• 08:00

    REGISTRATION & LIGHT BREAKFAST

  • 09:00
    Tracey Smith

    WELCOME NOTE

    Tracey Smith - Insurtech & Fintech SME - Independent

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    The insurtech space has come a long way from its early days in 2015/16 and over the last couple of years we have seen very significant valuations, 24 unicorns created and a few IPOs. How have insurtechs influence innovation insurance space, what is the role of AI within this and how will the landscape change going forward.

    Over 10 years experience working in the insurance sector with a focus on strategy and innovation. Expertise in the insurtech and fintech ecosystem in the UK and globally. Experienced in leading people, developing products and propositions, developing strategies & business models, consulting and M&A including startup

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  • CHANGING LANDSCAPE OF AI IN INSURANCE

  • 09:15
    Tracey Smith

    The Changing Landscape of InsurTech

    Tracey Smith - Insurtech & Fintech SME - Independent

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    The insurtech space has come a long way from its early days in 2015/16 and over the last couple of years we have seen very significant valuations, 24 unicorns created and a few IPOs. How have insurtechs influence innovation insurance space, what is the role of AI within this and how will the landscape change going forward.

    Over 10 years experience working in the insurance sector with a focus on strategy and innovation. Expertise in the insurtech and fintech ecosystem in the UK and globally. Experienced in leading people, developing products and propositions, developing strategies & business models, consulting and M&A including startup

    Linkedin
  • 09:40
    Avinash Mehrotra

    Building a Business Mindset for AI

    Avinash Mehrotra - Founder, CEO - Good Driver Car Insurance

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    This presentation will cover how to successfully take a project from POC to implementation, and a deep dive into the predictive model iceberg.

    Over 15 years of experience leading strategy, products and technology, setting up and scaling new ventures, pioneering innovations, leading strategy consulting engagements and setting up high performance teams within general insurance, financial services, biotech and internet sectors across UK, US and Europe. Areas of expertise include -

    Business Strategy and Planning, International Growth and Profitability, Cross Functional Leadership, Product and Tech Innovations, Partnerships and Contracts, Consultative Selling, Digital Transformation, Advanced Analytics, Offshoring and Operations Management.

    Linkedin
  • 10:05
    Christopher Holland

    Artificial Intelligence in Next-Generation Insurance: A Strategic Overview

    Christopher Holland - Professor of Information Management - University of Loughborough

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    Managers face key challenges in exploiting AI systems: to relate AI to business processes; develop an AI vision; and relate AI to the firm’s target business model. TECHNGI is a research project at Loughborough University investigating these and other ethical and regulatory challenges of AI adoption. Some important strategy results from this study are presented: an AI map of the insurance customer lifecycle; the data flywheel effect; and a business model typology that integrates AI and business models. The ideas are illustrated with examples, and the managerial implications of the results outlined.

    Professor C.P. Holland B.Sc. (Hons.) Ph.D. (Manchester), Fellow of the Institute of Directors Professor Holland has worked at the interface of business and digital technology throughout his career as an academic consultant. He leads on data science at the School of Business and Economics at Loughborough University, and is co-Director of TECHNGI, a novel University – industry partnership to investigate Artificial Intelligence (AI) in next-generation services. Professor Holland has extensive consultancy experience with a wide range of blue-chip organisations in telecommunications, technology, banking, insurance, grocery, and e-commerce. His main research and consultancy interests are digital marketing, Artificial Intelligence strategy, and AI ethics. He has held senior advisory roles in Government and regulatory authorities, including the Competition and Markets Authority (CMA) and the European Insurance and Occupational Pensions Authority (EIOPA).

    Linkedin
  • 10:30

    COFFEE & NETWORKING BREAK

  • AI DATA

  • 11:10
    Jonathan Davis

    Setting up Data Science for Delivery in Insurance

    Jonathan Davis - Lead Data Scientist - Zurich Insurance

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    Setting up a data science team with delivery at its heart is crucial to success. At Zurich we have been building a leading ML function, which combines a diverse skill-set with state-of-the-art tools. In this talk I will cover the journey we have been on to build our team, and the key skills we have needed to get to where we are. I will talk also about how we train and upskill our people, and how we make sure we are continuing to provide for the business and our customers.

    Jonathan holds the current position of Lead Data Scientist at Zurich Insurance UK, where he leads a team working on a variety of projects ranging from Internet of Things through to Natural Language Processing. He has a doctorate in Theoretical Astro-particle Physics from Durham University, and previously worked as a researcher at the Sorbonne in Paris and King's College London.

