Premium Risk net of Reinsurance: from short-term to medium term assessment

Solvency II requirements introduced new issues for actuarial risk management in non-life insurance, challenging the market to have a consciousness of its own risk profile, and also investigating the sensitivity of the solvency ratio depending on the insurance risks and technical results on either a short-term and medium-term perspective. For this aim, in the present paper, a partial internal model for premium risk is developed for three multi-line non-life insurers, and the impact of some different business mixes is analyzed. Furthermore, the risk-mitigation and profitability impact of reinsurance in the premium risk model are introduced, and a global framework for a feasible application of this model consistent with a medium-term analysis is provided. Numerical results are also figured out with evidence of various effects for several portfolios and reinsurance arrangements, pointing out the main reasons for these differences

Risk-mitigation techniques: from (re-)insurance to alternative risk transfer

Insurance risks knowledge is becoming essential for both financial stability and social security purposes, moreover in a country with a very low insurance education like Italy. In insurance industry, Solvency II requirements introduced new issues for actuarial risk management in non-life insurance, challenging the market to have a consciousness of its own risk profile, and also investigating the sensitivity of the solvency ratio depending on the insurance risks and technical results on either a short-term and medium-term perspective. For this aim, in the present thesis, firstly a partial internal model for underwriting risk is developed for multi-line non-life insurers. Specifically, the risk-mitigation and profitability impacts of traditional reinsurance in the underwriting risk model are introduced, and a global framework for a feasible application of this model consistent with a medium-term analysis is provided. Reinsurance have to be considered in the assessment of Non-Life insurers risk profile, with particular regard to the Solvency II Underwriting Risk because of its impact on business and risk strategy. Risk mitigation techniques appear as a key driver of Non-Life insurance business as they can change risk profile over either the short-term or medium-term perspective. They impact the technical result of the year in such a way that it is important to assess how reinsurance strategies decrease the volatility, reducing the capital requirements, but, on the other hand, they also change the mean of distributions in different ways according to the price for risk requested by reinsurers. At the same time, risk mitigation also influences Non-Life insurance management actions as it can improve business strategy and capital allocation (also in potential capital recovery plans). Furthermore, the analysis a medium-term capital requirement would ask insurers to have more capital than in a one-year time horizon, and in this framework risk mitigation effects linked to reinsurance strategies must be assessed on either risk/return perspective trade-off. On the other hand, (re)insurance can play an active role in mitigating physical risks, and in particular natural catastrophe risks. In this context, as well as in natural disasters, Alternative Risk Transfer (ART) is becoming a new significant actuarial and capital management tool for insurers and, potentially, for government measures in recovery actions of economic and social losses in case of natural disasters. Catastrophe Bonds are insurance-linked securities that have been increasingly used as an alternative to traditional reinsurance for two decades. In exchange for a Spread over to the risk-free rate, protection is provided against stated perils that could impact the insured portfolio. A broad literature has flourished to investigate what are the features that significantly influence the Spread, in addition to the portfolio’s expected loss. Almost all proposed models are based on multivariate linear regression, that has provided satisfactory predictive performance as well as easily interpretability. This thesis also explores the use of Machine Learning models in modeling the determinant at issuances, contrasting both their predictive performance and their interpretability with respect to traditional models. An overview of the economics of CAT bonds, on current literature and on the statistical methodologies will be provided also. Aim of this Thesis is to provide a solid framework of insurance risk transfer for both pure underwriting and catastrophe risks, investigating risk transfer practices from traditional to alternative and most innovative technique. In these fields, firstly a suitable risk model is used in order to describe main impacts on insurance business model. Then, the main innovative alternative risk transfer for catastrophe risks are illustrated and CAT Bond will be adequately described, investigating main pricing models using a machine learning approach. Finally, a possible Italian CAT Bond issuance is provided in order to investigate an integrated solution with a traditional reinsurance underlying an alternative risk transfer in order to achieve a public-private partnership to natural catastrophe

Premium risk net of reinsurance: From short-term to medium-term assessment

Solvency II requirements introduced new issues for actuarial risk management in non-life insurance, challenging the market to have a consciousness of its own risk profile, and also investigating the sensitivity of the solvency ratio depending on the insurance risks and technical results on either a short-term and medium-term perspective. For this aim, in the present paper, a partial internal model for premium risk is developed for three multi-line non-life insurers, and the impact of some different business mixes is analyzed. Furthermore, the risk-mitigation and profitability impact of reinsurance in the premium risk model are introduced, and a global framework for a feasible application of this model consistent with a medium-term analysis is provided. Numerical results are also figured out with evidence of various effects for several portfolios and reinsurance arrangements, pointing out the main reasons for these differences

Urine Dipstick Analysis on Automated Platforms: Is a Reliable Screening Tool for Proteinuria? An Experience from Umberto I Hospital in Rome

Urinalysis is commonly used as a screening tool for kidney disease. In many cases, the dipstick urine assay includes the assessment of albumin/protein and creatinine; consequently, the value of their ratio is available on the urine section report. Identification of albuminuria/proteinuria at early stages is an important issue to prevent or at least delay the onset of chronic kidney disease (CKD), kidney failure, and the progression of cardiovascular damage linked to the kidney’s loss of function. Sensitive and specific diagnostic methods are required for the assessment of such an important biomarker: urine albumin, creatinine, and their ratio (ACR) measured with quantitative assays are considered the gold standard. Routine dipstick methods (more rapid and at a lower cost) are intended for wide population screening. The aim of our study was to verify the reliability of an automated urinalysis dipstick method by comparing the results with the quantitative test of creatinine and albumin performed on a clinical chemistry platform. The first-morning voids of 249 patients who arrived from different departments were analyzed in the Central Laboratory of the University Hospital Policlinico Umberto I in Rome. We found a good correlation between the two assays, even though we observed that the dipstick assessment tends to overestimate the ACR’s value, disclosing a higher number of false positives if compared to the reference method. As an important novelty in this study, we analyzed our data considering age (starting from pediatric to geriatric patients) and sex as variables for a sub-stratification of the participants. Our results show that positive values need to be confirmed with quantitative methods, especially in women and younger people, and that from samples that resulted as diluted at the dipstick assay, the ACR’s values can be obtained if they are reanalyzed with quantitative assays. Moreover, patients with microalbuminuria (ACR 30–300 mg/g) or severe albumin urinary excretion (ACR > 300 mg/g) should be reanalyzed using quantitative methods to obtain a more reliable calculation of the ACR