IEEE Conferences

Symposium Chair

Kumar Bhaskaran, IBM TJ Watson Research Center (bha@us.ibm.com)

Program Committee

Winnie Cheng, Io-Tahoe and Forbes Technology Council Member (winnie.cheng@io-tahoe.com)
Emily Liu, Stevens Institute of Technology (rong.liu@stevens.edu)
Jorge Sanz, National University of Singapore (jorges@nus.edu.sg)
Chanaka Edirisinghe, RPI (edirin@rpi.edu)

Schedule - July 10

10:15 - 11:30: Morning Plenary Keynote - Navigating Technology Acceleration: Ensuring Safe Passage to AI-Powered Digital Business
Dr. Kathryn Guarini, VP, Industry Research, IBM
Location: Aula Magna (Universita' degli Studi di Milano)

Technology advancements are accelerating, creating new opportunities for industry transformation and business growth. Artificial intelligence (AI) and blockchain have emerged as key disruptors. This talk will describe the rapid progress of these advanced technologies, highlight the unique requirements for enterprise deployment, and showcase compelling use cases across different industries.

11:30 - 12:45: Plenary Panel - Future of Financial Services
Panelists include Christophe Spoerry, Ricardo Collado Soto, Michael Goul, Natalie Gill, Jorge Sanz, Rong N. Chang, and Emily Liu
Location: Aula Magna (Universita' degli Studi di Milano)

12:45 - 14:00: Lunch and Networking

14:00 - 15:15: Afternoon Keynote - FinTech: European Union Perspective
Dr. Mirjana Pejic' Bach, Full Professor, Faculty of Economics and Business, Zagreb University
Location: Aula Magna (Universita' degli Studi di Milano)



Emerging Financial Technologies (FinTech) are making financial services more accessible through new products and services in the areas of trading & investing, lending, payment, personal finance, and currency exchange and remittances. Utilization of new technologies, such as blockchain, overall improves the efficiency of the financial systems and infrastructure. The European Commission has adopted an action plan for the financial sector to make it more competitive by benefiting from these developments while keeping it safe for all stakeholders. This talk will describe some of the current EU FinTech projects and work of expert groups, with the goal to highlight the R&D opportunities and challenges in the FinTech area.

15:15 - 15:45: Networking Break

15:45 - 17:20: Financial Services Research Forum
Paper presentations & discussion
With Ricardo Collado Soto, Christophe Spoerry, Michael Goul, and Kumar Bhaskaran
Location: Aula Magna (Universita' degli Studi di Milano)

17:20 - 17:30: Wrap up and Passing the Baton to Beijing Organizers
Yanmei Zhang, Central University of Finance & Economics, Beijing
Location: Aula Magna (Universita' degli Studi di Milano)

17:30 - 19:00: PhD Forum
Location: Sala Napoleonica (Parallel & Main) (Universita' degli Studi di Milano)

Description & Scope (from the 2019 Future of Financial Services Symposium Call for Papers)

The financial services industry (banking, insurance and financial markets) face mounting pressure to reduce costs, improve customer experience, compete with emerging players and comply with new regulations. At the same time, the industry is seeking and investing in innovations with the potential to transform financial services using technologies like artificial intelligence (AI), blockchain, quantum computing, Internet-of-Things (IoT), cybersecurity, and cloud. These advances are surfacing new capabilities in risk modeling, fraud detection, regulatory compliance, distributed and decentralized trust models, digital customer journeys and data privacy. Financial institutions will be required to embrace these advanced technologies now in order to set a viable course for future growth.

The primary objective of this symposium is to bring academia and industry domain experts together to define the innovation opportunities in the industry inspired by data-driven and socio-technical topics that are essential to successfully lead the digital future of financial services. This workshop will focus on exchange of minds to better understand existing challenges in the industry and potential R&D advances that can bring transformative changes to the financial industry in coming years.