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  • INSURER SOLUTIONS

  • 11:35
    Melanie Zhang

    Algorithmic Underwriting at Lloyd's

    Melanie Zhang - Principal Algorithmic Portfolio Manager - Ki

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    Ki is the first fully digital and algorithmically-driven Lloyd's of London syndicate, offering instant capacity, anytime, anywhere. In 2020, Ki received the largest ever pre-series A investment for a FinTech in Europe, raising $500m from Blackstone and Fairfax. In our first year of trading, Ki became one of the largest ever start-up syndicates in Lloyd's with a 2021 full-year premium exceeding $400m. Find out more about how we built a data-first digital syndicate using a platform with proprietary algorithms, in collaboration with partners UCL and Google, to revolutionise a 333-year old insurance industry.

    Melanie is the Principal Algorithmic Portfolio Manager at Ki, working on pricing and data science strategies for the Ki algorithm. She previously worked as the Head of Property Innovation at AXIS and in various actuarial roles in the Lloyd's market since 2011. Melanie is a Fellow of the Institute and Faculty of Actuaries and holds an MSc in Computational Statistics and Machine Learning from UCL and an MA in Mathematics from Cambridge University.

    Linkedin
  • 12:00
    Sid Dhuri

    Understanding the Pain in the Claim with Human-In-The-Loop AI

    Sid Dhuri - Advanced Analytics Manager - Hiscox

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    Social media provides a more direct and relevant way for customers to interact with carrier’s around a claim and customers are active and vocal in sharing their positive or negative experience and the quality of customer experience can have a direct effect on the carrier's brand image and its customer base. After taking out an insurance policy, most customers will only interact with their insurer when they’re under the stress of experiencing a loss and need to make a claim. This is where most customer pain-points are typically realized. We apply NLP techniques with human-in-the-loop methodology to understand and eliminate the pain in the claim.

    Sid heads the claims analytics function at Hiscox, where he leads a team of data scientists across US, UK and Europe, helping claims operations with insights, forecasts and automation through the application of machine learning, modelling and NLP technologies. Sid has a Masters in data science from Ghent University, Belgium and has worked as an analytics consultant across industries applying machine learning, automation and AI to drive business outcomes. Previously Sid founded Orox.ai, an analytics as a service platform for marketing automation and analytics.

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  • 12:25

    LUNCH

  • 13:35
    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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  • 14:10
    Dapeng Wang

    Developing Monitoring Framework for Machine Learning Projects

    Dapeng Wang - Data Scientist - LV=

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    To ensure the continued benefit of a machine learning project, our work doesn’t stop after model deployment. With an ever-changing world and continued increase of decisions being driven by ML, it becomes increasingly important to understand any changes to the data and the model. We need to develop sophisticated monitoring to ensure expected performance of the model, highlight abnormalities, as well as provide meaningful set of result for the end user to act upon.

    The concept of monitoring is well known, often the requirement is an open-ended question. This talk will highlight some of the important points to consider when developing your ML monitoring framework.

    Dapeng Wang is a Senior Data Scientist at the insurance company LV=. He graduated in maths from the University of Cambridge and has an MSc from the University of Sussex. At LV=, Dapeng is leading in the adoption of Deep Learning across the company. He is currently developing the end to end pipeline to build and integrate Deep Learning within current LV= processes. Dapeng is also a frequent Kaggle competitor and Kaggle competition expert. Dapeng looks forward to using his experience to help the deep learning community find suitable and better implementation solutions for deep learning.

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  • 14:45

    COFFEE & NETWORKING BREAK

  • APPLICATIONS IN AI

  • 15:25
    Weijian Zhang

    Building Reliable and Scalable AI Systems

    Weijian Zhang - Machine Learning Engineer - Marshmallow Insurance

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    An artificial intelligence (AI) system is different from a traditional software system, in that we not only need to write production level code but also need to ensure and sustain data quality. There is often a lot of emphasis on novel algorithm design, however, we believe that more emphasis should be placed on the quality of data and the reliability of the AI system. An algorithm is only a small part of an AI system.

    At Marshmallow, we have designed and built a machine learning feature store in-house, which serves as the central source for common features, allowing for features to be used in both offline training and online serving. Utilising AWS SageMaker, we built a customised model training and deployment process. This has enabled our data scientists to own the whole machine learning life cycle and to stop relying on engineers for deployment.

