• AI IN REGTECH VIRTUAL SUMMIT

  • 09:00

    WELCOME & OPENING REMARKS (ALL TIMES EDT)

  • PLENARY SESSION

  • 09:10
    Javier Perez

    The Growth of AI Open-Source Software in Unexpected Platforms

    Javier Perez - Open Source Program Strategist - IBM

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    The Growth of AI Open-Source Software in Unexpected Platforms

    Today Open Source Software (OSS) is more prevalent than in any other era and continues to grow with the latest technologies from AI and Data Science to Blockchain and Autonomous Vehicles. In this session, we are going to review AI open-source in unexpected platforms. Specifically, we are going to cover OSS in the modern mainframe, the platform used by most financial services organizations, including now fintech startups every large financial institution.

    Tensorflow, Python, Spark, and many other widely used OSS have become the building blocks of all AI and ML applications. Open-source is addressing the major trends in the Financial industry: Modernization with AI and big data, regulatory compliance, and DevOps.
    Open Source Software for mainframes is neither widely known nor something new. This session is going to present information on how open source is done for mainframes and how to port existing software to a modern platform available in all Linux distributions.

    Key Takeaways: • Learn about available open source software in AI • Learn about the platform of choice for AI in Financial institutions • Learn how to continue the growth of the open-source ecosystem for AI

    Javier Perez leads the Open Source Program for the IBM Z and LinuxONE ecosystem at IBM. Javier has been in the Open Source, Cloud, SaaS, and Mobile industries for 20+ years. He has been working directly with Open Source Software (OSS) for over 10 years, more recently leading product strategy of the Software Composition Analysis product line at Veracode. Prior to Veracode, Javier was at Axway leading a successful open source project, Appcelerator, and at Red Hat where he was Director of Product Management driving the OpenShift-based Mobile Application Platform offering for developers and enterprises including containerized applications. Javier has had the opportunity to speak at webinars and conferences all over the world covering open source, security, cloud, and application development topics. Javier has held leadership positions in Product Management and Sales Engineering for different startups, leading successful product exits and product integrations post-acquisition. Javier holds an honors degree in Computer Systems and an MBA.

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  • THE CURRENT REGTECH LANDSCAPE

  • 09:20
    Colin Ware

    Horizon Scanning – Solutions Required to Understand and Interpret Regulations

    Colin Ware - Regulatory Product Manager - BNY Mellon

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    Horizon Scanning – Solutions Required to Understand and Interpret Regulations

    There is an increasing need to know what and when regulatory changes are coming, and how they may impact the industry. Market pressures are changing, and regulators are prioritizing the regulation of evolving business models. Firms are struggling to understand, prioritize and comply with the growing volume of regulations and reporting requirements. It is critical that financial firms increase their ability to: • Monitor and track complex regulations, updates and interpretations globally • Measure and assess the impact of regulatory changes on the business

    Colin has recently joined BNY Mellon as Regulatory Product Manager. He is responsible for ensuring that all products within Asset Servicing are compliant with upcoming regulations and serve our client’s needs to meet the regulatory requirements, including MIFID II, GDPR, MMFR. He represents the company on a number of RegTech Award panels and industry Event Advisory Boards, and helps to co-ordinate the BNY Mellon Tax & Regulatory Client Forum. This industry-leading event includes a number of RegTech panels and the creation of a regular BNY Mellon RegTech Forum. Prior to joining BNY Mellon, Colin spent 4 years working at Barclays as Industry & Regulatory Engagement Lead for Data Management, working with RegTech and vendor solution providers to assess solutions to meet the upcoming Regulatory challenges.Previously, he was Global Product Manager for Omgeo CTM responsible for developing the product to meet all client and regulatory requirements. He has also spent time at a number of leading Investment Bank institutions, including Deutsche Bank, Nomura, and Goldman Sachs, across a broad range of Data Management, Client Service and project management roles.

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  • 09:40
    Ansgar Koene

    UnBias AI For Decision Makers

    Ansgar Koene - Senior Research Fellow at Horizon Digital Economy Research institute - University of Nottingham

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    UnBias AI For Decision Makers

    To help decision makers involved in the development, deployment or use of AI systems explore how these systems align with their organisation’s ethos we developed the “UnBias AI For Decision Makers” (AI4DM) toolkit. The toolkit promotes a critical systems-thinking approach. It uses a set of hex-tiles with themes and questions to map the complexities of AI governance and policy against critical issues such as trust, reliability, quality assurance, due diligence and ethics.

