• 08:00

    REGISTRATION & LIGHT BREAKFAST

  • 09:00
    Marie Paolantonio

    WELCOME NOTE

    Marie Paolantonio - Data Governance Domain Expert - Informatica

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    Marie has over 20 years of experience in Data Strategy, Business Intelligence and Data Governance across industries from telecommunications to entertainment media and more. Having spent her career in the customer seat, she has a deep understanding of what drives customers to seek our solutions and what pain points organizations are trying to solve for. She believes in looking for ways to help organizations harness their goals through enabling data driven decisions and effective communication.

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  • CURRENT LANDSCAPE OF AI IN INSURANCE

  • 09:15
    Tamara Zaichkowsky

    Harnessing Human + Artificial Intelligence to Break Barriers

    Tamara Zaichkowsky - Chief Digital Officer - Acrisure

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    Harnessing Human + Artificial Intelligence to Break Barriers

    In this talk, Tamara will discuss how companies can use technology to expand beyond the boundaries of their industry’s traditional business models by blending human and artificial intelligence. This powerful combination balances the need to foster relationships, build trust and solve for customers’ complex needs, using the intuition, creativity and empathy that is only available from human intelligence – with the opportunity to go a step further, using data to act with a level of precision, efficiency, and insight that only AI can provide. Tamara will make the case for why doubling down on the blend of human capabilities and technology is necessary to drive innovation forward, ultimately enhancing the customer experience, increasing customer satisfaction, and driving faster, easier organic growth.

    Tamara Zaichkowsky is Chief Digital Officer at Acrisure, a fintech leader specializing in intelligence-driven financial services, providing a broad array of products and solutions across Insurance, Real Estate Services, Cyber Services, and Asset Management. In her role, Tamara is responsible for digital transformation across the organization specifically focused on the development and execution of the digital marketplace, digitally enabled cross selling and product optimization through the use of machine learning and artificial intelligence. Prior to joining Acrisure, she served as an Executive Vice President and Head of the Restructuring Office for Consumer and Business Banking, Santander, N.A. As such, Tamara oversaw Santander's activities related to corporate restructuring, operational redesign, and digital transformation across the branch network inclusive of the simplification and streamlining of processes and technical solutions. Tamara has held various leadership positions within Santander’s Business Development, IT Transformation, Finance and Human Resources departments.

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  • 09:40
    Michael Kropidlowski

    Intelligent Insurance Virtual Assistant using Conversational AI

    Michael Kropidlowski - Global VP, Product Marketing - kore.ai

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    Today, consumers have ultimate choice in nearly every industry, from financial and insurance services, to telecommunications, to online retail. Knowing how to provide the best engagement, every time, is the key to keeping customers coming back for more.  Today’s reality is consumers will stop doing business with a company because of a poor service experience and Insurance Providers are no exception and are usually well below average when compared to other vertical markets. In this session, we will cover how conversational AI for the insurance industry can be tuned and optimized to provide extraordinary service experiences, keeping employees happy and customers coming back for more.  We will explore how you can:

    Manage digital claims conversationally and quickly while eliminating avoidable delays and frustration

    Deliver personalized quotes without jumping through hoops, and simplify everyday tasks such as rate and provider searches, account updates and payments

    Provide right-time, right-fit suggestions that make sense, and offer instant support and omnichannel experiences across all channels – text, email, mobile app, website, or voice 

    Join us to learn how intelligent, AI-powered virtual assistants (VA)s create engaging and differentiated customer experiences for your policyholders – turning everyday interactions into familiar, personalized and highly informative engagements

    As a Worldwide VP of Product Marketing at Kore.ai, Michael contributes directly to company strategy with a view to market trends and product strategy, focusing on enhanced customer and employee experiences enabled through omnichannel conversational AI engagement strategies.

    Michael leads the product marketing team to effectively promote the value Kore.ai solutions can bring to existing customer and new logo client organizations. Additionally, his team is responsible for competitive intelligence, product sales enablement and analyst relations to drive growth and recognition of Kore.ai solutions in the market.

    Michael has more than 30 years of experience in the customer service and contact center industries. Before joining Kore.ai in February 2022, Michael spent 22 years at Alvaria where he initially directed sales and technical channel partner training and transitioned to lead product marketing for the company’s customer experience and workforce engagement contact center portfolio.

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  • 10:05
    Alejandro Zarate Santovena

    How to Achieve Effective AI Product Management

    Alejandro Zarate Santovena - Head of Data Strategy - Marsh

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    How to Achieve Effective AI Product Management

    When it comes to Artificial Intelligence new development, it is easy to fall prey to the illusion of all possibilities around new technologies. AI product management focuses on using artificial intelligence, machine learning, and deep learning to create or improve products. Making the most of new technology is critical to maintaining a disciplined approach to innovation. In this presentation, we will review the importance of effective product management and value proposition design before embarking on developing artificial intelligence-based analytics and products.