    In this talk, we will present this new Feature Store and SageMaker workflow and show how it enables us to build reliable and scalable AI systems.

    Weijiang is a Machine Learning Engineer at Marshmallow Insurance, working on Developing Scalable AI Models. Particularly in terms of Mitigating Risk, Employing Speed and giving more autonomy to the Data Scientists.

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  • 15:50
    Patricia Wang

    Machine Learning For Specialty Insurance Underwriting

    Patricia Wang - Actuary - Gen Re

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    The dominant underwriting approach is a mix between rule-based engines and traditional underwriting. Applications are first assessed by automated rule-based engines which typically are capable of processing only simple applications. The remaining applications are reviewed by underwriters or referred to the reinsurers. This research aims to construct predictive machine learning models for complicated applications that cannot be processed by rule-based engines. Techniques such as natural language processing and clustering analysis are used to process free-text data such as descriptions of impairments and occupations. Various feature selection methods such as mutual information and recursive feature elimination are used to improve prediction accuracies. Machine learning algorithms such as XGB and Random Forest are used to predict underwriting decisions. XGB is the best performer with 99.5% accuracy on the training set and 80% accuracy on the testing set. Various tools such as word clouds and feature ranking functions are used to give underwriting insights. The paper concludes with data limitations and further researches.

    Patricia is an actuary based in London at Gen Re. She is a Fellow of both the Actuarial Society of South Africa and the Institute and Faculty of Actuaries having a combined ten years of experience in the South African and London markets. Her experience is primarily in financial reporting, financial modelling, data analytics and machine learning. Patricia completed her undergraduate studies in actuarial science at UCT and completed an MSc (with distinction) at Imperial College London in data analytics and machine learning. She is specifically interested in using machine learning and data analytic tools to resolve business problems in the life and health insurance sector. In 2019, Patricia served as a committee member of the IFoA Asia Conference. She is fluent in English and Chinese (Mandarin) and spoke at various actuarial conferences.

    Patricia is the winner of Swiss Re Prize for Best Reinsurance or Risk Paper and RGA Best Paper by First-time authors at the South African Actuarial Convention in October 2021

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  • 16:15

    PANEL: The ROI of AI in Insurance

  • Robin Jose

    Moderator

    Robin Jose - Chief Data & Analytics Officer - Wefox

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    Robin focuses on building innovative products and platforms powered by the disruptive capabilities of Data. He has strong expertise in building and scaling high performance teams and making them autonomous. Strong evangelist of the competitive advantage Analytics and AI bring to Organizations in the Digital Age.

    ★ "India's Top 25 Digitalist Thought Leaders", SAP ACE Awards, 2015 ★ ★ "Analytics Leader of the Year" - India Analytics Summit, Bangalore, 2016 ★

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  • Neha Pandey

    Panellist

    Neha Pandey - Enterprise Architect, Data & Analytics - Direct Line Group

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    Neha is the Enterprise Architect for Data & Analytics at Direct Line, working in Solutions & Architecture Strategy, Cloud, AWS, AI, Machine Learning, Analytics Ops, MLOps, Big Data, Data Lake, Agile and Enterprise Architecture

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  • Fiifi Arthur

    Panellist

    Fiifi Arthur - Data Science Manager - Zego

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    Fiifi Arthur is a Data Science Manager at Zego. Zego is an insurtech disrupting the gig economy. He has spent his career to date in the Analytics & Data Science space. The last 6 years leading Data Science teams in Consulting, Retail Finance and most recently, Motor Insurance. He enjoys leveraging Data Science & Analytics to improve KPIs across business units such as Pricing, Claims, Sales & Marketing & Operations

    Linkedin
  • 17:00

    NETWORKING RECEPTION

  • 18:00

    END OF DAY 1

  • 08:00

    DOORS OPEN FOR DAY 2

  • 09:00
    Michael Natusch

    WELCOME NOTE

    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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  • DETECTING & PREVENTING FRAUDULENT CLAIMS

  • 09:15
    Julie Wall

    Conversational AI Solutions for Combatting Insurance Fraud

    Julie Wall - Reader in Computer Science - University of East London

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    Conversational AI Solutions for Combatting Insurance Fraud

    Speech and natural language technology have advanced at a rapid pace in recent years. This advance, a facet of the industry 4.0 era, has been driven in part by GPU hardware and the deep learning frameworks that use them, and by the adoption of open-source ​software by the academic and commercial AI community alike. These developments have markedly impacted the way in which humans communicate with computers and are currently driving numerous commercial products that rely on speech, natural language processing and natural language understanding, loosely termed Conversational AI. This talk will introduce the machine learning and deep learning approaches, which enable Conversational AI, and present a real-world case study in the insurance domain that exploits speech and language to detect deception and tackle fraud.

