs.
Speakers

Fabio Mercurio
Head of Quant Analytics
Bloomberg L.P.
Fabio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU. He has jointly authored the book "Interest rate models: theory and practice" and published extensively in books and international journals, including 20 cutting-edge articles in Risk Magazine.
Fabio is the recipient of the 2020 Risk quant of the year award.

Wim Schoutens
Professor
University of Leuven
Wim Schoutens is a quantitative finance professor at the University of Leuven, Belgium.
He has extensive practical experience of model implementation and validation. He is well known for his consulting work with the banking industry and national and supra-national institutions. He is an independent expert advisor to the European Commission, has worked for the IMF and is the author of several books on quantitative finance.
His latest books, co-authored with Dilip Madan, are about the brand new theory of conic finance.
He is also a member of different editorial Boards of international finance journals. Wim is also a founding partner of RiskConcile, a fintech company with roots within the University of Leuven.
He likes arbitrages, politically incorrect statements and making jam.

Andrew Green
Managing Director and Lead GFI Quant
Scotiabank
Andrew Green is a Managing Director and lead XVA Quant at Scotiabank in London. He is the author of XVA: Credit, Funding and Capital Valuation Adjustments which is published by Wiley, co-editor of Landmarks in XVA which is published by Risk Books and co-author of a number of technical articles on XVA in recent years.

Luca Capriotti
Managing Director, Global Head Quantitative Strategies, Credit
Credit Suisse
Luca works in the Quantitative Analysis and Technology (QAT) department in New York where he is the Global Head of Quantitative Strategies Credit, and he is responsible for both front office (pricing models, and eTrading) and capital models (including Var/IRC/FRTB SA, IMA and DRC) covering a variety of businesses including Global Credit Products, Structured Credit and Financing, Structured Notes, Corporate Bank, Commodities, Life Finance, and Treasury. He is also responsible globally for Liquidity Modelling and IRRBB.
Previous to this role, he was the global head of Quantitative Strategies for Credit and Structured Notes; he was the EMEA head and the US head of Quantitative Strategies Global Credit Products; he worked in Commodities in New York and London, and he was part of the cross-asset modeling R&D group of QS in the London office.
Luca is also visiting professor at the Department of Mathematics at University College London, Adjunct Professor at NYU, Tandon School of Engineering, and Adjunct Professor at Columbia University, at the Department of Industrial Engineering and Operations Research. His current research interests are in Credit Models, Computational Finance, and Machine Learning, with a focus on efficient numerical techniques for Derivatives Pricing and Risk Management, and applications of Adjoint Algorithmic Differentiation (AAD), which he has helped introduce to Finance and Physics, and for which he holds a US Patent. Luca has published over 70 scientific papers, with the top 3 papers collecting to date over 950 citations (h factor 25, i10 factor 46).
Prior to working in Finance, Luca was a researcher at the Kavli Institute for Theoretical Physics, Santa Barbara, California, working in High-Temperature Superconductivity and Quantum Monte Carlo methods for Condensed Matter systems. He has been awarded the Director's fellowship at Los Alamos National Laboratory, and the Wigner Fellowship at Oak Ridge National Laboratory.
Luca holds an M.S. cum laude in Physics from the University of Florence, and an M.Phil. and a Ph.D. cum laude in Condensed Matter Theory, from the International School for Advanced Studies, Trieste.
Specialties: Quantitative Analysis, Risk Management, Risk Measurement, Pricing and Hedging of Structured Products, Counterparty Credit Risk Management, Bank's own Credit Risk Management, Numerical Algorithms for Financial Engineering, Monte Carlo and Adjoint Methods, Teaching, and Training.

