This working party will conduct a systematic review of AI applications in actuarial science, leaning towards practitioner's perspective. The aim of this study would be to investigate whether the pricing/reserving/capital (actuarially driven departments in insurance companies) could improve their output through the use of AI-based tools and why. Both cases, where AI does not bring satisfiable results that would justify disruption and the converse should be examined, yielding a clear view of the direction of the actuarial profession. 

Chair: Karol Gawłowski 

Established: 2023

Published Content:

• The Actuary article: Gladiators, ready! Pricing models fight it out
  

neural networks

AI

Data Science

An online webinar delivered by John Taylor, immediate past-President of the Institute and Faculty of Actuaries. Despite long-running concerns that innovation could lead to widespread redundancy, technology has enabled greater productivity, created higher-value jobs and spurred us on to new heights. With artificial intelligence increasingly automating work undertaken by professionals, I look at the prospects for the actuarial profession in the era of unprecedented technological innovation. Whilst this “double-edged sword” will see some traditional actuarial tasks being automated, I contend it will create more opportunity for actuaries to contribute to a broader range of important issues such as climate change and consumer finances. Moreover, the prevalence of data provides a platform for actuaries to make a difference outside the traditional sectors of insurance and pensions.

Artificial Intelligence is heralded as a game-changer to the ways industries use data, with the insurance industry especially looking to embrace these new technologies. This brings many questions – not least around data privacy, ethics, potential biases and so on – with regulators increasingly interested in developments.

Moreover, whilst the stunning progress of specific technologies such as Watson and Alphazero made headlines some years ago, current commercial applications of AI remain far from mature.

Our two speakers from leading reinsurer Munich Re will share their experiences on both these areas. Frank Schiller will cover the conceptual framework needed for good governance, and Abhijit Pal will talk through some of the practical challenges of implementing AI to solve business problems.

For actuaries and data scientists this webinar will cover key current considerations in this important and exciting field.

Speakers: Dr Frank Schiller and Abhijit Pal, FIAI, FIA

Now that AI has arrived, it is time to consider how we can harness its power and incorporate AI into our jobs every day. Over the past year, ChatGPT has become synonymous with AI and new tools are being released all the time. The pace of innovation is moving at an incredible speed. Please join us in this session with Sally Bridgeland and Stuart Breyer where we: 

• go back to basics and discuss where AI works, and where it does not 

• explore the practical applications to our sector and respective businesses 

• discuss the ethical considerations in AI development 

• debate the role of governance and risk management with AI

Within modern society, artificial intelligence has long been a part of human innovation. Its increased prevalence in recent years has rocked society and captivated global interest. Many are now suggesting that the growth of AI is heading towards an inflection point. It could be capable of producing a technological renaissance akin to the rise of the internet or the splitting of the atom. But what does the rise of AI mean for the actuarial and wider financial services sector? Our thought leadership webinar series addresses this question. We draw on expertise from the worlds of policy, science, academia, and financial services to demystify AI and its growing role in society. We tackle the big debates around AI ethics and regulation and set out the work the IFoA is doing in this space. In the fourth and final webinar, we take a deep dive into what the increased prevalence of AI means for actuaries and their work. Both now and in the future. 

Speakers Matthew Edwards, Atreyee Bhattacharyya, Catherine Drummond and Dr. Alexey Mashechkin

Within modern society, artificial intelligence has long been a part of human innovation. Its increased prevalence in recent years has rocked society and captivated global interest. In fact, many are now suggesting the growth of AI is heading towards 

Speakers

Dr Cosmina Dorobantu, Matthew Edwards, Dr Florian Ostmann, Helene Panzarino and Andrew Strait

Within modern society, artificial intelligence has long been a part of human innovation. Its increased prevalence in recent years has rocked society and captivated global interest. Many are now suggesting the growth of AI is heading towards an inflection point. It could be capable of producing a technological renaissance akin to the rise of the internet or the splitting of the atom. But what does the rise of AI mean for the actuarial and wider financial services sector? Our new thought leadership webinar series addresses this question. We draw on expertise from the worlds of policy, science, academia, and financial services to demystify AI and its growing role in society. We tackle the big debates around AI ethics and regulation and set out the work the IFoA is doing in this space. In the third event of the series, we are joined by IAA President Charles Cowling, who will lead a discussion on: how the actuarial sector is reacting to AI developments globally how different jurisdictions are approaching this challenge 