    Dr Julie Wall is a Reader in Computer Science, Director of Impact and Innovation for the School of Architecture, Computing and Engineering and leads the Intelligent Systems Research Group at the University of East London. Her current research focuses on developing machine learning and deep learning approaches for speech enhancement, natural language processing and natural language understanding and she maintains collaborative R&D links with industry. This has led to the successful acceptance of two Innovate UK grants with a combined total value of £2,273,177. Since starting her PhD in 2006, Julie has been exploring the overarching research area of designing intelligent systems for processing and modelling temporal data. This primarily involves investigating the architectures and learning algorithms of neural networks for a variety of data sources.

    https://www.uel.ac.uk/research/intelligent-systems

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  • 09:45
    Özlem Gürses

    Insurtech and the Principles of Insurance Contract Law

    Özlem Gürses - Professor - Kings College London

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    Ethical, Legal & Cultural Considerations in Deep Learning

    Özlem Gürses is Professor of Commercial Law at King’s College London. She specialises in insurance and reinsurance law. Özlem is the author of Reinsuring Clauses (Informa), Marine Insurance Law (Routledge), Insurance of Commercial Risks (Sweet and Maxwell), and The Compulsory Motor Vehicle Insurance (Informa) as well as numerous articles published on insurance and reinsurance related topics. Özlem sits in the British Insurance Law Association Committee and the Presidential Council of the International Insurance Law Association (AIDA). She is Vice-Chair of the Reinsurance Working Party of AIDA. Özlem teaches insurance and reinsurance law at King’s College London and abroad, including National University of Singapore, University of Hamburg and World Maritime University, Malmö

  • 10:15

    COFFEE & NETWORKING BREAK

  • 11:00

    PANEL: The Future of AI in Insurance

  • Melanie Zhang

    Moderator

    Melanie Zhang - Principal Algorithmic Portfolio Manager - Ki

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    Ki is the first fully digital and algorithmically-driven Lloyd's of London syndicate, offering instant capacity, anytime, anywhere. In 2020, Ki received the largest ever pre-series A investment for a FinTech in Europe, raising $500m from Blackstone and Fairfax. In our first year of trading, Ki became one of the largest ever start-up syndicates in Lloyd's with a 2021 full-year premium exceeding $400m. Find out more about how we built a data-first digital syndicate using a platform with proprietary algorithms, in collaboration with partners UCL and Google, to revolutionise a 333-year old insurance industry.

    Melanie is the Principal Algorithmic Portfolio Manager at Ki, working on pricing and data science strategies for the Ki algorithm. She previously worked as the Head of Property Innovation at AXIS and in various actuarial roles in the Lloyd's market since 2011. Melanie is a Fellow of the Institute and Faculty of Actuaries and holds an MSc in Computational Statistics and Machine Learning from UCL and an MA in Mathematics from Cambridge University.

    Linkedin
  • Avinash Mehrotra

    Panellist

    Avinash Mehrotra - Founder, CEO - Good Driver Car Insurance

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    This presentation will cover how to successfully take a project from POC to implementation, and a deep dive into the predictive model iceberg.

    Over 15 years of experience leading strategy, products and technology, setting up and scaling new ventures, pioneering innovations, leading strategy consulting engagements and setting up high performance teams within general insurance, financial services, biotech and internet sectors across UK, US and Europe. Areas of expertise include -

    Business Strategy and Planning, International Growth and Profitability, Cross Functional Leadership, Product and Tech Innovations, Partnerships and Contracts, Consultative Selling, Digital Transformation, Advanced Analytics, Offshoring and Operations Management.

    Linkedin
  • Sid Dhuri

    Panellist

    Sid Dhuri - Advanced Analytics Manager - Hiscox

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    Social media provides a more direct and relevant way for customers to interact with carrier’s around a claim and customers are active and vocal in sharing their positive or negative experience and the quality of customer experience can have a direct effect on the carrier's brand image and its customer base. After taking out an insurance policy, most customers will only interact with their insurer when they’re under the stress of experiencing a loss and need to make a claim. This is where most customer pain-points are typically realized. We apply NLP techniques with human-in-the-loop methodology to understand and eliminate the pain in the claim.

