GeoAI for large-scale image analysis and machine vision: recent progress of artificial intelligence in geography
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for
spatial analytics in Geography. Although much progress has been made in exploring the …
spatial analytics in Geography. Although much progress has been made in exploring the …
Enhancing Auto Insurance Risk Evaluation with Transformer and SHAP
The evaluation of auto insurance risks is a fundamental task for financial institutions, crucial
for setting equitable premiums and managing risks effectively. Traditional machine learning …
for setting equitable premiums and managing risks effectively. Traditional machine learning …
An approach to multi-class imbalanced problem in ecology using machine learning
Ecologists collect their data manually by visiting multiple sampling sites. Since there can be
multiple species in the multiple sampling sites, manually classifying them can be a daunting …
multiple species in the multiple sampling sites, manually classifying them can be a daunting …
Boosting insights in insurance tariff plans with tree-based machine learning methods
Pricing actuaries typically operate within the framework of generalized linear models
(GLMs). With the upswing of data analytics, our study puts focus on machine learning …
(GLMs). With the upswing of data analytics, our study puts focus on machine learning …
County-level corn yield prediction using supervised machine learning
The main objectives of this study are (1) to compare several machine learning models to
predict county-level corn yield in the study area and (2) to compare the feasibility of machine …
predict county-level corn yield in the study area and (2) to compare the feasibility of machine …
The added value of dynamically updating motor insurance prices with telematics collected driving behavior data
R Henckaerts, K Antonio - Insurance: Mathematics and Economics, 2022 - Elsevier
We analyze a novel dataset collecting the driving behavior of young policyholders in a motor
third party liability (MTPL) portfolio, followed over a period of three years. Driving habits are …
third party liability (MTPL) portfolio, followed over a period of three years. Driving habits are …
Reinforcement learning for pricing strategy optimization in the insurance industry
E Krasheninnikova, J García, R Maestre… - … applications of artificial …, 2019 - Elsevier
Pricing is a fundamental problem in the banking sector, and is closely related to a number of
financial products such as credit scoring or insurance. In the insurance industry an important …
financial products such as credit scoring or insurance. In the insurance industry an important …
Towards virtual 3D asset price prediction based on machine learning
JJ Korbel, UH Siddiq, R Zarnekow - Journal of Theoretical and Applied …, 2022 - mdpi.com
Although 3D models are today indispensable in various industries, the adequate pricing of
3D models traded on online platforms, ie, virtual 3D assets, remains vague. This study …
3D models traded on online platforms, ie, virtual 3D assets, remains vague. This study …
[图书][B] Insurance, biases, discrimination and fairness
A Charpentier - 2024 - Springer
Preface “14 litres d'encre de chine, 30 pinceaux, 62 crayons à mine grasse, 1 crayon à mine
dure, 27 gommes à effacer, 38 kilos de papier, 16 rubans de machine à écrire, 2 machines à …
dure, 27 gommes à effacer, 38 kilos de papier, 16 rubans de machine à écrire, 2 machines à …
Neural networks for quantile claim amount estimation: a quantile regression approach
AG Laporta, S Levantesi, L Petrella - Annals of Actuarial Science, 2024 - cambridge.org
In this paper, we discuss the estimation of conditional quantiles of aggregate claim amounts
for non-life insurance embedding the problem in a quantile regression framework using the …
for non-life insurance embedding the problem in a quantile regression framework using the …