    Dr. Ansgar Koene is an AI Regulatory Advisor at the EY Global where he supports the AI Lab’s Policy activities on Trusted AI. He is also a Senior Research Fellow at the Horizon Institute for Digital Economy Research (University of Nottingham). Ansgar chairs the IEEE P7003 Standard for Algorithmic Bias Considerations working group, is the Bias Focus Group leader for the IEEE Ethics Certification Program for Autonomous and Intelligent Systems (ECPAIS), and a trustee for the 5Rgiths foundation for the Rights of Young People Online. Ansgar has a multi-disciplinary research background, having worked and published on topics ranging from Policy and Governance of Algorithmic Systems (AI), data-privacy, AI Ethics, AI Standards, bio-inspired Robotics, AI and Computational Neuroscience to experimental Human Behaviour/Perception studies. He holds an MSc in Electrical Engineering and a PhD in Computational Neuroscience.

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  • AI FOR REGULATORS

  • 10:00
    Knarig Arabshian

    LEX: Language Extraction Engine

    Knarig Arabshian - Senior Associate Knowledge Engineer - The Federal Reserve Bank of New York

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    LEX: Language Extraction Engine

    LEX, is a thematic language extraction NLP engine that uses rule-based and machine learning techniques to identify and extract thematic language from documents. The goal of LEX is to highlight sentences within documents pertaining to specific type of language. The engine uses two sources of input to determine the extractions: a lexicon of specific terminology as well as a word-vector model. The lexicon contains rules constructed by a domain expert; while the word embedding model is used to find similar terms to those contained in the lexicon rules. LEX provides a way for different GUI dashboards to be generated which allows users to further browse the document corpus and interact with the results. It also highlights the extracted sentences within the original document. Thus, after homing in on relevant sentences, the user can go directly to the sentence within the document and read it in context.

    Knarig is a Senior Associate Knowledge Engineer at the Federal Reserve Bank of New York. She conducts research in Natural Language Processing, Machine Learning and Semantic Technologies related to bank problems. Prior to her time at the Fed, she was a professor at Columbia and Hofstra Universities and a research scientist at Bell Labs. She holds a PhD in Computer Science from Columbia University.

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  • AI APPLICATIONS IN REGTECH

  • 10:20
    Igor Sumkovski

    AI and Machine Learning Solutions for Fighting Financial Crime – FIs (banks) and RegTech Firms Partnering for the Future

    Igor Sumkovski - Senior Manager Financial Crime Compliance Advisory - Santander

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    AI and Machine Learning Solutions for Fighting Financial Crime – FIs (banks) and RegTech firms Partnering for the Future

    This presentation will cover: - Where AI solutions are most helpful in solve regulatory compliance, with specific focus on financial crime related legal & regulatory obligations? - The role of RegTech in reducing inefficiency/ ineffective Financial Crime processes. - Barriers and obstacles to using AI. Overcoming challenges.
    - Bringing FIs (banks) and Regtech firms closer, better understanding of each other’s perspectives and finding common ground. - Future focus - keeping up with AI and Financial Crime risks in an evolving regulatory landscape.

    As a Senior Financial Crime Manager for Santander, Igor is responsible for the implementation and delivery of an effective Financial Crime risk management strategy and policy framework. He obtained his Master’s Degree in Financial Regulation, International Corporate Governance and Economic Law at the Institute of Advanced Legal Studies, University of London and he is ICA qualified financial crime professional with proven BAU and project management experience, gained within some of the largest UK and EU banks. Igor has a strong anti-financial crime background and comprehensive understanding of the external environment in respect to regulators, industry practice and benchmarking, strong knowledge of the UK/EU financial crime compliance legal and regulatory frameworks. He has genuine interest in AI and Machine Learning, committed to continuously exploring opportunities to use new technologies for greater effectiveness in combating financial crime.

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  • 10:40
    Aparna Dhinakaran

    Why You Need Machine Learning Observability

    Aparna Dhinakaran - Co-Founder & CPO - Arize AI

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    Why you need Machine Learning Observability

    This talk will cover common challenges seen in models deployed in production, including model drift, data quality issues, distribution changes, outliers, and bias. The talk will also highlight best practices to address these challenges and where observability and explainability can help identify model issues before they impact the business. Aparna will be sharing a demo of how the Arize AI platform can help companies validate their models performance, provide real-time performance monitoring and alerts, and automate troubleshooting of slices of model performance with explainability.