Petter Kolm
Clinical professor & director of the mathematics in finance
Courant Institute of Mathematical Sciences, New York University
Petter Kolm is the Director of the Mathematics in Finance Master’s Program and Clinical Professor at the Courant Institute of Mathematical Sciences, New York University and Partner at CorePoint-Partners.com. Previously, Petter worked in the Quantitative Strategies Group at Goldman Sachs Asset Management. Petter has coauthored four books: Financial Modeling of the Equity Market: From CAPM to Cointegration (Wiley, 2006), Trends in Quantitative Finance (CFA Research Institute, 2006), Robust Portfolio Management and Optimization (Wiley, 2007), and Quantitative Equity Investing: Techniques and Strategies (Wiley, 2010). He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich.
Petter is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Financial Data Science (JFDS), Journal of Investment Strategies (JoIS), and Journal of Portfolio Management (JPM). He is an Advisory Board Member of Alternative Data Group (AltDG), AISignals and Operations in Trading (Aisot), Betterment (one of the largest robo-advisors) and Volatility and Risk Institute at NYU Stern (VRI). Petter is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and Scientific Advisory Board Member of Artificial Intelligence Finance Institute (AIFI).
As a consultant and expert witness, Petter provides services in areas including alternative data, data science, econometrics, forecasting models, high-frequency trading, machine learning, portfolio optimization with transaction costs and taxes, quantitative and systematic trading, risk management, robo-advisory, smart beta strategies, tax-aware investing, and transaction costs.

Katia Babbar
Co-Founder
Immersive Finance
Katia Babbar is a Financial Markets executive with a career spanning 20+ years. She is the Co-Founder of Immersive Finance, a FinTech offering institutional grade risk management and alpha generation analytics for Digital Assets. Previously, Katia has held various senior positions in the City, from Head of FX Quant Research to MD of an e-FX Algo Trading business having worked at UBS, Citi and Lloyds Banking Group. Katia has been a Visiting Lecturer at the University of Oxford since 2018, where she teaches 'Statistics and Financial Data Analysis' and `Decentralized Finance' for the Mathematics and Computational Finance MSc. She holds a BSc in Mathematics from University College London and a PhD in Stochastic Analysis applied to finance from Imperial College.

Sergio Gago
Managing Director and Head of AI and ML
Moody’s Analytics
Sergio Gago is the Managing Director of Quantum Computing at Moody's Analytics and has more than 20 years of experience as an entrepreneur, CTO and general manager in startups, scaleups and corporations.
Prior to leading the Quantum Computing effort he led the Media Solutions operating unit for Moody’s that features the NewsEdge suite of real-time news-based solutions. He led advances in artificial intelligence and machine learning and applied these developments to news and other media content for companies seeking timely, highly relevant information to fuel decision making as news breaks. With previous experience at Rakuten, Zinio, VCG, Tangelo and Ares Development, Sergio brings more than two decades of executive management and technology experience leading highly technical organizations to drive digital transformation. He holds an MBA, Telecommunications Engineering and Quantum Computing & Information graduate degrees. He was also nominated "40 under 40" in data in 2021 by CDO. Sergio is also the Director at the Big Data and AI Master Degree at BTS / University of Barcelona and an Angel Investor in early stage startups.

Johannes Lotz
Senior Software Engineer and AD Lead
Numerical Algorithms Group
Johannes is the technical lead in the Automatic Differentiation (AD) product team at NAG since January 2021. After his PhD at the RWTH Aachen University on "Hybrid Approaches to Adjoint Code Generation using dco/c++", he continued as a postdoctoral researcher in the broad field of AD. As the main developer of the software package dco/c++, Johannes has been working closely with clients from different areas (e.g., computational finance), both in industry and academia. Over more than the last 10 years, he successfully integrated and helped integrate AD solutions into large-scale numerical codes of various shapes and complexity. His main focus is on AD of C++, CUDA, and Fortran codes for CPU and GPU architectures.