Speakers Charles Cowling, Bogdan Tautan, Fei Huang

Within modern society, artificial intelligence has long been a part of human innovation. But its rapid advancement and increased prevalence in recent years has captivated global interest. In fact, many are now suggesting the growth of AI is heading towards an inflection point capable of producing a technological renaissance akin to the rise of the internet or the splitting of the atom. But what does the rise of AI mean for the actuarial and wider financial services sector? In our new thought leadership webinar series, the IFoA will seek to address this question. We will draw on expertise from the worlds of policy, science, academia, and financial services to demystify AI and its growing role in society. The series will seek to tackle the big debates around AI ethics and regulation and set out the work we as an organisation are undertaking in this space. In the first event of the series, we will be joined by Felicity Burch, Executive Director of the Centre for Data Ethics and Innovation. Felicity will deliver a keynote presentation focusing on exploring AI, by explaining what it is, the latest development in its capabilities, and where it is being used across society and financial services.

Events of the last five to 10 years have inhibited the British state’s ability to plan for and deliver ‘good’ long-term policy. From the UK’s departure from the European Union to COVID-19 and the war in Ukraine, the UK government’s capacity to think beyond a typical parliamentary term has been severely hampered. This isn’t a party-political criticism, nor a slight on our dedicated civil servants. It is an assessment of the various structural and behavioural barriers that prevent longer term thinking in our politics. As experts in long-term risk management, the actuarial profession is advocating a return to long-term policymaking. Last autumn we published our policy prospectus Beyond the next Parliament, to suggest ways in which government and others can take an alternative approach to ensure a longer time horizon is considered in the policymaking process. As part of this campaign, the IFoA hosting a three-part webinar series, focusing on the key policy areas addressed in the prospectus. In the second event of the series, we will focus on how the UK can seize the longevity dividend. Advances in medical care and living standards means the population is living longer, but is the UK equipped to deal with the policy challenges this brings? That’s the topic our pensions and social care experts will debate. 

Speakers 

David Sinclair

Catherine Foot

Anna Brain

Debbie Webb 

Chair: David Heath

Part of the Current Issues in Life Assurance (CILA) 2023 Webinar Series We will consider how AI has been, and can be, used in the context of life and non-life insurers, as well as wider fields. We look at how ‘large language models’ work and their strengths and weaknesses. We will illustrate the use of this technology with the following use cases: IFRS 17 and AI – information search tool New AI coding assistant for actuaries How to prevent another global financial crisis. We will also consider WTW’s response to the recent consultation on AI in financial services.

Have you ever wondered how to introduce change and encourage a culture of continuous improvement within your organisation? In this talk, we will discuss just that. The session will focus on three key areas: Real-life case studies from the industry – to give you some examples of transformative changes made by actuaries to large organisations, along with some tips and tricks to influence strategy, explore and implement new technology and really make a difference A view on the “operating model of the future” – including some views on how IT, Change and Finance functions can better work together to support strategic change and improve BAU processes Innovation insights – we will discuss our own experiences in developing a team of technology-enabled actuaries within our organisation, and how we go about developing and supporting a culture of continuous improvement and innovation. 

Speakers: Will and Sian lead the UK Actuarial Technology offering for EY. This offering has three core focuses – actuarial modelling support (vendor-based), development of bespoke open-source solutions and research & development to identify new trends / offerings (including AI). They regularly bring new ideas and solutions to the insurance market in order to address a wide range of challenges, while also bringing their teams and clients along on the innovation journey. For example, since mid-2022 they have overseen the delivery of 600+ man-hours of actuarial technology training. Alongside this, they have successfully delivered a wide range of projects, from various tooling developments to some of EY’s largest actuarial transformation projects, and have supported clients with embracing cultural change in each of these.

