Accurate forecasting of insurance claims is of the utmost importance for insurance activity as the evolution of claims … determines cash outflows and the pricing, and thus the profitability, of the underlying insurance coverage. These are used as … inputs when the insurance company drafts its business plan and determines its risk appetite, and the respective solvency …

In this paper we analyze insurance demand when the utility function depends both upon final wealth and the level of … documented in real insurance markets. …

. The asset modeling framework leads to the proliferation of inappropriate assumptions about the effect of insurance line of … insurance parameter risk. …

-threat assessment in order to express the financial impacts. The study is based on an in-depth analysis of the insurance industry. The … of cyber threats for the field of insurance. …

Investments in security and cyber-insurance are two cyber-risk management strategies that can be employed together to … insurance liability scenarios (full liability, limited liability, and limited liability with deductibles) when we consider a … multi-branch firm with correlated vulnerability. The insurance component results to be the major expense. It ends up being …

The use of personalization mechanisms should allow the insurance distributor to reduce exploration costs and adjust the … offered insurance product to the needs, features, and situation of each individual client. This study seeks to examine how … liability should be allocated when the process of the personalization of an insurance product does not result in the client …

variables directly related to the insurance product (e.g., a regulatory restriction of insurance acquisition costs) as well as … importance of insurance distribution in banks. Significant risk factors (statistically significant) which determine gross … cooperation between banks and insurers as well as the specificity of insurance products distribution (also local) in the …

The growing trend in the number and severity of auto insurance claims creates a needfor new methods to efficiently … study considers how automotive insurance providers incorporate machinery learning intheir company, and explores how ML … models can apply to insurance big data. We utilize various MLmethods, such as logistic regression, XGBoost, random forest …

and the banking/insurance/reinsurance industry. Koch (2017) introduced a notion of spatial risk measure and a …

risks and profitability in Russian insurance companies in the context of digitalization. Structurally, the study consisted … of a comprehensive analysis of the insurance market in the Russian Federation, as well as an identification of the … components of the risk management process of insurance companies in the context of digitalization. Documents containing key …