    Aparna Dhinakaran is Chief Product Officer at Arize AI, a startup focused on ML Observability. She was previously an ML engineer at Uber, Apple, and Tubemogul (acquired by Adobe). During her time at Uber, she built a number of core ML Infrastructure platforms including Michaelangelo. She has a bachelors from Berkeley's Electrical Engineering and Computer Science program where she published research with Berkeley's AI Research group. She is on a leave of absence from the Computer Vision PhD program at Cornell University.

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  • 10:55

    COFFEE

  • CHANGES IN REGULATIONS

  • 11:30
    Eryk Walczak

    Measuring Complexity of Banking Regulations Using NLP & Network Analysis

    Eryk Walczak - Senior Research Data Scientist - Bank of England

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    Measuring Complexity of Banking Regulations Using Natural Language Processing & Network Analysis

    The banking reforms that followed the financial crisis of 2007–08 led to an increase in UK banking regulation from almost 400,000 to over 720,000 words, and to concerns about their complexity. We define complexity in terms of the difficulty of processing linguistic units, both in isolation and within a broader context, and use natural language processing and network analysis to calculate complexity measures on a novel dataset that covers the near universe of prudential regulation for banks in the United Kingdom before (2007) and after (2017) the reforms. Linguistic, ie textual and network, complexity in banking regulation is concentrated in a relatively small number of provisions, and the post-crisis reforms have accentuated this feature. In particular, the comprehension of provisions within a tightly connected ‘core’ requires following long chains of cross-references.

    Key Takeaways: • AI/ML techniques can be used to study complexity of banking regulations • We describe the changes to the UK banking regulations before and after the Great Financial Crisis (2007 vs. 2017) • We develop a new dataset that can be used for other purposes. This research can be seen as an early step towards automating banking regulations (RegTech)

    Eryk Walczak is a senior research data scientist in the Advanced Analytics Division at the Bank of England. Prior to joining the Bank, Eryk worked in analytic roles for a fintech and a social media company. His current research interests involve applying data science and experimental methods to study macroeconomics.

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  • RISK MANAGEMENT

  • 11:50
    Brennan Lodge

    A Home Grown Machine Learning Pipeline for the Security Incident Response Team (SIRT)

    Brennan Lodge - Data Science Lead for SIRT - Goldman Sachs

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    A Home Grown Machine Learning Pipeline for the Security Incident Response Team (SIRT)

    Security Incident Response Teams (SIRT) have a blend of infrastructures, disparate logs and data sets, a SEIM, ticketing systems and a need for analytics to better serve and improve their firm's detective cyber security control posture and incident response capabilities. An analytics platform that can be robust, stable, compliant, version controlled and automated to deploy analytics to better serve SIRTs missions are the goals to be discussed. An additional use case of implementing a machine learning application and API service to predict Domain Generating Algorithms with the integrated data science pipeline and platform is also discussed and used as a reference.

    Key Takeaways: • Implementing Data Solutions is hard • Machine Learning development should be treated differently from software engineering development • There are viable implementations of machine learning within the cyber security domain

    Brennan is a self-proclaimed data nerd. He has been working in the financial industry for the past 10+ years and is striving to save the world with a little help from our machine friends. He has held cyber security, data scientist, and leadership roles at JP Morgan Chase, the Federal Reserve Bank of New York, Bloomberg, and Goldman Sachs. Brennan holds a masters' degree in Business Analytics from New York University and participates in the data science community with his non-profit pro-bono work at DataKind, and as a co-organizer for the NYU Data Science and Analytics Meetup. Brennan is also an instructor at the New York Data Science Academy and teaches data science courses in R and Python.

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  • 12:10

    PANEL: How to Secure Representative Data Sets & Reduce Bias

  • Yemi Oluseun

    Moderator:

    Yemi Oluseun - Programme Manager - The Change Hive

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    Yemi is a Principal Consultant at The Change Hive, a strategic change management firm. She most recently led the digital transformation programme at a boutique Arab bank. She also previously delivered the key parts of the Brexit programme and the Ring Fenced Bank project at Barclays.

    She is listed on the 2020 and 2019 UK Top 100 Computing Weekly Most Influential Women in Technology and the 2019 TechWomen List.

    She holds an executive MBA from London Business School as well as First Class and Distinction Degrees in Computer Science. She co-led the winning team in the 2018 Barclays Social Fintech Innovation hackathon.

