The aim of this conference is to bring together European academics, young researchers, students and industrial practitioners to discuss the application of Artificial Intelligence in Industry and Finance.

The 1st COST Conference was held on September 15, 2016, the 2nd COST Conference was held on September 7, 2017, the 3rd COST Conference was held on September 6, 2018, and the 4th AI Conference was held on September 5, 2019.

All lectures are open to the public.

• Artificial Intelligence in Finance: Artificial Intelligence and Fintech challenges for the European banking and insurance industry
• Artificial Intelligence in Industry: Artificial Intelligence challenges for European companies from the mechanical and electrical industry, but also life sciences.
• Regulatory Technology in Finance: This session is devoted to the use of modern technology for the automation of regulatory reporting in finance.
• Ethical Questions in Artificial Intelligence: Issues arising in AI applications such as trust, explainability, neutrality, responsibility, moral consequences of algorithmic decisions.

In 2017, 2018, and 2019, we have had around 200 participants, both from Academia and Industry. The latest instalment of the AI conference also saw a large number of international guests and speakers, travelling to Switzerland from destinations such as the UK, Germany, the United States and Bulgaria.

The largest proportion of participants will come from the industry complemented by a significant number of academic researchers. This mirrors our unique approach of connecting the academic world to their respective fields of application, putting new exciting concepts to work in industrial frameworks, where they can open up new opportunities.

A Brief Biography

Igor Halperin is a researcher at Fidelity Investment and a Research Professor of Financial Machine Learning at NYU Tandon School of Engineering. His research focuses on using methods of reinforcement learning, information theory, neuroscience and physics for financial problems such as portfolio optimization, dynamic risk management, and inference of sequential decision-making processes of financial agents. Igor has an extensive industrial experience in statistical and financial modeling, in particular in the areas of option pricing, credit portfolio risk modeling, portfolio optimization, and operational risk modeling. Prior to joining Fidelity and NYU Tandon, Igor was an Executive Director of Quantitative Research at JPMorgan, and before that he worked as a quantitative researcher at Bloomberg LP. Igor has published numerous articles in finance and physics journals, and is a frequent speaker at financial conferences. He has also co-authored the books “Machine Learning in Finance: From Theory to Practice” (Springer 2020) and “Credit Risk Frontiers” (Bloomberg LP, 2012). Igor has a Ph.D. in theoretical high energy physics from Tel Aviv University, and a M.Sc. in nuclear physics from St. Petersburg State Technical University.

Inverse Reinforcement Learning: applications in Finance

In this talk, I will give a brief introduction to Inverse Reinforcement Learning (IRL), and give examples of its potential applications for quantitative finance.

A Brief Biography

Helmut Hauser is a Senior Lecturer (Associate Professor) at the Department of Engineering Mathematics at the University of Bristol. He is a leading researcher  in morphological computation and embodied intelligence. He seeks to understand the underlaying principles of how complex physical properties of biological systems are exploited to facilitate learning and controlling tasks, and how these principles can be employed to design better robots and novel sensor technologies. He has published over 60 papers including in high impact journals like Science Robotics, Nature Machine Intelligence and Scientific Reports. He won multiple awards including various “Best paper” awards and the  “Highly Commended - Industrial Robot Journal award for practical innovation in the field of robotic”.  He is currently leading the highly interdisciplinary Leverhulme Trust project  “Computing with spiders’ webs". He is also the director of the EPSRC Centre of Doctoral Training in Future Autonomous and Robotic Systems and he is leading the UKRI Strategic Task Group on Soft Robotics.

The Body as a Computer – From Computing Octopus Arms to Sensing Spider Webs to Growing Robots

Despite the remarkable success of robotics, biological systems are still outperforming machines in almost any task.  While robots are excellent at moving fast and precisely, they are surprisingly bad in robustness, adaptivity, energy efficiency and behavioral richness. It's speculated that one reason for this superiority of biological solutions is that nature exploits body dynamics for intelligent control,  sensing, and to facilitate any underlying learning problems.

In our field of research, called morphological computation, we try do understand how nature is able to find embodied solutions through the evolutionary process, and how we can transfer this knowledge in better machine designs.

We will present three examples from our lab that show how bio-inspired machines can take advantage of this approach including a silicone-based octopus arm that can compute, a spider-web inspired vibration sensor that can classify signals, and growing robots that can adapt to their environments.

