MAF 2026: Mathematics and Statistics at the Service of Actuarial Sciences and Finance

The programme combined plenary lectures, parallel sessions organised by thematic areas, and online presentations, reflecting both the diversity of approaches and the international character of the event.

Plenary Speakers

The first plenary lecture was delivered by José Garrido (Concordia University), who presented Accounting for temporal and spatial dependencies in multi-population mortality forecasts: the “transformer” approach. His work extended transformer architectures to incorporate structural dependencies between countries, combining mortality data with exogenous variables. The proposed approach showed a significant improvement in the accuracy of long-term mortality forecasts.

On the same Wednesday, Isabel Serra (Universitat Autònoma de Barcelona) gave the talk Maximum Likelihood Approach for Risk Assessment in Finance, in which she examined financial risk assessment from the perspective of statistical inference of extreme events. Her presentation connected extreme value theory, maximum likelihood estimation, and machine learning, addressing current challenges such as temporal dependence and the presence of mixtures in the data.

On Thursday, Katrien Antonio (KU Leuven) focused her lecture on Machine Learning in an Expectation–Maximisation Framework for Nowcasting. Starting from the issue of partially observable information and reporting delays, she proposed a framework based on expectation–maximisation that integrates machine learning and deep learning techniques. Her results, particularly relevant in contexts with non-linear effects and high-dimensional data, have direct applications in the modelling of claims related to weather-related events.

That same day, Claude Lefèvre (Université Libre de Bruxelles) addressed Insurance Coverage for SIR Epidemic Models, centred on stochastic SIR-type models for epidemics. From an actuarial perspective, he analysed premium determination using the equivalence principle, paying particular attention to the total duration of the epidemic process and the expected number of cases. His talk highlighted the mathematical complexity that arises when translating epidemiological models into insurance products.

On Friday, Pietro Millossovich (Bayes Business School) presented Three Actuarial Applications of an Iterative Least Square Monte Carlo Algorithm. His lecture demonstrated the flexibility of the Least Squares Monte Carlo (LSMC) method for solving complex problems in life insurance and mortality modelling. Through three applications, he illustrated how this approach allows optimal stopping problems to be addressed while significantly reducing computational complexity.

To conclude, Raúl Merino (VidaCaixa), in Expanding Expansions: Beyond Vanillas, reviewed classical expansion methods in quantitative finance and showed how they can be applied beyond so-called vanilla products, i.e. standard financial instruments with simple structures such as basic options or bonds. His talk focused especially on interest rate markets and, using Malliavin calculus techniques, presented approximations capable of systematically capturing convexity effects.

Parallel Sessions and Thematic Areas

In addition to the plenary lectures, MAF 2026 was structured around parallel and online sessions organised into eight major thematic areas, reflecting the main current research directions in actuarial sciences and finance:

1. Climate Risks and Sustainable Finance (ESG), focused on climate risks, energy transition, natural disasters, and sustainable finance.
2. Longevity, Health, and Pension Systems, devoted to population ageing, mortality, and the design of sustainable pension systems.
3. Machine Learning and Artificial Intelligence, featuring work on model validation, algorithmic biases, and advanced applications in finance and insurance.
4. Actuarial Pricing and Count Models, focused on statistical models for pricing and reserving in non-life insurance.
5. Financial Networks, Contagion, and Dependence, addressing systemic interconnections, financial contagion, and dependence modelling.
6. Portfolio Management and Investment Decisions, dedicated to portfolio optimisation and risk management.
7. Financial Mathematics, centred on theoretical models for the valuation of derivatives and complex financial products.
8. Actuarial Mathematics, with contributions on actuarial valuation, risk, mortality, and insurance contracts.

An Interdisciplinary Meeting Space

Over the course of three days, the CRM, through MAF 2026, showcased how methodological and theoretical advances can be translated into useful tools to address some of today’s major economic and social challenges, ranging from climate change to population ageing and the digital transformation of the financial sector.