Introduction to Data Science in Insurance (C1)

In this introduction of data science in insurance, we discuss data analysis and data sources and provide an overview of some data science techniques, before touching on the ethical considerations in data science and giving examples of the application of data science in insurance.

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Introduction

If you’re looking for a high-level understanding of data science, this course is ideal for you. An individual subscription gives you 3 months’ online access to:

  • Course materials
  • Discussion forums to engage and collaborate with like-minded individuals
  • Option to ask tutors questions through forums and Q&A sessions
  • On-demand access

As Well As

Our Data Science Resource Library which features Actuartech and Industry specific curated additional content to assist you on your data science journey

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Pick from any of our introductory or advanced courses with bespoke insurance and actuarial specific case studies.

Our platform is easy to use and embeds the coding environment and learning material in one place to enable you to apply data science hands-on.

We provide case studies and projects relevant to actuarial work, and based on relevant datasets provided. You have the option to interact and network with your peers.

Overview

In this training module, we introduce the use of data science in insurance on a conceptual level. This course aims to introduce individuals to the advantages of using data science and to expose individuals to certain data science techniques as well as data science risk management.

We discuss the main aims of data analysis and why it is valuable through the use of examples and we consider the various sources and types of data. Thereafter, we address data science techniques as well as the ethical issues that surround them.

We conclude with examples of the application of data science in insurance.

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Introduction to Data Science in Insurance

Sign up for a free preview of this introductory course in R and python

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£50 once-off (3-month access)

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Course Structure

In Chapter 1, we introduce data science by looking at the origins and definitions of data science.

Chapter 2 sees us exploring data science within the insurance context.

In Chapter 3 we discuss the data science pipeline.

In Chapter 4 and Chapter 5 we evaluate the various different sources and types of data.

In Chapter 6 we look at data science techniques whilst focussing on modelling.

Chapter 7 sees us discussing specific data science considerations, including ethics and explainability.

In Chapter 8 we address specific use cases within an actuarial context.

Chapter 9 concludes the course and The Appendix offers students further resources

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Who's this course suitable for?

  • Individuals and teams looking for a high-level understanding of data science.
  • Individuals and teams looking to find out how data science can improve their operations.
  • Individuals and teams working alongside data scientists.
  • Individuals and teams wanting to find out how data science can be applied in an insurance context.

Why is this topic important?

  • Data science isincreasingly being used for insurance applications.
  • An understanding of data science can improve collaboration amongst data scientists and actuaries.
  • Understanding data science can lead to an increased awareness of data management and expose new ways of using data.

Short note to say really enjoyed today’s webinar. It had a very clear message. […] fully in agreement with the comments that it is imperative we maintain our professional and ethical stance at all times if we want to continue to be trusted and relied on.

Webinars

I just wanted to say what an interesting presentation that was. Thank you so much for taking the time to put this on for us, it is very much appreciated by all – especially the flexibility around hosting as a webinar instead of the original [in-person] format. It worked very well indeed!

Webinars

I think I’m [one of the first actuaries in my area] who are pointing towards Data Science, creating the new [role] of Actuarial data Scientist. For this reason i [sic] decided to follow a post graduate master in Business Intelligence and Big data analytics. I'm actively following your company and i [sic] think it is one of the best Actuarial consulting company [sic] who [sic] is pointing towards data Science!

Webinars

I love your videos - being free and accessible really helped me. The Q&A session was fantastic! It always comes down to execution and I feel this should always accompany your presentations - answering the question of how will your participants use what you give them. Keep up the great work!

Round Table

Thank you for having me along. I really found it the most motivating conversation I’ve had in a while, and made me think about what I’m trying to achieve within this area. We all need evenings like that to get some perspective on what we *think* is going on and what actually is. It was a very good evening.

Round Table

It was a really good introduction to Data Science and afterwards I felt that I now have a platform that I could use to further my understanding in this area.

Webinars

I am really happy to have been part of the talk. It was very insightful and please keep doing more of this. I am a data science student currently but I have an actuarial background. I worked in life insurance for about 5 months before resigning to do my masters in Data science so that I blend the actuarial world and Data science together. The talk gave me perspective. Even suggested some potential topics for my Thesis.

Webinars

Short note to say really enjoyed today’s webinar. It had a very clear message. […] fully in agreement with the comments that it is imperative we maintain our professional and ethical stance at all times if we want to continue to be trusted and relied on.

Webinars

I just wanted to say what an interesting presentation that was. Thank you so much for taking the time to put this on for us, it is very much appreciated by all – especially the flexibility around hosting as a webinar instead of the original [in-person] format. It worked very well indeed!

Webinars

I think I’m [one of the first actuaries in my area] who are pointing towards Data Science, creating the new [role] of Actuarial data Scientist. For this reason i [sic] decided to follow a post graduate master in Business Intelligence and Big data analytics. I'm actively following your company and i [sic] think it is one of the best Actuarial consulting company [sic] who [sic] is pointing towards data Science!

Webinars

I love your videos - being free and accessible really helped me. The Q&A session was fantastic! It always comes down to execution and I feel this should always accompany your presentations - answering the question of how will your participants use what you give them. Keep up the great work!

Round Table

Thank you for having me along. I really found it the most motivating conversation I’ve had in a while, and made me think about what I’m trying to achieve within this area. We all need evenings like that to get some perspective on what we *think* is going on and what actually is. It was a very good evening.

Round Table

It was a really good introduction to Data Science and afterwards I felt that I now have a platform that I could use to further my understanding in this area.

Webinars

I am really happy to have been part of the talk. It was very insightful and please keep doing more of this. I am a data science student currently but I have an actuarial background. I worked in life insurance for about 5 months before resigning to do my masters in Data science so that I blend the actuarial world and Data science together. The talk gave me perspective. Even suggested some potential topics for my Thesis.

Webinars
Get started

Introduction to Data Science in Insurance

Sign up for a free preview of this introductory course in R and python

Free Preview

Preview

£50 once-off (3-month access)

Enroll Today

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