Maxime Bergeron
Director of R&D
Riskfuel
Maxime conducts cutting edge research in applied machine learning and the topology of high dimensional data. Prior to joining Riskfuel, Maxime was a faculty member in the Department of Mathematics at the University of Chicago where his research program focused on understanding the shape of high dimensional parameter spaces. He has a PhD in Mathematics from the University of British Columbia and a BSc/MSc in Mathematics from McGill University.
Erik Vynckier
Board Member & Chair of the Investment Committee
Foresters Friendly Society
Erik Vynckier is board member of Foresters Friendly Society and chair of the Investment Committee, following a career in investment banking, insurance, asset management and the petrochemical industry. He has been Chief Investment Officer and Chief Executive Officer and frequently consults in investment management, quantitative risk management and derivatives.
He co-founded EU initiatives on high performance computing and big data in finance and co-authored “High-Performance Computing in Finance” and “Tercentenary Essays on the Philosophy and Science of Leibniz”. Erik graduated as MBA at London Business School and as chemical engineer at Universiteit Gent.

Blanka Horvath
Associate Professor in Mathematical and Computational Finance
University of Oxford and Researcher
Blanka Horvath is a Lecturer in Financial Mathematics at King’s College London as well as a Honorary Lecturer at Imperial College London and a researcher at The Alan Turing Institute, where she is co-lead of the Machine Learning in Finance theme. Blanka holds a PhD in Financial Mathematics from ETH Zurich, a postgraduate Diplom in pure Mathematics from the University of Bonn and an MSc in Economics from the University of Hong Kong. In her latest research she focusses on non-Markovian models of nancial markets such as Rough Volatility models as well as modern DNN- based market generators. Prior to her position at King’s College, Blanka worked at JP Morgan on the re nements of the Deep Hedging programme and the development of generative market simulation models. Her work on DNN-based calibration of Rough Volatility models was awarded the Rising Star Award 2020 of Risk magazine.

Dmitri Goloubentsev
Head of Automatic Adjoint Differentiation
Matlogica
Dmitri has been a quant in Canadian and British banks for over 17 years, delivering multiple projects in Interest Rates, XVA, VaR areas and developed his own scripting language. In 2018, he realised that the popular tools for High Performance Computing in finance are not good enough: as a quant, he wanted an intuitive object-oriented approach that will extract maximum value from the CPU. Through this personal pain, Dmitri decided to change that and quit his last employer to build better tools for HPC - the one he would enjoy using

Ioana Boier
Senior Principal Solutions Architect, Applied Researcher – Financial Services
NVIDIA
Ioana Boier is a senior principal applied researcher and solutions architect at Nvidia. Her background is in Quantitative Finance and Computer Science. Prior to joining Nvidia, she built an extensive people and thought leadership track record at Alphadyne, Citadel LLC, BNP Paribas, and IBM T.J. Watson Research. She has a Ph.D. in Computer Science from Purdue University. She is the author of over 30 peer-reviewed publications, 15 patents, and the winner of several awards for applied research delivered into products used by clients worldwide.

