by IAASections Added 11 months ago 0 813 Views

by IAASections Added 11 months ago 0 464 Views

The comparison of different algorithms for insurance pricing exercise is a task that relies heavily on the data sample used. There are two options: real data and synthetic data. A critical issue with the real data is the lack of information of the exact u

by IAASections Added 11 months ago 0 242 Views

Following innovations in machine learning and computational statistics, a large variety of new modeling techniques are being applied to premium rating. In order to carry out model comparison and selection in this regime it is particularly valuable to deve

by IAASections Added 11 months ago 0 309 Views

This presentation focuses on the problem of moral hazard in health insurance. We introduce our solution by explaining how we have modelled the behaviour of supplementary health insurance policyholders within a context of moral hazard and build an Optimal

by IAASections Added 11 months ago 1 233 Views

In this paper, we develop stochastic models to determine the impact of a massive cyber attack on an insurance portfolio. The model is based on the classical SIR framework (Susceptible - Infected - Recovered) of epidemiological models. For a given type of

by IAASections Added 11 months ago 3 425 Views

In insurance and even more in reinsurance it occurs that about a risk you only know that it has suffered no losses in the past say seven years. Some of these risks are furthermore such particular or novel that there are no similar risks to infer the loss

by IAASections Added 11 months ago 0 239 Views

The American Academy of Actuaries (Academy) would be pleased to present Actuaries Climate Risk Index (ACRI): Research Update. The ACRI is derived from a model of the statistical relationship between the weather components of the Actuaries Climate Index (A

by IAASections Added 11 months ago 0 210 Views

Approximate Bayesian Computation (ABC) is a statistical learning technique to select and calibrate models in an automated fashion using the data at hand. It consists in simulating synthetic data from the potential models and assessing the distance between

by IAASections Added 11 months ago 1 179 Views

In this talk, we present a two-player extraction game where the random terminal times follow (different) heavy-tailed distributions which are not necessari!y compactly supported. Besides, we de!ve on the implications of working with logarithmic utility/te

by IAASections Added 11 months ago 0 212 Views

In this paper we propose an actuarial framework and a statistical methodology allowing the quantification of Cyber claims resulting from data breaches events even when applied on few and heterogeneous data. Indeed, for now, just a few Cyber insurance clai

by IAASections Added 11 months ago 2 250 Views

We study the relation between one-year premium risk and ultimate premium risk. In practice, the one-year risk is sometimes related to the ultimate risk by using a so-called emergence pattern formula introduced by England et al. (2012) and Bird, Cairns (20

by IAASections Added 11 months ago 0 205 Views

The (re)lnsurance industry is faced with a growing risk related to the development of information technology (IT). This growth is creating an increasingly digitally interconnected world with more and more dependance being placed on IT systems to manage pr

by IAASections Added 11 months ago 1 231 Views

Tree-based methods are convenient and powerful machine learning tools thatcan be seen as alternatives to classical regression and prediction models suchas generalized linear models, see for example. The most standard proceduresare designed to estimate the

by Deloitte Added 11 months ago 1 283 Views

Outstanding claims reserving have become most of the time Best Estimate whereas they used to be appropriate. These reserves should now be equal to the best estimate of the cost of the claims not yet settled and not yet reported. Even if new reserving meth

by Deloitte Added 11 months ago 0 615 Views

The international IFRS 17 standard will have a major impact on the valuation and accounting of insurance contracts and therefore on the profit signature of insurance companies.Actuaries have a central role in new standard implementation. They are strongly

by IAASections Added 11 months ago 1 573 Views

A simple formula for non-discriminatory insurance pricing is introduced. This formula is based on the assumption that certain individual (discriminatory) policyholder information is not allowed to be used for insurance pricing. The suggested procedure can

by IAASections Added 11 months ago 0 241 Views

The insurance industry are embracing innovation and technology where are not only Millennials and Generation Y customers accounted for the majority of online insurance sales. The InsurTech is breaking the paradigms affecting the insurance market by introd

by IAASections Added 11 months ago 0 204 Views

One of the first in the actuariat literature published agent based models (ABM) is by Ingram et al. The paper describes a model of a competitive (insurance) market that shows cyclical behavior. The authors put their focus on the model’s theoretic fo

by IAASections Added 11 months ago 1 214 Views

Leveraging from the patchwork copula formalization and from various piecewise constant density estimators (minimum-distance based, tree-shaped, Bayesian partitioning, Delaunay tree, Voronoi histogram), we derive a flexible, consistent, piecewise constant

by IAASections Added 11 months ago 2 684 Views

We discuss the statistical modeling cycle. This discussion highlights on how to enhance classical generalized linear models by neural network features. On the way to get there, we mention traps and pitfalls that need to be avoided to get good statistical

by IAASections Added 11 months ago 0 232 Views

In this work, we propose a methodology to predict the total cost of a natural catastrophe shortly after itsoccurrence. Thanks to a large database provided through a partnership with Federation Francaise d'Assurance,we manage to have access to a very la

by IAASections Added 11 months ago 0 187 Views

by Milliman Added 11 months ago 0 236 Views

For both Solvency II and IFRS 17 the actuary can use unpaid claim variability estimates for cash flows and the runoff of unpaid claims in addition to the more widely used accident year view of the unpaid claims. This paper is based on a review of the foun

by IAASections Added 11 months ago 4 660 Views

In recent years, one of the most critical tasks for actuaries is to adopt data science techniques in predictive modeling practice. However, due to the peculiarity of insurance data as well as the priorities taken by actuaries in decision-making, such as t

by IAASections Added 11 months ago 0 252 Views

Among the several features of cyber-attacks one wants to reproduce, those related to the memory of events and self-exciting behavior is of major importance, as it underlies the clustering and auto-correlation of times of cyber-attacks. In this paper, we p

by IAASections Added 11 months ago 0 282 Views

In 2019, Alibaba reinvents healthcare thanks to a P2P insurance model which has been a huge commercial success with more than 100 million users in China.Despite commercial failures of most P2P models (B2C) attempts in Europe, Alibaba proves that P2P model

by IAASections Added 11 months ago 1 311 Views

In non-life insurance, the payment history can be predictive of the timing of a settlement for individual claims. Ignoring the association between the payment process and the settlement process could bias the prediction of outstanding payments. To address

by IAASections Added 11 months ago 2 244 Views

The goal of this paper is to jointly model the development of individual daim payments and daims incurred. Our analysis only focuses on the development of the so-called Reported But Not Settled (RBNS) daims. We develop regression models and postulate dist

by IAASections Added 11 months ago 1 258 Views

The volume of digital data is increasing by around 61 % annually. The rapidly developing techniques of predictive analytics make it possible to use this data in underwriting and pricing of insurers. These novel technologies present huge opportunities for

by IAASections Added 11 months ago 0 206 Views

Deep Learning models are currently being introduced into business processes to support decision-making in insurance companies. At the same time model risk is recognized as an increasingly relevant field within the management of operational rlsk that tries