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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 …
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The previous performance evaluation studies towards non-life insurance companies emphasized on the comparative … evaluation among public and private sector companies. Early detection and diagnosis of bankruptcy of insurance companies is much … variables and determine how they contribute to bankruptcy risk prediction, based on which the non-life insurance companies are …
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We propose a generic workflow for the use of machine learning models to inform decision making and to communicate modelling results with stakeholders. It involves three steps: (1) a comparative model evaluation, (2) a feature importance analysis and (3) statistical inference based on Shapley...
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Value-at-risk (VaR) is an important risk measure now widely used by financial institutions and regulators to quantify market risk and compute regulatory capital charge. The performance of VaR model can be examined by back-testing. Based on back-testing information, this paper develops a Machine...
Persistent link: https://www.econbiz.de/10014235441
Modeling advances create credit scores that predict default better overall, but raise concerns about their effect on protected groups. Focusing on low- and moderate-income (LMI) areas, we use an approach from the Fairness in Machine Learning literature — fairness constraints via group-specific...
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