    Alejandro Zarate Santovena has more than 25 years of global experience in technology, consulting, and marketing. His work has taken him to Europe, Latin America, and the United States, where he has become a leader in business intelligence, product development and Artificial Intelligence.

    Alejandro began working in sales and business development in 2010 at Marsh Mexico. He is now Managing Director at Marsh-USA, where he leads Data Strategy for Global Placement and Specialty. Throughout his career at Marsh, Alejandro has focused on utilizing Machine Learning and Data Science to drive business intelligence and innovative product development globally, leading teams in New York, London and Dublin. Alejandro received an M.S. in Management of Technology - Machine Learning, AI and Predictive Modeling from the Massachusetts Institute of Technology, an M.B.A. from Carnegie Mellon University and a B.S. in Chemical Engineering from the Universidad Iberoamericana in Mexico City.

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  • 10:30

    COFFEE & NETWORKING BREAK

  • AI SOLUTIONS

  • 11:15

    Probabilistic Document Routing with Schema Drift Conformance

  • Sajad Alabadi

    Speaker

    Sajad Alabadi - Lead ML Engineer - Accelerant Holdings

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    Augmenting and improving operational insurance processes to support dynamic data extraction for downstream activities. After analyzing over 1000 varying insurance documents, we have utilized supervised classification machine learning models with probabilistic means inserted at critical decision points in the flow. We cut down the operation cost of the initial files onboarding process by 50% using ML models/Process in place of humans in the loop.

    • +5 years of working experience as Data Scientist, Machine Learning and Computer Vision Eng. • Strong data analytical and programming skills, specifically with SQL, Python, Java, Scala, Spark. • Strong web development skills including but not limited to Django, Bootstrap, HTML, JS. • Strong Knowledge with the Online Clouds/ML platforms, Google, Azure, H2O and Databricks. • Strong Knowledge with Analytical platforms such as PowerBI and Tableau. • Ability to work under pressure and possess exceptional problem-solving skills. • Excellent organizational and time management skills, awareness of devOps and Agile principles. • Team player with excellent written/verbal communication skills.

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  • Philip Cwynar

    Speaker

    Philip Cwynar - ML Engineer - Accelerant Holdings

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    Augmenting and improving operational insurance processes to support dynamic data extraction for downstream activities. After analyzing over 1000 varying insurance documents, we have utilized supervised classification machine learning models with probabilistic means inserted at critical decision points in the flow. We cut down the operation cost of the initial files onboarding process by 50% using ML models/Process in place of humans in the loop.

    Linkedin
  • 11:40
    Pamela Negosanti

    The Moment of Truth: How Intelligent Automation Can Put Customers First in the Claims Process

    Pamela Negosanti - Global Head of Insurance - expert.ai

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    Customer centricity is the core of every insurance strategy, but how can AI and specifically NLP help carriers put customers first when it comes to claims? The challenges around speed and quality remain, but technology proved to bring tangible results.

    In this session we will cover:

    • Top challenges when it comes to automating the claims process? • How to automate claims processes? • The main KPIs to watch when it comes to claims automation using NLP? • Best practices and a few real-world case studies

    Pamela Negosanti is the Global Head of Insurance at expert.ai. She specializes in helping companies in the insurance space, such as carriers, brokers, reinsurers, and TPAs execute business transformation through artificial intelligence. Pamela has spent most of her career in the technology sector where she has established expertise in artificial intelligence, cognitive computing, intelligent automation, natural language understanding and semantics, to name a few. She owns a degree in translating and interpreting with a specialization in computational linguistics, and speaks fluent Italian, English, French and German. Fueled by change and curiosity, she is firm believer in the power of knowledge share and communities.

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  • 12:05
    Julia Romero

    Delivering On The Promise Of AI/ML In Life Insurance

    Julia Romero - Lead for Actuarial Engineering & Advanced Modeling - Haven Technologies

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    When we first started talking about AI and ML in the life and annuity space, we had big ambitions about how these new tools would help us crack some of the most significant challenges facing the industry. By lowering costs, improving precision, and improving access AI and ML were going to allow us to: • Get life insurance coverage into the hands of the middle market • Smooth the path from retirement savings to income security • Find new ways to help financially insecure Americans deal with a sudden illness or injury

    Standing here in 2022, it is clear that the industry has failed to deliver on these goals in any meaningful way.

    This talk is about why the industry has failed to deliver on the initial ambitions of AI and ML, what we need to learn from those failures, and most importantly, why we should keep trying to pursue the spirit of those original aspirations.