This working party will: 

Co-chairs: George Tzougas and Debashish Dey 

Established: 2022

Published Content:

• Part 1 - Introductory analysis of S&P Green Bond Index
  
• Classification of climate-related insurance claims using gradient boosting
  
• Blog post: Time series analysis of S&P Green Bond Index
  
• Time series analysis of GSS bonds Part 2 – Further univariate analysis of S&P Green Bond Index
  

Data science

sustainability

climate change

green bonds

• Actuaries in Data Science - reflections from the panel webinar
• Data Science and AI cutting through the hype and doing right webinar
• Actuaries Embracing Data Science webinar
• Pathway for Actuaries into the field of Data Science webinar
• Driving true customer value at Prudential Financial webinar
• Machine Learning Actuaries webinar
• Data Science Health Care: Leveraging Big Data in Predictive Modelling webinar
• Data Visualisation as a powerful means of communication webinar
• Machine Learning for Actuaries webinar
• Emerging risk actuaries, artificial intelligence and the Board webinar
• Advanced 'Big Data' Analytics for mortality webinar
• Training a neural network to fit curves to claim data webinar
• Case Studies in Machine Learning and AI webinar
• Data Science Ethics Discussion webinar
• The use of predictive analytics to enhance life insurance portfolio management webinar
• Predicting the probability of a severe bodily injury in a car accident webinar
• Risk Pricing with XGBoost webinar
• You Can Code Your Own Way: Building Data Science Capability in Risk webinar
• Re-think not re-write webinar
• Data Science and Machine Learning meets Mortality Modelling paper
• A Neural Network Extension of the Lee-Carter Model to Multiple Populations paper

This working party will conduct a systematic review of AI applications in actuarial science, leaning towards practitioner's perspective. The aim of this study would be to investigate whether the pricing/reserving/capital (actuarially driven departments in insurance companies) could improve their output through the use of AI-based tools and why. Both cases, where AI does not bring satisfiable results that would justify disruption and the converse should be examined, yielding a clear view of the direction of the actuarial profession. 

Chair: Karol Gawłowski 

Established: 2023

Published Content:

• The Actuary article: Gladiators, ready! Pricing models fight it out
  

neural networks

AI

Data Science

This working party will investigate tools and packages available to perform data visualisation and produce outputs that conform to best practice in the area. 

Chair: Stephen Windell 

Established: 2020

Published Content:

• Data Visualisation in Insurance presentation: Malgorzata Smietanka
  
• Python for Excel GitHub article
  

Data science

visualistion

libraries 

Data science

visualistion

python

excel

What are the advantages of using artificial intelligence (AI) in investing? What are the differences between traditional quant and AI? This new webinar discusses challenges and the future of AI in the investment sector.

Speakers Daniel Philps, CFA PhD, Head of Rothko Investment Strategies, and Raj Shah FIA, Assistant Portfolio Manager at Rothko Investment Strategies, will look at:

• The difference between applying AI versus traditional quant investing
  
• Where in the investment process AI can be used
  
• How do we overcome inconsistencies in data via intelligent cross validation and error correction
  
• Intelligent trading (reinforcement learning) and extracting alpha
  
• What is the next generation of artificial intelligence and how do we look deeper into continual learning.

Moving from expert to leader can be tough, especially when your expertise is all about data-driven decision making. Please join us in this session with Richard Galbraith and Clive Elwood. They will cover the biology of emotions and the importance of building emotional intelligence for leaders. Our panellists will share their experiences as technical experts, leaders, and coaching practitioners. They will explore ways in which we can all improve this aspect of our leadership.

Speakers:

Clive Elwood

Richard Galbraith

Nozipho Gazi

This presentation will involve a comprehensive quantitative analysis of how the AI risks landscape could change drastically in the future.

We will help attendees understand how we can map probability. We’ll also explore the severity of AI-related loss incidents currently and over the next decade, due to risks like data bias, cyber incidents and algorithmic and performance-related issues. Participants will gain insights on how re/insurers can help mitigate some of these risks.