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  • Michael Berns

    Panelist:

    Michael Berns - Director, AI & FinTech Lead - PwC

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    Michael is a Director at PwC where he leads the AI and FinTech Practice. He is an AI Thought Leader & FinTech Veteran with 17 years of international experience having run client engagements on five continents.

    He spent more than a decade leading engagements with Fortune 500 companies before then disrupting that space with innovative solutions after his Executive MBA at London Business School.

    Michael has a broad background across blue chip names such as Morgan Stanley & Moody's as well as a range of smaller innovative AI Firms.

    Aside from his day job he also takes a keen interest in understanding the latest in innovation by helping AI firms to scale and has been a Mentor and Judge for organizations like Startup Bootcamp, Virgin Money Startup, Cocoon Network, Level 39 and MIT IIC for the last 9 years.

    As a well-known Expert in his field, Michael acts as keynote speaker at international conferences and guest lecturer at a number of business schools including London Business School, Mannheim Business School, IMC and others.

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  • James Brusseau

    Panelist

    James Brusseau - Director of Data Ethics Site - Pace University

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    James Brusseau (PhD, Philosophy) is author of books, articles, and media in the history of philosophy and ethics. He has taught in Europe, Mexico, and currently at Pace University near his home in New York City. As Director of AI Ethics Site, a research institute currently incubating at Pace University, he explores the human experience of artificial intelligence in the areas of privacy, autonomy, and authenticity, and as applied to finance, healthcare and media. Current applied ethics project is AI Human Impact: AI-intensive companies rated in human and ethical terms for investment purposes.

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  • Martina Macpherson

    Panelist:

    Martina Macpherson - SVP Strategic Partnerships & Engagement - Moody's

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    Martina Macpherson is Senior Vice President, Strategic ESG Engagement & Partnerships, at Moody’s, and President of the Network for Sustainable Financial Markets. Martina has held a number of ESG and innovation leadership roles including Head of ESG Index Products at S&P DJI, Managing Director of Sustainable Investments Partners Ltd. and Vice President of ESG Solutions at MSCI. She has been working in the ESG, index and asset management industry for almost 20 years and has been a member of multiple sustainable finance associations and policy working groups at UK, EU and at an international level. Currently, Martina is part of the UNGC SDG CFO Taskforce, the European Law Institute’s Sustainable Finance Working Group, CBI’s Transition Bond Technical Expert Group, and Enterprise Data Management’s Working Group on ESG Data, Innovation, Technology and Metrics. She co-authored “The AI Book” (2020). Martina is a visiting fellow in sustainable finance at University of Zurich and Henley Business School. She has an MBA certificate in finance and business from LSBF / UK, and a MA in Law and Human Sciences from University of Frankfurt in Germany. She is a doctoral fellow of the Institute of Certified Risk Management Professionals UK, a fellow member of the ICRS, and an alumni of the German National Academic Foundation.

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  • Ansgar Koene

    Panelist:

    Ansgar Koene - Senior Research Fellow at Horizon Digital Economy Research institute - University of Nottingham

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    UnBias AI For Decision Makers

    To help decision makers involved in the development, deployment or use of AI systems explore how these systems align with their organisation’s ethos we developed the “UnBias AI For Decision Makers” (AI4DM) toolkit. The toolkit promotes a critical systems-thinking approach. It uses a set of hex-tiles with themes and questions to map the complexities of AI governance and policy against critical issues such as trust, reliability, quality assurance, due diligence and ethics.

    Dr. Ansgar Koene is an AI Regulatory Advisor at the EY Global where he supports the AI Lab’s Policy activities on Trusted AI. He is also a Senior Research Fellow at the Horizon Institute for Digital Economy Research (University of Nottingham). Ansgar chairs the IEEE P7003 Standard for Algorithmic Bias Considerations working group, is the Bias Focus Group leader for the IEEE Ethics Certification Program for Autonomous and Intelligent Systems (ECPAIS), and a trustee for the 5Rgiths foundation for the Rights of Young People Online. Ansgar has a multi-disciplinary research background, having worked and published on topics ranging from Policy and Governance of Algorithmic Systems (AI), data-privacy, AI Ethics, AI Standards, bio-inspired Robotics, AI and Computational Neuroscience to experimental Human Behaviour/Perception studies. He holds an MSc in Electrical Engineering and a PhD in Computational Neuroscience.

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  • 12:50

    VIDEO ROUNDTABLE NETWORKING MIXER

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