    Julia Romero is the lead for Actuarial Engineering and Advanced Modeling at Haven Technologies, a modern, advanced, and cloud-native insurtech offering for the life, disability, and fixed annuities industries. At Haven Technologies, Julia is focused on actuarial technology and applying data science and other analytics models to drive innovation in actuarial services. Prior to joining Haven Technologies, Julia oversaw similar responsibilities at Haven Life, the digital life insurance agency backed and wholly owned by MassMutual.

    Prior to Haven, Julia worked as an actuary at AXA US, where she focused on the development of agent-based models of annuity policyholder behavior. Julia graduated from Colgate University and is a Fellow of the Society of Actuaries and a Member of the American Academy of Actuaries.

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  • 12:30

    LUNCH

  • 12:30
    Bill Cox

    ROUNDTABLE: How Deep Learning Models Help Infuse AI to Assess, Automate and Accelerate Core Financial Functions

    Bill Cox - Senior Director, North America Sales - SambaNova Systems

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    ROUNDTABLE: How Deep Learning Models Help Infuse AI to Assess, Automate and Accelerate Core Financial Functions

    Finance has long been seen as visionary; applying machine learning algorithms to automate and accelerate key business processes from capital markets to compliance, risk, and enhancing the customer experience. Today, many of the legacy models are losing their effectiveness while the velocity of data has grown exponentially with an increasing variety of data types and formats. Quite often, the teams that build these older models are long gone. The convergence of these factors presents both a dilemma and an opportunity. In this roundtable session you will learn how NLP models can uncover non-linear patterns between disparate & unstructured datsets impacting risk, compliance, capital markets and customer engagement technology.

    Bill Cox is the Senior Director Sales North America at SambaNova Systems driving deep learning implementations for both Public Sector and Enterprise accounts. Bill has extensive experience leading Global Sales teams in HPC compute and storage companies.

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  • AI APPLICATIONS IN INSURANCE

  • 13:40
    Antonio Hung

    What's Inside the Box: A Guide on How to Understand What Your Model is Doing

    Antonio Hung - Machine Learning Engineer - Progressive Insurance

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    What's Inside the Box: A Guide on How to Understand What Your Model is Doing

    As machine learning models become larger, the harder it is to understand their inner workings. As these models achieve and even beat human-level performance at many tasks, it might not be as useful, if you don't understand why the model predicts a certain result for a given feature set. In any domain, especially in insurance, we as Data Scientists and ML Engineers, should know why a model predicts a certain outcome and be able to deliver those findings to stakeholders and even our customers. We also need to be aware of scenarios where simple models, which are easy to understand, are a better choice than more complicated, yet more accurate deeper models This talk will cover why it is important to understand model predictions and how it impacts the customer. We’ll also cover a few techniques on interpreting machine learning models and learn how we can integrate these techniques into out Machine Learning pipelines. We'll also talk about simpler models, and even rule based models, which might not be the best in terms of accuracy, but are more explainable.

    Tony Hung is a Data Engineer Lead at Progressive, working on building out systems to help accelerate the use of data science by removing the burden of infrastructure provisioning, enabling the sharing of curated data among different teams, and ensuring that artificial intelligence is used responsibly and in compliance with upcoming AI regulations. In previous lives, he worked as a machine learning practitioner, for both small and large companies, building out models in NLP, audio and financial time series data

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  • 14:05
    Lifan Wu

    Premium anomaly detection in Life Insurance

    Lifan Wu - Data Scientist - Swiss RE

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    Premium anomaly detection in Life Insurance

    While pricing and underwriting are core to the insurance industry, it is also critical for insurance companies to keep healthy portfolios in their books for operational risk control and profitability. In this session, we will talk about and compare several statistical and machine learning methodologies that help automatically identify abnormal premium received from clients on a large scale. Such ideas can also be generalized to a broader context, for example, claims.

    Lifan Wu is a Data Scientist at Swiss Re, working on building machine learning models and providing data-driven solutions to facilitate underwriting and portfolio management across business lines. Before joining Swiss Re, Lifan completed her Ph.D. study in operations research from Cornell University with her research focusing on extreme value theories. She also finished her M.Eng. in financial engineering at Cornell as well as her B.S. in actuarial science and mathematics at Purdue University.

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  • 14:30
    Monique Hesseling

    The Potential, the Possible and the Pragmatic of AI in Insurance

    Monique Hesseling - Managing Director of Insurance - Cloudera

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    Opportunities abound for the application of AI across the insurance spectrum from sales & marketing initiatives to improved underwriting and claims processing. Yet, advancing an organization from traditional, proven methodologies to the potential offered by artificial intelligence requires both maturing the technology and an organizational shift. What does it take to move from experimentation to production? In this session we’ll review some of the evolution to date including:

    • AI project goals - improved risk assessment, personalization, cost reduction, etc. • Tools for Success - Data, Skill sets, Sponsor • Sample Success - Example case studies • Gotchas - Lesson learned, best practices and what to avoid

    Monique brings insight and expertise in both business leadership and data strategy to her role at Cloudera, where she works with insurance clients to optimize their use of data, analytics, and machine learning across the enterprise. Monique’s career has primarily been in business leadership and data and analytics roles in insurance, working for companies including AON, Chubb, Mutual of Omaha, and Zurich Financial Services.