This is a novel approach towards understanding AI risks. Techniques used in different parts of the analysis include text processing, ensemble learning and regression.

Target audience and assumed knowledge level: No specialist knowledge is required.

Speaker and company: Mitali Chatterjee, Swiss Re

Analytics and machine learning methods are common in personal lines pricing. Less so in commercial lines, where the application, use and potential is varied and, currently, largely untapped.

Join this session on commercial lines analytics to explore the potential of varied applications, with the aim of significantly enhancing the efficiency and accuracy of processes across the insurance value chain.

During the session, attendees will be:

• introduced to a series of AI and machine learning use cases used to enhance various processes within commercial lines, from data ingestion and pricing to risk management and reserving
• explore some of the methods, research and findings from the Actuarial Science Data Science Working Party and GenAI Working Party
• gain insights from a variety of perspectives, including insurer, MGA, Insurtech and consultancy

Target audience and assumed knowledge level: No specialist knowledge required.

Speaker and company: 

Betty Zhu, Akur8
Bijal Patel, Aurora
Karol Gawlowski, Allianz Global Corporate & Specialty
Bruno Bécha, Akur8

Pragmatic Reserving Working Party:

Wrap-up and next steps

Alessandro Carrato and Markus Gesmann

16 June 2015

Contents

1. Wrap-up: The Ultimate View of Reserve Risk

2. Next Steps: 1yr View and Reserving with R

Update from the PPO Working Party

Emma Potter – Towers Watson

Deputy Chair of PPO Working Party

Presentation to General Insurance Reserving Seminar 2015

18 June 2015

Agenda

• Reserving methodology

• Propensity

• Introduction of Irish PPOs

Event Paper: GIRO 2022: D5 Understanding AI - eXplainable AI (XAI) techniques in practice

Agenda

1. ICE – Individual Conditional Expectation 

2. PDP – Partial Dependence Plot 

3. ALE – Accumulated Local Effects 

4. XAI in 

5. SHAP – Shapley Values 

Federated learning is a new method of training machine learning models pioneered by Google in 2016 for use on smartphones. This concept enables the direct training of machine learning models on users’ devices, eliminating the need to share or transfer potentially sensitive data to a centralized server.

Unlike traditional machine learning methodologies, federated learning adopts a model where the algorithm is brought to the data, rather than transferring the data to the algorithm.

In this presentation, the Federated Learning Working Party (part of the IFoA Data Science Research Section) will illustrate how insurers can leverage this technique.

We will show how companies can collaboratively develop a neural network model to predict claims frequency. This collaboration allows for the combination and utilization of their customer data without sharing or compromising any sensitive information. This maintains data privacy while building an AI model. We achieve this using the Flower and PyTorch packages in Python.

We will cover the basics of how federated learning uses a unique form of encryption that enables modelling without the need to see sensitive data, using simple, easy to follow examples.

Target audience and assumed knowledge level: No prior knowledge of federated learning necessary. Some familiarity with claims frequency and neural network modelling is assumed.

Speaker and company: Dylan Liew, BUPA, Malgorzata Smietanka, UCL, Michelle Chen, AIG

Event Paper: TIGI 2019: Machine Learning: Now and in the Future

Andy Rigby & Renaud Million

Keywords: Core competency, modelling, modelling application, data, process, risk, drone, smart homes, technology

Event Paper: TIGI 2019: Machine Learning: “Pricing” the Way Forward

Navarun Jain Actuarial Analyst Lux Actuaries & Consultants Dubai

Machine Learning – The Concept Gradient Boosters 

• Decision Trees 

• How Gradient Boosting works Artificial Neural Networks 

• Structure and Architecture 

• How ANN’s Work and Learn What does it mean to “learn”? 