    Sid heads the claims analytics function at Hiscox, where he leads a team of data scientists across US, UK and Europe, helping claims operations with insights, forecasts and automation through the application of machine learning, modelling and NLP technologies. Sid has a Masters in data science from Ghent University, Belgium and has worked as an analytics consultant across industries applying machine learning, automation and AI to drive business outcomes. Previously Sid founded Orox.ai, an analytics as a service platform for marketing automation and analytics.

    Twitter Linkedin
  • Weijian Zhang

    Panellist

    Weijian Zhang - Machine Learning Engineer - Marshmallow Insurance

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    An artificial intelligence (AI) system is different from a traditional software system, in that we not only need to write production level code but also need to ensure and sustain data quality. There is often a lot of emphasis on novel algorithm design, however, we believe that more emphasis should be placed on the quality of data and the reliability of the AI system. An algorithm is only a small part of an AI system.

    At Marshmallow, we have designed and built a machine learning feature store in-house, which serves as the central source for common features, allowing for features to be used in both offline training and online serving. Utilising AWS SageMaker, we built a customised model training and deployment process. This has enabled our data scientists to own the whole machine learning life cycle and to stop relying on engineers for deployment.

    In this talk, we will present this new Feature Store and SageMaker workflow and show how it enables us to build reliable and scalable AI systems.

    Weijiang is a Machine Learning Engineer at Marshmallow Insurance, working on Developing Scalable AI Models. Particularly in terms of Mitigating Risk, Employing Speed and giving more autonomy to the Data Scientists.

    Twitter Linkedin
  • 11:45

    PANEL: Assessing Privacy & Regulation in AI Development & Deployment in Insurance

  • Ansgar Koene

    Moderator

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

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    Given the rapid growth of AI deployment, successful implementation of risk-based AI regulations will require AI risk assessments to be conducted at a scale that will be difficult to achieve without some level of automation. The need for automated AI risk assessments is further emphasised by the need to perform post-deployment monitoring.

    In his talk I will present the findings of a survey on AI risk assessment methodologies, outlining commonly identified assessment factors. Based on these survey results I will discuss key challenges and potential approaches towards automation of the AI risk assessments that will be required by risk-based AI regulations.

    Key takeaways:

    risk-based AI regulations will require large scale risk assessments of AI application; AI risk assessment involves evaluation of multiple technical and non-technical risk factors; AI can play an important role in automation of AI risk monitoring.

    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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  • Robert Moorehead-Lane

    Panellist

    Robert Moorehead-Lane - Chief Risk Officer - Aspen Insurance

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    Risk Management Executive with over twenty-five years of financial services experience, delivering risk management solutions within banking and insurance industries across a variety of global jurisdictions. With experience of strategic transformation, risk framework development and implementation and regulatory interventions. Operating at the forefront of risk management developments from a regulatory and business perspective. Experience of Regulatory policy making with the Financial Services Authority during Basel II and with KPMG during the development of Solvency II. Specialist skills include: Enterprise Risk Management development; Solvency and Risk Based Capital framework solution's (Solvency II); Risk Strategy and Profile definitions; Risk Appetite setting and organisational cascade; Risk Information development and delivery; Board Risk training; Development of Risk / Reward strategy and risk diligence during M&A activity.

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  • Janthana Kaenprakhamroy

    Panellist

    Janthana Kaenprakhamroy - CEO - Tapoly

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    Janthana Kaenprakhamroy is the CEO and Founder of Tapoly, winner of Insurance Provider of the Year at the British Small Business Awards 2018 and finalist for both the MGA Initiative of the Year and Technology Service Provider of the Year at the Insurance Times Awards 2021. Tapoly is a digital managing general agent (MGA) providing tailored commercial lines insurance to micro SMEs and freelancers. Tapoly also provides an end-to-end white labelled SaaS solution utilising emerging technologies to connect insurers with their distribution partners across the globe.

    Janthana was named Insurance Woman of the Year at the Women in Finance Awards 2021, was listed by Forbes as number 6 of the Top 100 Women Founders to watch and was named in the Insurance Business UK’s Elite Women List 2021 and 2022. Janthana is a chartered accountant and former internal audit director at top-tier investment banks. Find out more about Tapoly at https://www.tapoly.com/

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  • 12:30

    LUNCH

  • 13:30

    SESSIONS WILL CONTINUE ON THE AI IN FINANCE SUMMIT TRACK FOLLOWING THE LUNCH BREAK

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