Non-Life Pricing Using Machine Learning Techniques with R Applications

Introduction & Programme

Non-Life insurance is facing many challenges ranging from fierce competition in the market or evolution in the distribution channel used by consumers to evolution of the regulatory environment.

Pricing is the central link between solvency, profitability and market shares (volume). Improving pricing practice encompasses several dimensions:

• Technical: is our pricing adequate to cover the underlying cost of risk of my policyholders and the other costs we are facing? Which are the key variables driving the risk? Are they adequately taken into account in our pricing? What’s the impact of the claims history of my policyholder on its expected risk? In which segment are we profitable and in which are we not profitable?
• Competition: at what price will we attract the segments that we target and price out those that we do not want? Is the positioning of our competitors influencing our pricing practice and our profitability? What’s my position with respect to my competitors in terms of pricing? What are the segments in which I am well positioned and the segments where I am not well positioned?
• Elasticity: what price (evolution) are our existing customers prepared to accept? Does the sensitivity to price evolution depend on the profile of my customer?
• Segmentation: is our segmentation granular enough for our purposes?

The aim of this web session is to present some advanced actuarial techniques used in non-life pricing, competition analysis and profitability analysis. The web session focuses on some practical problems faced by pricing actuaries and product managers and presents some new techniques used in non-life pricing in order to open new perspectives for product development (competition analysis, profitability analysis,…).

Preliminary Programme
Tuesday, 8 December 2026
09:00-10:30 Data Selection, Pre-Analysis and Feature Selection (data quality, pre-treatment, missing values, feature engineering and feature selection)
Overfitting and cross-validation 
Example: Data Analysis and filtering
10:30-10:45 Break
10:45-12:30 Regression tree models
Example: Fitting a regression tree on frequency
12:30-12:45 Break
12:45-14:00 Bagging and random forest models
Example: Fitting a random forest on frequency
Case Study: Random forest model adjustment for cost

Wednesday, 9 December 2026
09:00-10:30 GBM models
Case Study: GBM model adjustment for frequency
10:30-10:45 Break
10:45-12:30 Explainable machine learning techniques (PDP, H statistics, Shape value, EBM)
12:30-12:45 Break
12:45-13:45 Case study: Features selection, partial dependence plot and Shapley Value

Thursday, 10 December 2026
09:00-10:30 Case study: Application of GBM method to highlight interactions
Unsupervised machine learning 
10:30-10:45 Break
10:45-12:30 Profitability analysis: profitability and positioning assessment with ML techniques
Example: profitability analysis with regression trees 
12:30-12:45 Break
12:45-13:45 Competition analysis: understanding competitors prices
Example: Reverse engineering of competitors prices
Client behaviour and Elasticity 

All the above times are given in CET (Central European Time).

Learning Objectives & Approach

The web session will alternate between methodological concepts, practical examples and case studies in order to ensure a comprehensive understanding of the techniques presented.

The participants will be requested to look at 4 e-learning modules (of around 30 minutes each) presenting the basics of machine learning before the web session. The access to these e-learning modules will be granted up to the end of the web session. These 4 e-learning modules are:

• Introduction to Machine learning
• Supervised learning (parts 1 and 2)
• Unsupervised learning

The case studies will be performed by the participants with the R software. An individual support will be available during the case study sessions thanks to breakout rooms.

Participants

The web session is developed for non-life actuaries or statisticians but also for managers working in product development or risk management departments. Participants should ideally have basic knowledge of non-life pricing. A basic knowledge of the R software is useful.

Technical Requirements
Please check with your IT department if your firewall and computer settings support web session participation (the programme Zoom will be used for this online training). Please also make sure to join the web session with a stable internet connection.

Attendees are encouraged to have a laptop computer with R installed as well as some useful packages (all the information will be provided).

Language & CPD Credits

The language of the web session will be English.

CPD Credits
For this web session, the following CPD credits are available under the CPD scheme of the relevant national actuarial association:

• Austria: 13 points
• Belgium: 13 points
• Bulgaria: 15 points
• Croatia: individual accreditation
• Czech Republic: 13 hours
• Denmark: 13 credits
• Estonia: 13 hours
• Finland: 8.5 points
• France: 75 points
• Germany: 13 hours
• Greece: 17 points
• Hungary: 13 hours
• Iceland: 13 credits
• Ireland: 13 hours
• Italy: approx. 4 credits (individual accreditation)
• Latvia: 13 hours
• Lithuania: 13 hours
• Netherlands: approx. 13 PE-points (individual accreditation)
• Norway: 13 points
• Poland: 13 hours
• Portugal: 13 hours
• Russia: 40 points
• Serbia: 5 hours
• Slovakia: 8 points
• Slovenia: 50 points
• Spain: CAC: 13 hours, IAE: 13 hours
• Switzerland: 15 points
• USA: SOA (Section B): up to 15.60 hours

No responsibility is taken for the accuracy of this information.

Fees & Registration Details

Early Bird Registration Fee (until 27 October 2026):

• For private customers in the EU: €1,040.00 + VAT of the billing country (example Germany: €1,237.60 incl. 19% VAT)
• For private customers outside the EU: €1,237.60 (incl. 19% VAT)
• For businesses within the EU (excl. Germany, with valid VAT ID): €1,040.00 (net, reverse charge applies)
• For businesses in Germany: €1,237.60 (incl. 19% VAT)

Regular Registration Fee (from 28 October 2026):

• For private customers in the EU: €1,365.00 + VAT of the billing country (example Germany: €1,624.35 incl. 19% VAT)
• For private customers outside the EU: €1,624.35 (incl. 19% VAT)
• For businesses within the EU (excl. Germany, with valid VAT ID): €1,365.00 (net, reverse charge applies)
• For businesses in Germany: €1,624.35 (incl. 19% VAT)

Important VAT Information:

• For private customers with a billing address in an EU country: VAT will be charged at the applicable rate in the country of the billing address. The final amount, including VAT, will be calculated upon invoicing.
• For customers with a non-EU (third country) billing address: Only a non-company billing address is accepted for VAT compliance reasons. 19% VAT applies to all non-EU private customers.
• For businesses within the EU (excluding Germany), Iceland, Liechtenstein, Norway, Switzerland, and the UK with a valid VAT ID: The reverse charge mechanism applies (net price; VAT will not be charged). Please ensure your valid VAT ID is entered correctly during registration.
• For all customers with a billing address in Germany: 19% VAT applies.

Please submit your registration using our online form below. Closer to the event, you will receive further login details to join the web session.

Your registration is binding. Cancellation is only possible up to 2 weeks before the first day of the event. If you cancel later, the full participation fee is due. You may appoint someone to take your place but must notify us in advance. EAA has the right to cancel the event if the minimum number of participants is not reached.

We will send you an invoice via email. Please allow a few days for handling. Please always give your invoice number when you effect payment. All bank charges are to be borne by the participant.

Registration is open until two working days before the web session. If registration has already been closed for this web session, please call us or send an email to contact@actuarial-academy.com in order to find out whether a late registration is still possible.