The workshop will seek wide participation from academia and industry to address four research themes:

• Decentralization as a New Model of Trust
  The explosive growth of FinTech, new regulations such as Payment Services Directive 2 (PSD2) that require financial institutions to openly collaborate, and the push to seek top-line growth are motivating the exploration of new business models and ecosystems in the finance industry. Ecosystems are evolving. They are becoming ever more decentralized and customer-centric. How can trust be established between customer and financial services in these new ecosystems? Blockchains represent one future of secure, trusted and digital business transactions in decentralized ecosystems that involve multiple parties. Blockchains likely span organization and geographic boundaries, and they usher in new efficiencies in terms of transparency and traceability, lower cost, reduced risk, and faster time-to-value by reducing the business-to-business (B2B) friction that is pervasive in today’s business networks and supply chains which are fraught with manual processing of paper documents. Today’s solutions involve numerous intermediaries with varying degrees of trust, resulting in unacceptable transaction latencies and overall poor customer experiences. This theme will focus on blockchain for finance, and invited submissions will focus on related technologies and business models.
  
  
• AI and the Interconnectedness of Everything
  We are witnessing the emergence of “digital enterprises” with business architectures founded on pervasive interconnectedness with customers, ecosystem partners, and their business networks. The ensuing explosion of data is accelerating the need for and the rise of systems that can understand, reason, and learn from data to augment human decision making at all levels of the enterprise. This is referred to broadly as artificial intelligence (AI) - a suite of mathematical and computer science tools and algorithms for machine learning, engaging naturally with humans through introspection and explanation, and learning from big and small data to address meaningful challenges in industries. This theme will focus on the application of AI to finance in areas such as services computing platforms for accelerated and optimized AI workloads, automation and decision support for financial processes such as financial crimes compliance (including Know-Your-Customer (KYC), and Anti Money Laundering (AML)), regulatory compliance, financial forecasting and credit risk management, and developing digital experiences for customers. This theme will also focus on enterprise capabilities that are required to scale AI in a highly regulated industry such as the finance industry by addressing transparency of models, interpretability of model outcomes, detection and mitigation of bias in data and models, model-risk governance, and emerging risk and liability assessment of AI applications.
  
  
• Secure and Trusted Cloud Services
  The financial services industry is the most targeted and attacked industry with mounting losses due to cybercrimes ranging from direct monetary thefts from bank accounts by phishing and credential-stealing malware, to running malicious code to intercept on-line transactions, to targeting of bank customers by organized crime gangs, to sophisticated injection attacks aided by inadvertent insiders breaching confidential data, and to increasing threats from nation-state actors orchestrating attacks on financial infrastructures. Omnichannel customer engagement, the growing deployment of AI in financial processes, regulatory pressures to move towards open APIs, the transition of workloads to cloud for operational efficiencies, the rise of cryptocurrencies and new modes of payments, and the emergence of new financial ecosystems will further challenge and shape the future state of cybersecurity and the technologies that can address the changing threat landscape. This theme will focus on key areas of interest to the industry such as advances in AI models for security as well as the advances in security necessary to protect AI models, the emergence of Data Trusts that use tokenization and pseudonymization technologies to ensure data privacy while complying with new regulations such as (General Data Protection Regulation (GDPR), and the use of secure service containers that protect against insider threats and malware.
  
  
• Applications of Quantum Computing in Finance.
  The computers we use today, known as classical computers, have enabled amazing things and transformed how we work and live. There are, of course, still problems to solve beyond the capabilities of classical computers. These problems generally involve exponential scaling such as large-scale optimization or simulations of quantum systems such as molecules. Quantum computers are being built to work with classical computers to explore how we might solve these problems. Quantum computers are incredibly powerful machines, built on the principles of quantum mechanics, that take a new approach to processing information. This theme will focus on the potential of near-term quantum computers for financial applications such as risk analysis, portfolio optimization and time-series forecasting and machine learning. This theme addresses the question, “What classes of financial services problems can benefit from quantum speedup and advantage?” Additionally, it is well known that quantum computers have the potential to factor large numbers much faster (e.g. Shor’s Algorithm), and this poses significant risks to cryptographic protocols that are at the heart of financial infrastructures today.
  
  This theme invites new R&D directions in quantum-safe cryptographic techniques and protocols. Further, we also invite ideas on how quantum computing can impact risk analysis, portfolio optimization, time-series forecasting, and machine learning. We invite R&D directions in the development of algorithms to solve large optimization problems related to financial applications and the statistical analysis of the solutions obtained from noisy intermediate-scale quantum (NISQ) computers.