Robert Jarrow
Ronald P. and Susan E. Lynch Professor of Investment Management
Cornell’s SC Johnson College of Business
Robert Jarrow is the Ronald P. and Susan E. Lynch Professor of Investment Management at Cornell’s SC Johnson College of Business. He is a co-creator of the Heath-Jarrow-Morton (HJM) model, the reduced form credit risk model, and the forward price martingale measure. These are the standard models used for pricing and hedging derivatives in major financial institutions. He was the first to distinguish forward/futures prices and to study market manipulation using arbitrage-pricing theory. He has written seven textbooks, including the first on the Black Scholes Merton (BSM) and Heath Jarrow Morton (HJM) models, and has over 200 academic journal
publications.
Jarrow is on the advisory board of numerous academic journals including the Frontiers of Mathematical Finance. His research has won many awards, including the Graham and Dodd Scrolls Award 2001, the CBOE Pomerance Prize 1982, the Ross Best Paper Award 2008, and the Bernstein Fabozzi/Jacobs Levy Award 2009. In 1997, he was named IAFE Financial Engineer of the Year in recognition of his research accomplishments. He is currently an IAFE senior fellow. He is in the Fixed Income Analysts Society Hall of Fame, Risk Magazine’s 50 member Hall of Fame, and listed in the Who’s Who of Economics. He received Risk Magazine’s Lifetime Achievement Award in 2009. He also serves on various industry advisory boards.
Donald R. van Deventer
Managing Director and co-chair of the Center for Applied Quantitative Finance in the Risk Research and Quantitative Solutions division
SAS Institute Inc
Donald R. van Deventer is Managing Director and co-chair of the Center for Applied Quantitative Finance in the Risk Research and Quantitative Solutions division of SAS Institute Inc. Prior to the SAS acquisition of Kamakura Corporation in June, 2022, Dr. van Deventer was Chairman and Chief Executive Office since founding the company in April, 1990. He is the author of Advanced Financial Risk Management and three other risk management books.
Dr. van Deventer was senior vice president in the Tokyo investment banking department of Lehman Brothers from 1987 to 1990. From 1982 to 1987, Dr. van Deventer headed the funding department for First Interstate Bancorp in Los Angeles. Dr. van Deventer was a Vice President in the risk management department of Security Pacific National Bank from 1977 to 1982.
Dr. van Deventer holds a Ph.D. in Business Economics from Harvard University. Dr. van Deventer also holds a degree in mathematics and economics from Occidental College, where he graduated second in his class, summa cum laude, and Phi Beta Kappa
Zacharia Issa
PhD Candidate
King’s College London
Zacharia Issa is currently a PhD student at King's College London and a quantitative researcher at Kaiju Capital Management. His research interests include on- and offline market regime detection, kernel methods and two-sample testing on path space, and market generation.

Claudio Senatore
Actuary, Global Solution Leader for Dynamic Actuarial Modeling
SAS
Claudio is a distinguished actuary who has been serving as the Insurance Solution Leader within the Risk Quantitative Solution team at SAS since September 2021. As a dedicated member of the Italian Actuarial Association, he actively collaborates with both the International and European Actuarial Associations especially in the Data Analytics and AI areas. With a diverse background in consultancy, direct insurance, and reinsurance, Claudio's expertise spans multiple domains, including Insurance Data Analytics, Property & Casualty Ratemaking, as well as Explainable and Ethical Artificial Intelligence.

Daniel Schobel
Executive Director, Insurance & Asset Management Solutions
Numerix
Daniel Schobel is an actuary in Numerix 's Client Solutions Group, where he collaborates with clients to create Economic Scenario Generators that meet regulatory requirements and support effective risk management. Drawing on his extensive actuarial knowledge and proficiency with advanced analytics tools, Daniel helps clients optimize their economic scenarios and develop strategies to mitigate potential financial risks.
Before joining Numerix, Daniel spent five years at New York Life in roles related to valuation, annuity pricing, and scenario generation. During this time, he was responsible for calibrating and generating market-consistent and real-world scenarios for purposes such as economic capital, stochastic product pricing, VA guarantee valuation, and surplus-at-risk. Daniel's broad expertise in these areas has made him an invaluable asset to both his current and former employers, and he is widely respected throughout the actuarial community for his skill and knowledge.

Stan Roberts
Consultant
Willis Towers Watson
Stan Roberts, FSA, EA, MAAA
Stan has over 20 years of actuarial experience with Willis Towers Watson. In addition to his expertise in Pension Risk Transfer (PRT) solutions for life insurance companies, he has assisted life insurers in navigating and implementing the LDTI accounting standards as well as providing clients a variety of solutions on actuarial topics.
Education and Credentials
Stan earned a B.S. in mathematics from Evangel University. He is a Fellow of the Society of Actuaries, an Enrolled Actuary under ERISA, and a Member of the American Academy of Actuaries.