A Brief Biography

Liudmila Zavolokina is an IT consultant at Ergon Informatik and a postdoctoral researcher in Information Systems at the Information Management Research Group at the University of Zurich. She’s also a member of the Blockchain Center of the University of Zurich. Her research includes blockchain platforms and their impact on trust relationships, blockchain business models, and digital innovation in the financial area (FinTech). During her PhD, Liudmila co-initiated the Cardossier project – the Swiss blockchain ecosystem for car’s history - and led its research team. Today, Liudmila helps businesses leverage potential of blockchain technology and develop innovative solutions.

Blockchain for business

Blockchain has been around for a long time but, as the hype dies down, this security-based technology continues to challenge the business status quo across many organisations and industries. So, what does it look like behind the scenes of the technology everyone is talking about? In this talk, I show an approach that businesses may use to assess the usefulness of blockchain technology , and discuss potentials and benefits of blockchain technology for value creation.

A Brief Biography

Jens Frühling is a Principal Director from Accenture, he joined Accenture in January 2017, having previously had leading positions in the areas of analytical Customer Relationship Management, Big / Smart Data and Digital Marketing in Banking. He benefits from 20 years of experience in management of complex BI and campaign automation projects.

Today he is responsible for GoTo Market of artificial intelligence (AI) Use Cases with the goal to establish Enterprise AI in all industries. Before that he built the artificial intelligence (AI) delivery capability within Accenture Applied Intelligence.

Jens holds a degree in Geography with specialization in geo-based marketing from Johann Wolfgang Goethe University, Frankfurt / Germany.

In the past twenty years he is Speaker at home and abroad and author of publications on analytical CRM and in recent times for Artificial Intelligence.

Bot and claims handling automation + automated damage assessment with AI

Global players like Ping An Insurance / China are leading the way: Consistent use of AI to reduce costs and increase customer satisfaction at the same time!

The vision: Capturing and checking the coverage of simple claims in a single customer contact - if possible automated until payment. Automatic real-time recognition of loss event, object, location, time, etc. from the description of the loss event. Collection of all relevant information for the cover check - if desired also with AI supported document check.

The result: Claims experts are relieved and can concentrate on complex cases, while increased customer satisfaction through "immediate decision" or already as complete as possible data collection in the first contact. 

A Brief Biography

Angus Moir: Senior Manager, Data Collection Transformation team

Angus leads the data collection transformation team at the Bank of England: responsible for delivering a transformation of the way the Bank collects data from the UK financial sector. Previously, he led the Bank’s engagement in the Digital Regulatory Reporting initiative and played a key role in delivering a new supervisory dataset from the UK’s CCPs. Prior to dedicating his life to data and data collection, he held a number of roles at the Bank and in the private sector, primarily with a focus on risk analysis.

Originally an economist by training, his current primary interest, apart from improving data collection, is how to write rules and regulations in a “digital first” manner

Digital Regulatory Reporting, automating the reporting process

From 2016 to 2019, the Bank of England, FCA and participants from industry participated in a series of events under the banner of Digital Regulatory Reporting (DRR). At the events the UK financial regulators worked with industry to explore how the regulatory reporting process could be automated. DRR culminated with two six months pilots that developed a number of prototypes showcasing how automation may work in practice.

A Brief Biography

Jefferson Braswell has been successfully providing leading-edge business solutions for the financial sector for over 30 years. Tahoe Blue provides technology consulting, identification management services, and the development of enterprise risk models and data standards for the financial industry. 

As one of its founding Directors, he has recently completed a 6-year term on the Board of the Global LEI Foundation (GLEIF), where he chaired the Technology, Operations and Standards Committee.  He is also the Chair of the Board of Governors of the ACTUS Financial Research Foundation, and actively participates in several other ongoing financial data standards initiatives, including those of CPMI-IOSCO, ISO 20022 and ISO TC68 (Financial Services) and ISO TC307 (Blockchain) .

As co-founder and President of Berkeley-based Risk Management Technologies (RMT), Braswell designed and led the successful implementation of advanced, firm-wide risk management solutions integrated with enterprise-wide data management tools on high-performance computing platforms for many of the world's largest financial institutions, including Wells Fargo, Credit Suisse, Chase, PNC, Sumitomo Mitsui Banking Corporation, Mellon, Abbey National, Wachovia, Union Bank and ANZ.

Opportunities for the Innovative Application of Analytics in Financial Risk Management and Reporting

The availability of transparent -- and mathematically rigorous -- open-source standards for financial contract data and corresponding algorithms (such as ACTUS) has given rise to opportunities to leverage these standards as components in the application of innovative financial risk analytics in risk management applications.  The opportunities to incorporate innovative analytics with a foundational platform that can generate cash flow projections from actual balance sheet contracts could be grouped, for convenience, into three basic stages: the input preparation stage, the cash-flow generation stage, and the output post-processing stage.  The interaction of external risk models with internal contractual cash-flow algorithms in the generation stage is complex, and involves many factors. A careful delineation of the dynamics of such interactions is required in order to achieve the transparency, and explainable defensibility, of risk models. On the other hand, a discussion of opportunities to apply innovative analytical techniques in the input preparation stage and the output post-processing stage is more tractable, and this presentation will focus more on some of these opportunities.