• Gradient Descent Applications to Insurance Data Interpreting Machine Learning Models 

• Measuring Feature Importance 

• Finding Variable Interactions

Event Paper: TIGI 2019: Pricing Workshop – Overview and Practical Applications of Machine Learning Methods in Pricing

Bethan Faultless & Matthew Lambert

• Context of machine learning in pricing
• Decision trees • Random forests
• Gradient boosting machines 
• Practical applications of ML techniques
• Conclusions

The aim of this working party is to: 

 Chair: Malgorzata Smietanka 

Established: 2020

Published Content:

• The Actuary: Pieces of the technology puzzle
  
• SSRN Paper: Federated Learning for Privacy-preserving data access
  
• Insurance: Collaboration without compromise
  
• All together now: modelling claims using federated learning
  
• Federated Learning: Collaboration with no compromise
  
• Application of Federated Learning in Predictive Maintenance to Predict Remaining Useful Life
• Splitting dataset for federated learning

There has much discussion around the world in the last few months, in various forums and in the media, about the use of generative AI. Some see clear opportunities for its use as a controllable tool across different professions. Others see major potential legal, reputational, and societal risks associated with it, particularly in the case of corporate reporting. Please join us for a lively debate on this topic with Claire Bodanis and Zhixin Lim. Claire Bodanis is Director of Falcon Windsor Ltd. She is a corporate reporting and communications specialist and author of ‘Trust me, I’m listed’. Zhixin Lim is Actuarial Head of Projects at HSBC. He has a passion for AI and tech and recently published the article ‘master the genie’ in The Actuary magazine. The webinar will be chaired by Richard Galbraith, Director of ERM at Canada Life. Richard is an actuary and an executive coach.

The GenAI Working Party aims to explore, research, and provide guidance on the application of Generative AI in the fields of actuarial science, insurance, and finance. It seeks to assess the impact of AI on the industry, promote best practices, and develop strategies to leverage AI technologies for enhancing decision-making processes.

Chairs: 
Lei Fang
Betty Zhu
Daniel Ramsay

Established: 2024

In the ever-expanding world of data science, machine learning, and AI, actuaries have access to unprecedented modelling power and opportunities for efficiency in their work. 

But could actuaries be responsible for the next big data privacy scandal? Is following the letter of the law enough when it comes to AI? Just because you can, does it mean you should? 

Using real examples and case studies, the Data Science Community – Professionalism, Regulation and Ethics Working Party explores the ethical use of these tools and talks through some of the regulatory and professional obligations actuaries should consider before embracing them. 

Speakers: Murray Lidgitt, Hymans Robertson; Hazel Davis, Sabre

The IFoA GI Insurtech Working Party has been carrying out research focused on the four main technologies driving innovation in insurance: IoT devices and sensors; video, image and audio processing; blockchain and parametric solutions; AI, big data and robotic process automation. 

We would like to present the findings to GIRO, including: 

• An overview of each technology 
• The applications to insurance 
• Data and analytics 
• The impact on actuarial work and opportunity 
• Examples of actual use cases 

Speakers: Ed Plowman, Cherry Chan and Harjit Saini

In the ever changing fast-paced world of Artificial Intelligence, we look to  shine a light on the opportunities for Actuaries to expand their knowledge, network and keep ahead of the latest trends.

This Hot Topics page will be regularly updated over 2024/2025, with new content items added.

"We will explore key issues and challenges in AI risk management from an actuarial perspective, based on discussions and outcomes from a transregional industry focus group. We will define the gaps and challenges faced when it comes to implementing and utilising modern modelling techniques from a risk-perspective, in the context of regulation, and discuss best-practice guidelines: 

An overview of key issues related to data science and AI regulation and risk management Industry examples of the key modelling issues in traditional and non-traditional actuarial work Best practice and practical tips for AI risk management 

Speakers: Valerie du Preez, Dupro Advisory Actuartech; Richard Galbraith, Canada Life"

Life Conference 2020, featuring the following sessions:

• 2030 – a view from the future - lessons in resilience and climate change risk management
• Covid-19 – where are we now? A medical and an actuarial perspective
• IFRS 17: So far, but we have another year to 2023!
• Recent CMI activity: Implications of COVID-19 for future mortality
• Shining a light on the “black box” of price optimisation
• Part VII transfers in the current environment
• Onboarding With-Profits: All in to last out
• GBP inflation & the RPI curve: A tale of two halves
• AI in an actuarial world: training a machine to assess matching adjustment eligibility
• With-Profits - current areas of focus: A panel discussion
• Sustainability and climate change: I’d like to help – but I’m an actuary
• An alternative take on how to be 'professional'
• Changes in insurers investment strategies
• Weathering the Climate storm - creating an enhanced disclosure and climate scenario testing
• IFRS17 – how do we explain ourselves better? Tackling analysis of change
• The greatest threat to with-profits
• International Capital Standards - an Equity Analyst’s views on ICS and current solvency/capital
• Assessing Model Drift – Do internal models accurately reflect the risks that UK life insurers face?
• ESG and climate change integration – the journey for life insurers
• Application of machine learning techniques to financial reporting
• What's a 1-in-200 year stress when you're in a market downturn?
• Integrating ESG into long-term strategic asset allocation

This session will illustrate the transformative potential of generative AI. It will do this through a range of concrete AI use cases, showcasing a wide range of powerful applications seen in this field. Most discussion of large language models (LLMs) focuses on their ability to write essays or computer code, which is impressive but less relevant to actuaries. Instead, this session will examine how LLMs can be augmented with insurance domain knowledge and be integrated into processes to accelerate actuarial modelling and financial reporting. This presentation will build on earlier versions presented at CILA and the Society of Actuaries, Ireland, with a wider range of practical insurance-related use cases. It will outline the workings of the LLMs that underlie tools like ChatGPT and Github Copilot. Given the rapid advances in this field, it will also provide an update on other leading AI models advances (that is, ‘non-ChatGPT’ models). It will discuss the pros and cons and potential future capabilities of these models. The agenda will cover: introduction to LLMs; AI use cases; expert systems; documentation generation; writing code; model translation; what’s new in 2023 ‘Q3.5’?

Speakers: Matthew Edwards, Daniel Ramsay, and Arlen Galicia Carreon, WTW

This panel discussion will explore key issues and challenges in AI risk management from an actuarial perspective based on discussions and outcomes from a transregional industry focus group. The session will define the gaps and challenges faced when it comes to implementing and using modern modelling techniques from a risk-perspective, in the context of regulation. They will also discuss best practice guidelines and how to take a practical approach to AI risk management. Practical outcomes include: an overview of key issues related to data science and AI regulation and risk management from an actuarial perspective; industry examples of the key modelling issues in practice in traditional and non-traditional actuarial work; best practice guidelines for data science and AI risk management; practical tips for data science and AI risk management; This discussion is aimed at participants who are looking to implement AI or data science within their functions or looking to improve their risk management in these domains. No prior technical knowledge on the topic is required. Research findings from the working group is available on request at info@actuartech.com. Comments on the panel discussion are invited either before or during the session.

Speakers: Valerie duPreez, Dupro Advisory Actuartech, Richard Galbraith, Canada Life, Charles Cowling, Mercer, Perry Thomas, Chair of the AI Ethics Working Party, Kalpana Shah, IFoA President-elect

To support membership engagement and events on data Science topics. 

Key objectives

Chair: Alexey Mashechkin

Published content:

• Webinar: Actuaries in data science
• Article: The data science process (28 August 2019)
• Article: Statistics vs Machine Learning (5 September 2019)
• Article: Fitting data with XGBoost (11 October 2019)
• Paper: What Makes a Data Scientist? Author: Alex Labram

This working party will conduct a systematic review of AI applications in actuarial science, leaning towards practitioner's perspective. The aim of this study would be to investigate whether the pricing/reserving/capital (actuarially driven departments in insurance companies) could improve their output through the use of AI-based tools and why. Both cases, where AI does not bring satisfiable results that would justify disruption and the converse should be examined, yielding a clear view of the direction of the actuarial profession. 