Oana Avramescu
Global Solution Leader for Dynamic Actuarial Modeling
SAS
As a risk domain expert, Oana advises financial institutions on how to best improve their risk measurements and regulatory compliance.
Since joining SAS in August 2012, Oana’s focus was helping customers to tackle their biggest challenges and gain more business within the Risk Management area. She was acting as an SME on Solvency II and IFRS17 programs for various major insurance companies.
Right now, she is leading the Insurance Capital Management Value Proposition (Solvency II, ICS) and Actuarial Transformation Value Proposition (Pricing, Reserving).
Oana holds an MBA diploma and has more than 15 years of experience in various roles within the insurance, banking, and software industry, working for big financial institutions, as well as with recognized regulatory software vendors.
STORM50 2023 - Agenda
09:30 – 09:35
Welcome Message
09:30 - 09:35
Mark Feeley, Global Brand Director/Research Director, Chartis Research
09:35 – 09:40
Chartis Research presentation: The state of hardware acceleration
09:35 - 09:40
This brief overview suggests methods institutions can use to gain computational efficiencies and covers the current landscape of hardware acceleration, multilingual programming environments and future trends.
Sidhartha Dash, Chief Researcher, Chartis Research
09:40 – 10:00
Presentation: ‘15 Years of AAD’ ‒ how to use upside-down derivatives to better hedge financial risks, crack some of the puzzles of condensed matter and much more
09:40 - 10:00
Known in its modern form since at least the 1960s, adjoint algorithmic differentiation (AAD) is a computational technique that was ‘rediscovered’ in finance a decade or so ago and now has become mainstream. Learn what makes AAD an important innovation in financial risk management and how the same ideas can be applied in condensed matter physics. It can be used in contexts that require a large number of derivatives to be computed accurately and efficiently.
Luca Capriotti, Managing Director and Global Head of Quantitative Strategies ‒ Credit, Credit Suisse
10:00 – 10:20
Presentation: From research to industry: automatic differentiation in C++
00:01 - 00:02
The broad field of automatic differentiation (AD) has been researched for many decades and has experienced important breakthroughs over time. Constant advancements in both theory and tools, in combination with evolving programming languages, have led to its success in industry. This session will explore some of the most interesting and crucial breakthroughs, as well as the current state of AD software at NAG.
Johannes Lotz, Senior Software Engineer and AD Lead, Numerical Algorithms Group
10:20 – 10:25
Chartis Research presentation: Clash of the cultures – the role of structure in quantitative modeling
00:01 - 00:02
Technology trends in different financial services industry segments can significantly influence the way technology evolves in other segments within financial services. Ideas, methodologies and tools inevitably pass between risk areas and business lines; however, the convergence of different modeling styles is not always straightforward. This brief presentation outlines the role of structure in neural networks versus more conventional modeling approaches.
Maryam Akram, Senior Research Specialist, Chartis Research
10:25 – 10:45
Presentation: Large language models with applications to quant finance
00:01 - 00:02
This session will focus on the capabilities and challenges of large language models (LLMs) and how they can be applied in quant finance.
Ioana Boier, Senior Principal Solutions Architect, Applied Researcher – Financial Services, NVIDIA
10:45 – 11:05
Presentation: Functional interpolation and neural networks
10:45 - 11:05
Neural networks are function approximators that can define complex nonlinear functions. This session will focus on the use of neural networks to approximate functions and contexts where this can be applied.
Maxime Bergeron, Director of R&D, Riskfuel
11:05 – 11:10
Chartis Research presentation: Two sides of the computational coin – neural networks as computationally intensive and computationally efficient algorithms
00:01 - 00:02
As a process of brute force computation, deep learning neural networks have gained a reputation for being computationally inefficient and energy intensive. High-profile large language models (LLMs), which have dominated media headlines, are inordinately expensive to train and deploy. However, neural networks are being used in finance for data compression and as alternatives to costly and inefficient simulations, such as ‘bump and reprice’. This brief overview presents some of the techniques being used to make deep learning more energy efficient.