Panelists:

• PJ Di Giammarino, JWG, London
• Francis Gross, European Central Bank, Frankfurt
• The Honorable Allan I. Mendelowitz, ACTUS Financial Research Foundation, Washington

Moderator: Prof. Dr. Wolfgang Breymann, ZHAW

PJ Di Giammarino is an independent RegTech authority with a global network of senior bankers, regulators, and technologists which he brings together to enable compliance via adoption of new technology resulting in better, faster, cheaper and safer solutions.

Following a career of building systems and top management consulting including McKinsey,  PJ was the COO of Technology at Barclays Capital.

Seeing the RegTech opportunity early, he founded JWG Group in 2006 to provide practitioners a platform for Joint Working Groups. As an independent think-tank JWG leverages its unique position with regulators, firms and their suppliers to facilitate the right RegTech dialogues and drive global change.

Currently JWG is working with the top players in the industry to deliver on the promise of digital regulatory reporting for global OTC derivatives and defining holistic management obligations for trade surveillance.

Since 2015, JWG has worked with global financial institutions to develop and deploy RegDelta - the gold standard for AI-powered control over regulatory obligations. Today we harness decades of intelligence to source tens of thousands of global regulatory texts and filter the noise to allow rapid risk assessment and effective control.

PJ has been based in Europe for 20 years and London for 15. He is an active member of the International Organisation for Standardization and he also serves as Chairman of the Committee to Establish the RegTech Council.

Francis Gross is Senior Adviser in the Directorate General Statistics of the European Central Bank.

Francis’ main interest lies in developing vision, sustainable conceptual design and strategy for overcoming the dual disruption of rapid globalization and digitization. The focus lies on measurement. The crisis taught us that we need to build measurement tools that will be effective at the scale and speed of finance also in 20-30 years, i.e. global and real time, especially in a crisis. The immediate aim is to design and drive the implementation of concrete, feasible measures with transformational power.

The underlying strategic credo is that to achieve that goal we must make the world more measurable. A simple first step is to build global data infrastructures that make global standards real for all. For that, authorities and the private sector must work together, globally, separating areas for cooperation from those for competition.

Francis’ immediate focus lies on the “real world - data world” interface, beginning with object identification, specifically legal entities. He serves on the Regulatory Oversight Committee of the G20-backed Global Legal Entity Identifier System (GLEIS) and has been instrumental from the start in the emergence and development of the GLEIS.

Prior to joining the ECB in 2001, Francis spent fifteen years in the automotive industry, eight of which at Mercedes, working mainly on globalisation, strategic alliances and business development.

He holds an engineering degree from École Centrale des Arts et Manufactures, Paris, and an MBA from Henley Management College, UK

In his free time, Francis coaches athletes for javelin throwing, including the current decathlon world champion.

The Honorable Allan I. Mendelowitz is President of the ACTUS Financial Research Foundation.  The ACTUS Foundation is a not-for-profit corporation that is dedicated to creating and promoting an open-source fee-free algorithmic financial contract standard that enables current and forward-looking analysis.  Over the course of his career he has held a number of senior executive government assignments.  In his last position he served as Chairman of the Federal Housing Finance Board, the prudential regulator of the Federal Home Loan Bank system.  He has published articles in scholarly journals and popular publications, lectured widely in the United States and abroad on economic and financial topics, and testified as an expert witness before the U.S. Congress more than 145 times.  His education includes economics degrees from Columbia University (A.B.) and Northwestern University (Ph.D.).

Prof. Dr. Wolfgang Breymann is head of the group Finance, Risk Management and Econometrics at Zurich University of Applied Sciences, Institute of Data Analysis and Process Design, which he shaped by developing the research activities in financial markets and risk. After a career in theoretical physics, he turned to finance in 1996 as one of the early contributors to the then burgeoning field of Econophysics and joined ZHAW in 2004. He is one of the originators of project ACTUS for standardizing financial contract modelling and member of the board of directors of the ACTUS Financial Research Foundation as well as founding member of Ariadne Software AG and Ariadne Business Analytics AG. His current R&D interests are focused on the automation of risk assessment to improve the transparency and resilience of the financial system.

Wolfgang Breymann has managed large national and international projects. He authored or co-authored over 40 refereed papers and co-authored the book “Unified Financial Analysis”. He has given many invited talks at universities and conferences all over the world.