Chair: Karol Gawłowski 

Established: 2023

Published Content:

• The Actuary article: Gladiators, ready! Pricing models fight it out
  

In today’s rapidly evolving digital landscape, some actuaries are increasingly leveraging AI tools such as ChatGPT, Copilot, and Bard to enhance their work. While these tools offer numerous benefits, including increased efficiency and accuracy, they also introduce new risks that must be carefully managed. In this webinar, our guest speaker Jeremy (Jez) Bassinder, Watson X and Generative AI Leader for UK and Ireland at IBM, aims to provide some practical guidance for actuaries to safely and effectively use AI tools in their practice. Agenda: Understanding and mitigating risks associated with public AI tools Ensuring high-quality output when using AI Effective governance of AI tools IBM’s approach to AI tool governance Q&A session (20 minutes) This webinar is promoted by the AI Ethics Risks Working Party of the IFoA’s Risk Management Research and Thought Leadership Committee. Perry Thomas is Chair and Jerome Nollet is Deputy Chair. It is important to note that neither the IFoA nor any of its members or parties endorse any software, tools, or products that may be discussed or presented during the webinar. 

Speakers Jez Bassinder, Perry Thomas and Jerome Nollet

How we communicate ourselves and engage with others at work is key to professional success; we do not work independently of others. Please join us in this session led by Joanna Gaudoin, where we will look at: • what personal impact really is • why it matters • the key ‘tools’ you have to improve it to build better relationships at work – for both the short and long term You will leave the session with practical tips you can put into practice. Joanna Gaudoin (MD, Inside Out Image) spoke at our popular past webinar ‘Skills to future-proof your career’ (6 November 2023), covering a number of key skills. She is kindly leading this follow-up session to cover the personal impact topic, which appeared to create a great deal of interest in the audience.

Sir Adrian Smith will outline how advances in data science, machine learning and artificial intelligence in the world of big data will transform the nature of many industries, including financial services. The broader environment within which mathematics is applied will change rapidly, often led by innovative yet disruptive forces outside. These changes will undoubtedly have an impact on the work of actuaries - and the profession will need to adapt quickly to thrive. Actuaries are well-placed to consider the long-term implications of a world in which data technology informs not just traditional actuarial sectors of insurance, pensions, risk, investment and healthcare, but also to drive policy decisions to address broader societal challenges. Sir Adrian will encourage the profession to step out of its traditional areas of strength, with a more ambitious mindset, to take advantage of the opportunities that these sweeping changes will provide. This is not just about embracing the skill sets which are required in the digital world; a whole new mindset and reinvention are necessary. There is also a heightened need for leadership to identify and develop the appropriate talent for new, emerging roles. Given the IFoA’s public interest perspective, the debate is not just about innovation in data technology but must include fostering trust in data through good ethical practice. Sir Adrian will also speak to the profession’s responsibilities in the ethical implementation of data science and the need for new standards, regulation and transparency to protect society in this new world. John Taylor and Marjorie Ngwenya will join the session as panellists. John will focus on the links between data science, AI and the IFoA's Great Risk Transfer work, and Marjorie will debate how the profession ensures that existing and new technologies work to the benefit and purpose of people.

Recent advances in large language models (LLMs), such as GPT-4, have spurred interest in their potential applications across various fields, including actuarial work. This paper introduces the use of LLMs in actuarial and insurance-related tasks, both as direct contributors to actuarial modelling and as workflow assistants. It provides an overview of LLM concepts and their potential applications in actuarial science and insurance. In this webinar, we will: explore the main elements of this paper: what LLMs are and their uses including 2 case studies close off on a discussion of risks and new developments since writing

Given the increasing focus on water risks, the International Actuarial Association have convened a task force to provide appropriate guidance to the actuarial profession. Following the publication of the first paper “Sink or Swim: An actuary’s guide to water risks” this webinar will cover the current and future risks of water to the actuarial profession. 