Maryam Akram, Senior Research Specialist, Chartis Research
11:10 – 11:30
Presentation: Real-world machine learning operations (MLOps) in asset management
00:01 - 00:02
This session explores the place for MLOps solutions in finance and the adoption challenges the industry has faced so far. The massive growth the MLOps market is experiencing is driven by increased digitalization and deep learning models, as well as advances in ML research and tooling. ML solutions offer a range of functions, including data/feature engineering, the collection of metadata, experiment tracking and access to advanced custom deployment options, etc. These functions are not at all new to financial services, yet the adoption of MLOps in this sector has been slower compared to other industries. Learn more about how MLOps can support data-driven modeling processes in finance.
Petter Kolm, Clinical Professor of Mathematics, Courant Institute of Mathematical Sciences, NY University
11:30 – 11:45
Presentation: Beyond Cost Savings: Leveraging Automatic Adjoint Differentiation and Cloud Computing for Real-Time Risk Assessment in Banking
00:01 - 00:02
While cost savings may be a motivating factor, many banks continue to use cloud services primarily for batch processing, missing out on the true potential of cloud computing. By combining automatic adjoint differentiation (AAD) with cloud computing, banks can achieve real-time risk assessment, facilitating an ‘always hot’ service to compute the entire portfolio risk. In this session, attendees will learn how to maximize the potential of cloud computing and AAD to achieve more efficient and effective risk management in banking.
Dmitri Goloubentsev, CTO | Head of Automatic Adjoint Differentiation, Matlogica
11:45 – 12:05
Fireside chat: State of play with quantum computing
11:45 - 12:05
This conversation will explore when quantum computing will be ready for general-purpose computing and when it will be ready for use in financial services. The discussion will include the ‘risks and costs’ and the ‘risks and rewards’ for putting quant computing in place, as well as the benefits of quantum computing.
Andrew Green, Managing Director and Lead GFI Quant, Scotiabank in conversation with Sergio Gago, Managing Director and Head of AI and ML, Moody’s Analytics
12:05 – 12:07
Closing remarks
12:05 - 12:07
12:07 – 12:22
Announcement of QuantTech50 winners
12:07 - 12:25
12:22 – 12:23
End of day 1
12:25 - 12:26
09:30 – 09:35
Welcome Message
09:30 - 09:35
Mark Feeley, Global Brand Director/Research Director, Chartis Research
09:35 – 09:50
Presentation: Impact of long-duration targeted improvements (LDTI) on insurance models
09:35 - 09:50
The session addresses how LDTI is changing product design and the transformation of the insurance product landscape.
Stan Roberts, Consultant, Willis Towers Watson
09:50 – 10:05
Fireside chat: Developments and advances in market consistent scenario generation techniques
09:50 - 10:05
Sidhartha Dash, Chief Researcher, Chartis Research
in conversation with
Daniel Schobel, Executive Director, Insurance & Asset Management Solutions, Numerix
10:05 – 10:20
Presentation: Beat your competitors in P&C with distribution-free approach and pricing optimization
10:05 - 10:20
The session will describe how the distribution-free technic can provide more accurate insights in the pricing methodology for P&C. The combination of this technic and the optimization logics can allow the insurer to increase the competitiveness of their offerings to increase profitability and market share.
Oana Avramescu, Global Solution Leader for Dynamic Actuarial Modeling, SAS
Claudio Senatore, Actuary, Global Solution Leader for Dynamic Actuarial Modeling, SAS
10:20 – 10:25
Chartis Research presentation: Opening up actuarial modeling ‒ reengineering actuarial platforms with new data and computational tools
10:20 - 10:40
The traditional field of actuarial modeling is evolving as firms are being confronted with new analytics demands and methodologies. New product strategies, market dependencies, increased data availability and capital and risk demands are pushing insurers to progressively integrate standardized stress testing frameworks and banking ALM practices. Learn more about how platforms are developing to support diverse computational and data requirements.
Sidhartha Dash, Chief Researcher, Chartis Research
10:25 – 10:45
Presentation: Economic scenario generation ‒ challenges and innovations in market implied frameworks and neural network applications