A Brief Biography

Karin Tien received her degree in Business Law in 2015 (University of Innsbruck, Tyrol, Austria) after she completed her education at the HTL Dornbirn in Chemical Engineering with focus on Textile Chemistry. Beside her diploma studies she worked from 2010 to 2015 in an IT-start-up, based in Vorarlberg, pioneering in the field of development of Mobile Apps which is why her master's degree thesis deals with legal requirements of  “Bring your own device and mobile device management” (employee privacy issues).

After her judicial clerkship in the district of the Higher Regional Court Vienna she started as an associate in international law firms ingrained in the Technology, Media and Communications sectors. Her practice focused on providing legal advice on all matters relating to data protection law. Before founding a consultancy business, she passed the Austrian Bar Exam and worked at the Austrian Financial Market Authority (FMA) in areas of Crisis Management and Recovery Planning.

Over time, she mainly specialized in the field of data protection, both from the legal and from the organizational as well as from the management perspective. She performed implementations, assisted clients as data protection officer and external auditor. Furthermore, she creates Corporate Digital Responsibility (CDR) programs and ethical guidelines dealing with risks and privacy conflicts (trust vs. convenience of digital).

She authored or co-authored several papers about data protection as well as CDR and has given many invited talks at universities and conferences. Additionally, she supervises Master thesis (FHW Vienna) and professionally supports the Data Protection Think Tank at the Institute of Internal Auditors (IIA) in Austria.

Implementing CDR Strategies – Ways of Managing Privacy Risk from a Law and Ethical perspective

In many cases, prior to considering which ethics regulations AI Programs should comply with, it is often a beneficial approach to review the organization’s existing ethical standards. In various departments (eg HR, Sales, Marketing, R&D, Customer Service) different purposes for data use are given priority. This often leads to the fact that internal regulations based on a Corporate Digital Responsibility (CDR) program may help to harmonize the vision of values and to unite the actions of data processing.

For customers and conscious consumers, the existence of digital ethics programs is a sign of quality, as well as the basis of a long-term, trustful customer relationship. The experience of the past has shown that if there is no trust in the way an organization is processing data, the product or service might be rejected by the consumers and end users.

Today some organizations have already started to establish CDR programs. They have chosen different methods and strategies to address CDR and ethical issues in their development of software/products and data usage. This course of action is primarily driven by Corporate Social Responsibility (CSR) and Internal Audit Departments as they recognize risks (loss of reputation and customers, data breaches, non-acceptance of innovations) which could arise from blind spots.

This presentation will focus on different implementations of CDR strategies and gives a short overview about the key challenges organizations are facing in this context.

A Brief Biography

Corinna Hertweck is a PhD candidate at the Zurich University of Applied Sciences and the University of Zurich. Prior to starting the joint PhD program in 2020, she worked as a software engineer and graduated from the University of Helsinki with a master's degree in computer science. In her research, she focuses on the intersection of algorithms and social sciences. In particular, she is interested in questions of fairness and ethics arising when applying machine learning in the fields of education, recruitment, migration and criminal justice.

Tim Räz is a postdoctoral researcher in philosophy. He is working on the project “Socially acceptable AI and fairness trade-offs in predictive analytics in recruitment and education/training” (part of NRP 77 “Digital Transformation”). He is based at the Institute of Biomedical Ethics and History of Science (IBME), University of Zürich. His background is in philosophy (MSc., University of Bern, 2006), philosophy of science (PhD, University of Lausanne, 2013) and mathematics (MSc., University of Bern, 2019). His research interests include philosophy of science, philosophy of AI, and in particular philosophical issues of machine learning, including interpretability, explainability, and algorithmic fairness.

Algorithmic Decision Making and Social Justice: On the morals of Predictive Modeling

Algorithmic decision making based on predictive modeling is an intrinsic part of many AI solutions in finance and other services. The underlying algorithms are typically developed for optimizing business goals such as profit maximization or risk management, but the derived decisions have a concrete impact on the lives of humans. Basic societal values such as equality, freedom, or justice are on stake, and often threatened, as it turns out in the implemented practice. People are treated differently, as intended and needed for the business case. However, many recent examples show that algorithms may systematically discriminate against specific social groups. As a consequence, involved companies often face major reputation problems.

In our talk, we show why typical prediction-based decision systems nearly automatically generate issues of social fairness. We show how fairness of a decision system can be measured and managed, in order to avoid or minimize these issues, and we present an overview on fairness measures that have been established in practice. Finally, we comment on the ethical and moral significance of choosing to implement a specific form of fairness.