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  • 14:55

    COFFEE & NETWORKING BREAK

  • 15:40
    Michael Natusch

    Deep Learning in Insurance Beyond Niche Applications

    Michael Natusch - Chief Science Officer - Prudential

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    A look into leading-edge statistical methods to tackle real-world problems, which today means applying machine learning and neural networks to large-scale, multi-structured data sets.

    Michael is the Chief Science Officer of Prudential plc. He joined Prudential last year from Silicon Valley based Pivotal Labs where he led the Data Science team. His experience lies in the application of artificial intelligence methods to large-scale, multi-structured data sets, in particular neural network based deep learning techniques. Michael previously founded and sold a ‘Silicon Roundabout’ based startup and prior to that was a partner at a major consulting firm. Michael holds a PhD in theoretical physics from the University of Cambridge and is a Fellow of the Royal Statistical Society.

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  • 16:15

    PANEL: Operationalizing AI in Insurance

  • Julia Romero

    Moderator

    Julia Romero - Lead for Actuarial Engineering & Advanced Modeling - Haven Technologies

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    When we first started talking about AI and ML in the life and annuity space, we had big ambitions about how these new tools would help us crack some of the most significant challenges facing the industry. By lowering costs, improving precision, and improving access AI and ML were going to allow us to: • Get life insurance coverage into the hands of the middle market • Smooth the path from retirement savings to income security • Find new ways to help financially insecure Americans deal with a sudden illness or injury

    Standing here in 2022, it is clear that the industry has failed to deliver on these goals in any meaningful way.

    This talk is about why the industry has failed to deliver on the initial ambitions of AI and ML, what we need to learn from those failures, and most importantly, why we should keep trying to pursue the spirit of those original aspirations.

    Julia Romero is the lead for Actuarial Engineering and Advanced Modeling at Haven Technologies, a modern, advanced, and cloud-native insurtech offering for the life, disability, and fixed annuities industries. At Haven Technologies, Julia is focused on actuarial technology and applying data science and other analytics models to drive innovation in actuarial services. Prior to joining Haven Technologies, Julia oversaw similar responsibilities at Haven Life, the digital life insurance agency backed and wholly owned by MassMutual.

    Prior to Haven, Julia worked as an actuary at AXA US, where she focused on the development of agent-based models of annuity policyholder behavior. Julia graduated from Colgate University and is a Fellow of the Society of Actuaries and a Member of the American Academy of Actuaries.

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  • Philip Cwynar

    Panelist

    Philip Cwynar - ML Engineer - Accelerant Holdings

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    Augmenting and improving operational insurance processes to support dynamic data extraction for downstream activities. After analyzing over 1000 varying insurance documents, we have utilized supervised classification machine learning models with probabilistic means inserted at critical decision points in the flow. We cut down the operation cost of the initial files onboarding process by 50% using ML models/Process in place of humans in the loop.

    Linkedin
  • Sajad Alabadi

    Panelist

    Sajad Alabadi - Lead ML Engineer - Accelerant Holdings

    Down arrow blue

    Augmenting and improving operational insurance processes to support dynamic data extraction for downstream activities. After analyzing over 1000 varying insurance documents, we have utilized supervised classification machine learning models with probabilistic means inserted at critical decision points in the flow. We cut down the operation cost of the initial files onboarding process by 50% using ML models/Process in place of humans in the loop.

    • +5 years of working experience as Data Scientist, Machine Learning and Computer Vision Eng. • Strong data analytical and programming skills, specifically with SQL, Python, Java, Scala, Spark. • Strong web development skills including but not limited to Django, Bootstrap, HTML, JS. • Strong Knowledge with the Online Clouds/ML platforms, Google, Azure, H2O and Databricks. • Strong Knowledge with Analytical platforms such as PowerBI and Tableau. • Ability to work under pressure and possess exceptional problem-solving skills. • Excellent organizational and time management skills, awareness of devOps and Agile principles. • Team player with excellent written/verbal communication skills.

    Linkedin
  • Eileen Potter

    Panelist

    Eileen Potter - Solution Leader, Insurance - ABBYY

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    Results-driven business professional with more than 25 years of insurance and insurance technology experience. Extensive knowledge of commercial, personal and specialty lines, including insurance operations on both the agency and company levels.

    Creative problem solver with experience in software marketing, industry alliances, sales support, business operations and system implementations. Strong communication skills with the ability to execute and partner with peers, clients and other stakeholders.

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  • 17:00

    NETWORKING RECEPTION

  • 18:00

    END OF SUMMIT

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