10:25 - 10:45
The presenters will evaluate the key challenges in economic scenario generation tools and market implied frameworks. Learn more about the use of neural networks/ML to accelerate and improve functional approximation.
Blanka Horvath, Associate Professor in Mathematical and Computational Finance, University of Oxford and Researcher
Zacharia Issa, PhD Candidate, King’s College London
10:45 – 11:15
Panel: Cyber and black swan events - modeling specialized risks
10:40 - 11:10
The insurance market has seen an increase in demand for coverage of cyber and special events, such as natural disasters or terrorist attacks. Modeling these risks is a complex process that requires the use of sophisticated mathematical and statistical techniques. The panelists will discuss the changes witnessed by market participants in catastrophe modeling and the latest trends, such as the rise of open source.
Moderator: Maryam Akram, Senior Research Specialist, Chartis Research
Wim Schoutens, Professor, University of Leuven
Erik Vynckier, Board Member & Chair of the Investment Committee, Foresters Friendly Society
11:15 – 11:20
Closing remarks
11:10 - 11:15
11:20 – 11:35
Announcement of the InsuranceAnalytics25 winners
11:15 - 11:30
11:30 – 11:31
End of day 2
11:30 - 11:31
09:40 – 09:45
Welcome Message
09:30 - 09:35
Mark Feeley, Global Brand Director/Research Director, Chartis Research
09:45 – 10:05
Conversation: Industrializing financial advice ‒ challenges, risks and trade-offs
09:45 - 10:05
This conversation will explore how advisory services can be industrialized, including industrial-scale financial advice and planning challenges and trade-offs. Learn more about robo advisers and financial planning platforms, their challenges and risks, and how optimal they are.
Sidhartha Dash, Chief Researcher, Chartis Research in conversation with Petter Kolm, Clinical Professor of Mathematics, Courant Institute of Mathematical Sciences, NY University
10:05 – 10:35
Panel discussion: Pricing and modeling of structured products
10:05 - 10:35
This discussion will focus on the latest trends and the potential pitfalls and risks of investing in structured products in today’s market, and how to navigate the complexities of the market. Learn more about the various pricing and modeling techniques used to value these products, including Monte Carlo simulations, lattice models and closed-form solutions. The speakers will also explore the impact of market volatility, interest rates and credit spreads on the pricing and modeling of structured products.
Moderator: Sidhartha Dash, Chief Researcher, Chartis Research
Fabio Mercurio, Global Head of Quant Analytics, Bloomberg
Katia Babbar, Co-Founder, Immersive Finance
10:35 – 10:55
Presentation: Modeling retail financial assets - a contingent claim approach for demand deposits and credit cards
10:35 - 10:55
This session will discuss the concept of contingent claim theory and how it can be applied to model credit cards. The presenters will also focus on how to formulate and handle embedded options in credit cards, both structural and behavioral, using this approach, with examples and case studies that illustrate the application of these concepts in real-world scenarios.
Donald van Deventer, Managing Director, Risk Research and Quantitative Solutions, SAS
Robert Jarrow, Ronald P. and Susan E. Lynch Professor of Investment Management, Samuel Curtis Johnson Graduate School of Management at Cornell University in Ithaca, NY. and an Advisory Industry Consultant, SAS
10:55 – 11:15
Chartis Research presentation: Democratizing financial advice by leveraging available technology
10:55 - 11:15
Sidhartha Dash, Chief Researcher, Chartis Research
11:15 – 11:20
Closing remarks
11:15 - 11:20
11:20 – 11:35
Announcement of Retail Finance Analytics25 winners
11:20 - 11:35
11:35 – 11:36
End of day 3
11:35 - 11:36
Previous Reports
RiskTech100® 2023
The latest iteration of the most comprehensive independent study of the world’s major players in risk and compliance technology.
ALM Technology Systems
ALM: An analysis of the market and vendor landscape for asset and liability management (ALM) solutions. Includes four RiskTech Quadrants.
xVA Solutions
xVA: This report focuses on the suite of valuation adjustments that have become crucial to derivative valuation, notably CVA, MVA, ‘universal xVA’ and analytical components
STORM50 - 2021
The inaugural STORM50 ranking and analysis, focused on the computational infrastructure and algorithmic efficiency of the vast array of technology tools used across the financial services industry