Speakers Emily Forsyth-Davis, Sara Goldberg, Hayley Clarke and Lylah Davies

Statistical Learning in Actuarial Applications The aim of this research is to construct highly flexible actuarial models such as: 

Chair: George Tzougas 

Established: 2020

Published Content:

• Bivariate Mixed Poisson Regression Models with Varying Dispersion
  
• The multivariate mixed Negative Binomial regression model with an application to insurance a posteriori ratemaking
  
• A first-order binomial-mixed Poisson integer-valued autoregressive model with serially dependent innovations
  
• Applying Analytics in Embedded Insurance
  
• EM Estimation for the Bivariate Mixed Exponential Regression Model
  

Data Science; Statistical learning; poisson; regression; models Data Science; Statistical learning; Data Science; Statistical learning; Poisson; models Embedded insurance; data science; anaytics Data Science; Statistical learning; bivariate, regression

Experiment with methods including feature engineering and data management to improve supervised learning model prediction accuracies. 

Chair: Neptune Jin 

Established: 2020 – 2023

Published Content:

• Modular Framework of Machine Learning Pipeline
  
• Differential Privacy and Fairness in Automated Decision Making
  
• Examples of Potential Actuarial Applications
  

Data science; machine learning; actuarial control cycle Data Science; automated decision making Data Science; models; applications

Join us for an insightful webinar hosted by the Mental Health Working Party. This session aims to explore the potential value of digital mental health tools in life and health insurance. This meeting will be chaired by Lisa Balboa who co-leads the working party. We have on our panel 3 digital mental health providers: Thrive, Headspace Health, and Dialogue. They will be joined by Dr Tarun Gupta, Chief Medical Officer of L&G, adding a wealth of clinical experience to the discussion. This session is about understanding the impact and value of these digital tools in the insurance value chain. It offers insights into some of the different types of providers and the value digital mental health tools can provide in life and health insurance. Our panellists will bring this topic to life with real-world examples and insights, making it a practical and interesting discussion. Dr Gupta will also provide his first-hand clinical experiences with such tools. The session will conclude with an interactive Q&A, providing you with an opportunity to engage directly with our experts. 

Chair: Lisa Balboa. 

Speakers: Frank Cheung, FSA, MAAA, Tarun Gupta, Martin Jervis, Simon Miller and Wendy Rose

Machine Learning: Now and in the Future

Andy Rigby & Renaud Million

25 April 2019

• Machine learning has now become “mainstream” 
• But current applications limited: – Pricing (risk and retail/behavioural) Reserving
• Looking at other industries and emerging trends, applications could be much wider 
• A whistle -stop tour through other applications to show both potential benefits and risks/challenges:
  • Core competencies 
  • Non-core competencies

The aim of this presentation is to present the potential and latest advances of GenAI in streamlining life & health underwriting and claims processes. These processes currently involve a large manual effort for a significant proportion of customers, as the risk is often controlled by reviewing unstructured medical evidence. GenAI enables much more effective and accurate automated analysis of evidence, compared with pre-existing technologies. The presenters will also explain why they believe that GenAI solutions will become a commodity and why our underwriting and claims teams need to shift their knowledge and expertise to make the most of GenAI solutions. Underwriting and claims expertise will become essential in helping to build solutions (e.g. through prompt engineering) and in using them effectively in daily operations (e.g. case summaries and auto-decisioning).Presenters will also introduce the tech behind AIssistant, a GenAI solution already live and built by SCOR teams, which helps streamline our underwriting and claims operations. 

Speakers Antoine Ly, Chief Data Science Officer, SCOR | Debbie Bolton, Remark Group

The Southampton Data Science Academy and the IFoA present:

Why data science and AI needs us more than ever

Speakers: Dame Wendy Hall, DBE, FRS, FREng (keynote), Melanie Zhang FIA, Stuart Coleman SDSA, Colin Thores IFA, IFoA

The aim of this working party is to: 

Chair: David Bennett 

Established: 2017

Published Content:

• All clear: How Shapley values make opaque models more transparent
  

Data Science; Statistical learning; poisson; regression; models Data Science; Statistical learning; Data Science; Statistical learning; Poisson; models Embedded insurance; data science; anaytics Data Science; Statistical learning; bivariate, regression