Lapse Experience Analysis in R (R2)

Discover how to use advanced techniques in R, including fitting regression and classification machine learning models, data cleaning, feature engineering, preliminary visualisations, and reporting to investigate lapse rates in this end to end walkthrough.

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Introduction

If you’re looking to learn how to utilise advanced applications of R in an insurance context, this course is ideal for you. An individual subscription gives you 3 months’ online access to:

  • Coursematerials
  • A personal coding environment through Jupyter Notebooks
  • Discussion forums to engage and collaborate with like-minded individuals
  • Instructional videos
  • Option to ask tutors questions through forums and Q&A sessions
  • Hands-on practical examples linked to actuarial work
  • 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.

You can also request to access toa coding project to practice the skills you learn in this course.

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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

This course serves as an end-to-end walk-through of an investigation into lapse rate analysis through applying machine learning techniques using the R programming language. The aim of using machine learning techniques is to better understand our data, the key drivers behind lapse rates, and how various models can be fitted and their performance compared. We guide the student through importing, cleaning, investigating, modelling, visualising, and interpreting data using interactive Jupyter notebooks.

This course is structured as a case study to help you, the student, better understand machine learning techniques and how they may be applied to a business context. The goal is not to provide a model that can be copied and applied to any situation, but rather to teach you how to apply machine learning techniques.

We will demonstrate, with the use of a practical case study, how the full cycle of actuarial analysis is evolving, from data collection and data enhancement, feature engineering, modelling, verification, and ultimately application & communication.

The case study also provides an introduction to regression modelling using standard techniques and more advanced machine learning with application to insurance.

If you're not already familiar with R, we recommend that you start with our Foundations in R course.

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Lapse Experience Analysis in R

Sign up for a free preview of this advanced R case study

Free Preview

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£150 once off (3-month access)

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Course Structure

Chapter 1 of the course serves as an Introduction to the course, discussing the implications of lapses on insurance companies and the dataset that will be used.

Chapter 2 is on Problem Specification, covering the business context and the techniques available. It also offers an exploratory overview of the data and discusses external libraries and packages that we will be using.

Chapter 3 covers Data Management, which includes a preliminary analysis and feature engineering to reduce dimensionality of the data and make the data more suitable for model fitting.

Chapter 4 is Model Building, in which we fit various regression models to determine whether or not an individual will lapse.

Chapter 5 is the Reporting chapter which reports on the findings of the model fitting stage by analysing and comparing the results of the various models fitted, and in which we discuss the key factors driving lapses.

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Who's this course suitable for?

  • Individuals with a good grasp of the fundamentals of R.
  • Individuals unfamiliar with tree-based modelling techniques.
  • Individuals with an interest in applying regression techniques within a data science context

Why is this topic important?

  • Regression techniques are applicable to a variety of actuarial use cases.
  • Data often requires processing and manipulation before model fitting can take place successfully.
  • Being able to determine the importance of various factors has implications in various aspects of abusiness, including risk management, product development, and marketing.

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

Lapse Experience Analysis in R

Sign up for a free preview of this advanced R case study

Free Preview

Preview

£150 once off (3-month access)

Enroll Today

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