Actuarial Science and Insurance Education and events

Reverse Mortgages: Impact on Household Financial Sustainability

Abstract
Reverse mortgage is one of the products (perhaps the main one) that is good to obtain additional income by using the habitual residence as collateral. This paper analyzes the effects that contracting a reverse mortgage has on the finances of families of a country or group whose members who aged 65 or older are the sole owners of the 100% of the property, regardless of the receipt of a retirement pension. For this purpose, an economic-financial model based on the life cycle model is defined, which considers a double source of randomness: mortality and dependence of family members. Long-term effects are measured using probabilistic, temporal and monetary indicators. For each country, the model must be adapted according to the legal framework for retirement and long-term care benefits and for the actuarial mortality and long-term care tables. We also studied the importance of the socioeconomic group to which the family belongs in quantifying these effects. As an illustration, this model was applied on Spanish families using data from the Spanish Survey of Household Finances 2017.

Biography
M. Mercè Claramunt Bielsa holds a PhD in Economics and Business Studies (University of Barcelona) and is an Actuary from the same university. She is a research associate professor at the University of Barcelona and has focused her research and teaching career on pensions, insurance and the solvency of insurance companies.

She has been coordinator of the Doctorate in Business at the University of Barcelona, general coordinator of the Doctorate in Business Studies at the University of Barcelona and coordinator of the Master in Business, Finance and Insurance Research at the same university.

She is currently head of the research group consolidated by the Generalitat de Catalunya, Actuarial and Financial Modeling. She is also head of research at the Observatory of European Complementary Social Pension Plans.

She is a member of the Col·legi d'Actuaris de Catalunya (CAC) and of the education and Pension committees of the Actuarial Association of Europe and the International Actuarial Association as a representative of the CAC, and also a member of the OPSG of EIOPA.

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Calibration of risk aversion to real pension asset allocation

Abstract:
An investor's risk aversion is a fundamental element in financial decision-making and preferences but lacks a standardised calibration method. We propose an approach to measure the risk aversion of an investor managing a diverse portfolio that includes pension savings, real estate, and free funds. We utilise the investor's real asset allocation as the optimal strategy, assuming the investor's preferences follow a power utility function (CRRA utility function). We calibrate a risk aversion parameter by building on Merton's formulas for optimal investment strategies. For pension savings, we account for the present value of future premiums, which results in an optimal investment strategy consistent with real life-cycle pension products. Realistic and stable risk aversions are calibrated by constructing a customised risky fund aligned with the investor's preferences. Disparities in risk aversion across financial categories are examined by certainty equivalents, and a numerical study with a real Danish pension portfolio emphasises the practical applications of our results.

The talk is based on a working paper with Professor Mogen Steffensen (University of Copenhagen) and Jens-Philip Dehn-Toftehoej (Datasolvr ApS)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4898823

Biography:
Debbie is currently a Lecturer at the Department of Mathematical Sciences at the University of Liverpool since 2023. Originating from Denmark, she studied her Undergraduate, Master and PhD in insurance mathematics at the University of Copenhagen. The PhD was part of a collaboration between the IT company Edlund, the University of Copenhagen, and the IT-University Copenhagen, which involved simulation-based projection models. Debbie obtained her PhD degree in 2022 under the supervision of Mogens Steffensen. Afterwards, she worked as a postdoc at the University of Copenhagen for one year, considering a project on risk aversion and stochastic control theory in collaboration with FinTech companies Dreamplan and Datasolvr.

Her main areas of research are on risk calculation, valuation and stochastic control theory for pension, health and life insurance. She is particularly interested in preferences (normative economics) and realised behaviour (positive economics) in the optimal control of insurance risk, product design and investments. Debbie is also interested in applying theoretical knowledge and research findings to real-world problems and the interplay between theory and practice. Furthermore, she has experience with and an interest in Machine learning.

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Global Sensitivity Analysis with Optimal Transport

Abstract:
We examine the construction of variable importance measures for multivariate responses using the theory of optimal transport. We start with the classical optimal transport formulation. We show that the resulting sensitivity indices are well-defined under input dependence, are equal to zero under statistical independence, and are maximal under fully functional dependence. Also, they satisfy a continuity property for information refinements. We show that the new indices encompass Wagner’s variance-based sensitivity measures. Moreover, they provide deeper insights into the effect of an input’s uncertainty, quantifying its impact on the output mean, variance, and higher-order moments. We then consider the entropic formulation of the optimal transport problem and show that the resulting global sensitivity measures satisfy the same properties, with the exception that, under statistical independence, they are minimal but not necessarily equal to zero. We prove the consistency of a given-data estimation strategy and test the feasibility of algorithmic implementations based on alternative optimal transport solvers. Application to the assemble-to-order simulator reveals a significant difference in the key drivers of uncertainty between the case in which the quantity of interest is profit (univariate) or inventory (multivariate). The new importance measures contribute to meeting the increasing demand for methods that make black-box models more transparent to analysts and decision-makers.

