Master’s in Telematics and Actuarial Pricing of Connected Mobility Engineering
Online master's programme of 1,900 hours in telematics and actuarial pricing engineering for connected mobility, structured in 12 modules covering connected vehicle data, insurance price theory, telematics technical pricing, elasticity and demand, price optimisation, connected mobility products, pricing engines, regulation and portfolio profitability, with an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Analyse the connected vehicle data ecosystem.
Design technical tariffs based on usage and behaviour.
Estimate demand elasticity in mobility insurance.
Apply price optimisation techniques in compliance with regulation.
Design insurance products for new forms of mobility.
Implement real-time pricing engines.
Assess the profitability and ethics of pricing strategies.
Who it's for
- Pricing analysts.
- Pricing actuaries.
- Mobility product managers.
- Pricing data scientists.
- Embedded insurance consultants.
- Vehicle manufacturer partnership managers.
- Engineering or science graduates seeking to enter motor insurance.
What you'll work with
- Directive (EU) 2016/97 (IDD) (insurance distribution)
- Regulation (EU) 2023/2854 (Data Act) (access to and use of data)
- Regulation (EU) 2016/679 (GDPR) (data protection)
- Delegated Regulation (EU) 2017/2358 (governance of insurance products)
- Regulation (EU) 2024/1689 (artificial intelligence)
- Directive 2010/40/EU (intelligent transport systems)
- Law 50/1980 on Insurance Contracts (Spanish insurance contract law)
- Python (pandas, scikit-learn)
- R
- Earnix
- Radar (WTW)
- Power BI
12 modules · 1900 h
1.1Evolution of the connected vehicle1.2Factory-fitted telematics control units (TCU)1.3Manufacturer data platforms1.4Vehicle data aggregators1.5Data access and the EU Data Act1.6V2X communications and C-ITS standards1.7Mobility as a Service (MaaS)1.8Shared and subscription vehicles1.9New players in the value chain1.10Workshop: data flow map of a connected vehicle
2.1Technical cost versus market price2.2Structure of the commercial premium2.3Expenses, commissions and margin2.4Risk-based and demand-based pricing2.5Competition and the market cycle2.6Segmentation and cross-subsidies2.7Renewal versus new business pricing2.8Regulation of price optimisation2.9Principles of fair customer treatment2.10Case study: breakdown of a commercial premium
3.1Usage variables: distance, time of day, road type3.2Behavioural variables: speed and events3.3Context: weather, traffic and road type3.4Per-kilometre frequency models3.5Expected cost per trip3.6Base tariff plus variable component3.7Monthly dynamic premium adjustment3.8Models for drivers without history3.9Pricing vehicles with ADAS3.10Practical exercise: calculating a per-kilometre premium
4.1Conversion and retention as response variables4.2Logistic demand models4.3Estimating price elasticity4.4A/B price experiments4.5Causal inference and treatment effects4.6Instrumental variables and selection bias4.7Uplift modelling4.8Customer lifetime value4.9Cannibalisation between products4.10Laboratory: renewal elasticity model
5.1Formulating the optimisation problem5.2Business and regulatory constraints5.3Portfolio-level optimisation5.4Optimisation with linear and non-linear programming5.5Growth versus profitability scenarios5.6Ban on price walking at renewal5.7Monitoring results5.8Market and competitor simulation5.9Governance of the pricing process5.10Case study: optimisation with renewal limits
6.1Per-kilometre insurance6.2Usage-based insurance for car sharing6.3Covers for moped sharing and e-scooters6.4Insurance embedded in the vehicle purchase6.5Insurance for delivery and last-mile fleets6.6Insurance for electric vehicles6.7Battery and charging covers6.8Insurance for subscription vehicles6.9Ecosystems with manufacturers and dealers6.10Practical exercise: designing an embedded insurance product
7.1Real-time traffic data7.2Weather and meteorological conditions7.3Risk by road type and section7.4Accident black spots and clusters7.5Open data from the DGT and public administrations7.6Merging context data with trips7.7Spatio-temporal models7.8Dynamic risk maps7.9Using context in the premium7.10Laboratory: road section risk with open data
8.1Behavioural economics applied to insurance8.2Driver feedback and gamification8.3Rewards programmes8.4Driver coaching8.5Measuring behaviour change8.6Selection effect versus improvement effect8.7Designing the policyholder app8.8Communicating the score to the customer8.9Programme drop-out and fatigue8.10Case study: evaluation of a coaching programme
9.1Real-time rating engines9.2Quotation APIs9.3Model deployment with containers9.4Latency and scalability9.5Tariff versioning9.6Automated underwriting rules9.7Integration with aggregators and price comparison sites9.8Tariff regression testing9.9Price audit and traceability9.10Practical exercise: usage-based quotation API
10.1IDD and product governance10.2EIOPA guidance on pricing practices10.3Personal data and mobility under the GDPR10.4Data Act and access to vehicle data10.5AI Act and price transparency10.6Discrimination and proxy variables10.7Protection of vulnerable consumers10.8Complaints and the customer ombudsman service10.9DGSFP supervision10.10Case study: governance review of a UBI product
11.1Loss ratio indicators and combined ratio11.2Monitoring the tariff in production11.3Variance analysis11.4Portfolio mix and risk drift11.5Reinsurance of telematics portfolios11.6Results forecasting11.7Pricing dashboards11.8Pricing committees11.9Planning tariff reviews11.10Workshop: dashboard for a UBI portfolio
12.1Definition of the product or pricing problem12.2Market and competitor analysis12.3Preparation of usage and context data12.4Technical risk model12.5Demand model12.6Optimisation and pricing strategy12.7Regulatory and ethical assessment12.8Implementation plan12.9Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so the programme can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (pandas, scikit-learn), R, Earnix, Radar (WTW) and Power BI, in free, academic or evaluation versions. Testing is studied through real procedures for per-kilometre tariff calculation with connected vehicle data, renewal elasticity estimation with A/B experiments and price optimisation under regulatory constraints. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Directive (EU) 2016/97 (IDD), Regulation (EU) 2023/2854 (Data Act), Regulation (EU) 2016/679 (GDPR), Delegated Regulation (EU) 2017/2358, Regulation (EU) 2024/1689, Directive 2010/40/EU, Law 50/1980 on Insurance Contracts.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme's software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Python (pandas, scikit-learn), R, Earnix, Radar (WTW) and Power BI, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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