Doctoral Researcher in Accounting
Catholic University of Leuven

(ref. BAP-2022-649)
The Department of Accounting, Finance and Insurance offers a dynamic, stimulating and pleasant working environment. Moreover, AFI enjoys a strong international reputation and is part of a wide network consisting of other universities, companies and institutions. LRisk is the KU Leuven center for insurance and financial risk analysis, acting at the forefront of the international research community in the field of actuarial science, financial engineering and risk management for financial institutions.



This is a joint PhD project offered by the actuarial science research groups at KU Leuven and University of Melbourne. This vacancy applies to the PhD position with Leuven as home institution. The PhD candidate will visit the University of Melbourne during minimum 24 months.

The insurance industry faces fundamental changes that will not be tackled by incremental improvements of existing techniques, but call for entirely new insurance pricing paradigms. The dynamics of emerging risks such as cyber and weather related risks need to be handled with little or no past data. At the same time, for more traditional covers the wealth of data that is collected now presents new challenges (e.g., computational or ethical) and opportunities (e.g., statistical power). Bringing together the Leuven-based expertise on machine learning practice for insurance data with the knowledge on stochastic processes, behavioral data and dependencies from the Melbourne team, this PhD project will focus on:

  1. formulas for discrimination-free insurance pricing;
  2. predictive modeling tools for the actuarial valuation of emerging risks; and
  3. the creation of data analytic tools for a customer-centric, usage based insurance paradigm that bundles selected products and even services.

Differential pricing is a foundation of modern-day insurance and deals with the actuarial valuation of risk by calculating a fair price for a new policy sold to a given risk profile.  The so-called best estimate price   is calculated as the ‘expected frequency times expected impact’ of the insured event resulting from standard regression models (the generalized linear models, or GLMs) for claims data. These predictive models are key in a business that is highly regulated, strongly valuing the explainability of the algorithms driving decisions with impact on customers. After selling a contract to a client, the insurer is liable for the claims arising from this contract. Capital must be held to meet these future liabilities. Calculating the necessary amount of capital is the job of a reserving actuary. Even though these key actuarial tasks are treated in silos in current insurance practice and literature, reserving is the mere continuation of pricing. Whereas pricing happens at the onset of the insurance policy – before any coverage has been provided – reserving is, in some way, an updated pricing of the insurance policy. The pricing actuary values the total loss on a policy from ground-up, while the reserving actuary assesses the total loss in the presence of some (though incomplete) information on the development of occurred claims.

As such, we will design dynamic, responsive and resilient pricing and reserving techniques for traditional but also emerging risk types, including machine learning methods that balance predictive value and acceptability by major stakeholders (e.g. explainable to management, discrimination-free pricing). Access to real data and strong links with practice will ensure applicability and relevance of our developments.

Bringing together the available expertise (in Leuven) on machine learning practice with the knowledge on stochastic processes and dependencies (from Melbourne) the first PhD project will focus on (1) a probabilistic framework for discrimination-free pricing in tariff plans, (2) predictive modeling tools for the actuarial valuation of emerging risks and (3) the creation of data analytic tools for a new insurance paradigm: customer-centric, usage based, bundling selected products and even services.

The new PhD student will join an existing group of graduate students already working on the project. The project will complement an ongoing project on Combined actuarial and financial valuation of hybrid insurance liabilities and the collaboration will ensure a successful completion of the project.



We are looking for a highly motivated, enthusiastic, communicative, and eager-to-learn researcher with a passion for actuarial science, statistics, probability theory and analytics. 

Specific qualifications: 

  • Holder of a Master's degree in mathematics, actuarial science, statistics, engineering, or another related, quantitative field, with excellent grades.
  • Interested in programming and computational work.
  • A high level of proficiency in English, both spoken and written.



Full-time employment in an international context with a competitive salary/scholarship. You will join the doctoral school of the Faculty of Economics and Business of KU Leuven. Funding is available for 4 years. You will join the Insurance research group which is part of the LRisk research center of KU Leuven. See the website of the center for more information. The main focus is on research but you will provide occasional support in the teaching and administrative activities of the group 

You will work towards a joint PhD degree by KU Leuven and the University of Melbourne. 

Start date: September 1, 2023 or to be negotiated


For more information please contact Prof. dr. Katrien Antonio, mail: or Prof. dr. Benjamin Avanzi, mail:

You can apply for this job no later than June 30, 2023 via the
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at
  • Employment percentage: Voltijds
  • Location: Leuven
  • Apply before: June 30, 2023
  • Tags: Economie
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