Summary of joint works with Alessio Figalli (ETH), Elmar Plischke (Dresden), Promit Ghosal (U. Chicago) and Giuseppe Savarè, Bocconi University

Preprint of the first paper available at:

https://people.math.ethz.ch/~afigalli/papers-pdf/Global-sensitivity-analysis-via-optimal-transport.pdf

Biography:
Emanuele Borgonovo is Full Professor and Director of the Department of Decision Sciences at Bocconi University. He is co-editor-in-chief of the European Journal of Operational Research, advisor of the Springer International Series in Management Science and Operations Research, Co-Chair of the Committee on Uncertainty Analysis of the European Safety and Reliability Association, and member of the Scientific Committee of the Fondazione Silvio Tronchetti Provera. He was the president of the Decision Analysis Society of INFORMS in 2020-2022. At Bocconi University he was Director of the Bachelor in Economics, Management, and Computer Science (BEMACS) from 2016-2022, and director of the ELEUSI Research Center from 2008 to 2012, as well as director of the SDA Bocconi Management Science Lab from 2013 to 2016. He holds a Ph.D. in Probabilistic Risk Assessment from the Massachusetts Institute of Technology and is the recipient of several national and international awards. He is a member of the editorial boards of numerous international journals, such as Risk Analysis, Decision Analysis, Reliability Engineering & System Safety, Operations Research Perspectives, the Journal of Business Logistics. He has published more than 100 scientific articles, in journals such as the European Journal of Operational Research, Management Science, Operations Research, Risk Analysis, the Journal of the Royal Statistical Society Series B, Statistics and Computing, the Scandinavian Journal of Statistics, SIAM/ASA Journal on Uncertainty Quantification, and worked on international research projects with, among others, the US Defense Advanced Research Project Agency (DARPA), the US Nuclear Regulatory Commission, the US Department of Energy, the Idaho National Laboratory, Electricité de France, Charles River Analytics, etc. In his works, he has introduced several new sensitivity analysis techniques. The differential importance measure is part of the NASA Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners. He is the author of the book “Sensitivity Analysis: An Introduction for the Management Scientist.

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Abstract:

The results emphasize distribution-free calculation of premia, without the need for stochastic model assumptions. We illustrate to what extent traditional non-life pricing practices, such as GLM, and modern predictive approaches are consistent with our approach to pricing.

The talk is based on joint work with Mathias Lindholm and Julien Trufin.

Title: Non-life pricing: back to first principles

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Şule Şahin is currently a Senior Lecturer in Actuarial Science at the University of York. Previously, she served as a Lecturer in Actuarial and Financial Mathematics at the University of Liverpool (2017-2022) and held an Associate Professor position in the Department of Actuarial Sciences at Hacettepe University, Türkiye, from 2018 to 2020. She is the Director of the Centre for Actuarial Compensation and Valuation of Life (CAVOL), a member of the Ogden Working Party responsible for the analyses underpinning the Ogden Tables used in determining compensation for personal injury and fatal accident cases, and a Board Member of the AFIR-ERM section of the International Actuarial Association (IAA).

Dr Şahin earned her PhD in Actuarial Mathematics from Heriot-Watt University in 2010. She also holds an MSc in Actuarial Science from Hacettepe University, an MSc in Sociology, and a BSc in Statistics from the Middle East Technical University in Ankara, Türkiye. She is a Fellow of the Institute and Faculty of Actuaries and a Corresponding Member of the Actuarial Society of Türkiye.

Her research interests include stochastic investment models for long-term applications, mortality modelling, and compensation for loss of earnings. She has undertaken research visits to the University of the Witwatersrand, Johannesburg, in 2012 and Columbia University, New York, in 2019 as part of projects funded by the University of the Witwatersrand, the Casualty Actuarial Society, and the Society of Actuaries. In addition to attending numerous conferences, she has published papers in leading actuarial, applied mathematics, and statistics journals. Dr Şahin is also a co-editor of the open-access Springer Actuarial Series book, Pandemics: Insurance and Social Protection, published in 2021.