Using Best's Ratings in Life Insurer Insolvency Prediction

Ambrose, Jan M.; Carroll, Anne

doi:10.2307/253713

Cited by 39 publications

(25 citation statements)

References 10 publications

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“…BarNiv (1990) uses logit and other models to forecast the financial distress of property and casualty insurance firms. Other studies in this line of research are Ambrose and Carroll (1994), BarNiv and McDonald (1992), S. H. Lee and Urrutia (1996), and Baranoff, Sager, and Witt (1999).…”

Section: Theorymentioning

confidence: 99%

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Distributional Properties of Some Financial Ratios in Insurance

van der Heijden

2011

SSRN Journal

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This paper presents a distributional analysis of some financial ratios in the insurance industry.Although previous studies have established a reasonably good understanding of the frequency distributions of financial ratios, to date most of our knowledge has been derived from cross-sectoral studies, or from the manufacturing sector in particular. This paper aims to contribute to the literature by further applying and extending this knowledge into the financial services sector.The focus is on four key profitability ratios: the combined ratio, the expense ratio, the loss ratio and return on assets. A sample of 115 global insurance conglomerates, 64 from the United States and 55 from the EU, is used to test the effects of an outlier-removal procedure and data transformation on the normality of the distributions. The study successfully applies a modest normalisation procedure for all four ratios, highlights the dangers of conducting parametric tests on non-normal data series, and finds that lognormal transformation is beneficial just for the Return on Assets ratio.

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Section: Theorymentioning

confidence: 99%

“…Similarly, Ambrose and Carroll (1994) uses a stepwise logit model in favour of multiple discriminant analysis to deal with the violations of normality. These studies serve to illustrate that insurance data also suffers from non-normality of financial ratios, and that is worth examining this issue in more detail.…”

Section: Theorymentioning

confidence: 99%

Distributional Properties of Some Financial Ratios in Insurance

van der Heijden

2011

SSRN Journal

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“…Due to differences in staffing and funding, Canadian insurers are now examined by regulators every year whereas U.S. insurers are examined every three to four years. This is significant since studies that attempt to predict insolvency for U.S. insurers are only accurate one to two years prior to insolvency (Ambrose and Carroll, 1994;Barniv and Hershbarger, 1990).…”

Section: Explanations For the Difference In Insolvency Experiencementioning

confidence: 99%

An Analysis of the Difference in Solvency Experience of U.S. and Canadian Life Insurers

Kleffner

Jorgensen

1997

Geneva Pap Risk Insur Issues Pract

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“…Ambrose and Seward (1988) used multivariate discriminant analysis (MDA) in order to compare the insolvency prediction abilities of Best's ratings, the sets of financial ratios, and a two-stage prior probability approach. Ambrose and Caroll (1994) by using a logit model examined the efficiency of Best's recommendation, IRIS ratios, and other financial measures in their statistical ability to classify solvent and insolvent life insurers. Best's Interactive Financial Strength Analysis is an interactive financial strength assessment and provides an objective opinion on the ability of a specific insurance operation to meet its ongoing obligations to policyholders.…”

Section: Introductionmentioning

confidence: 99%

Robust Eligible Own Funds and Value at Risk Under Solvency II System

Pitselis

2013

Communications in Statistics - Simulation and Computation

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In the present article, we focus on the estimation of the eligible capital (own funds) an insurance company should hold in order to manage losses and avoid insolvencies under Solvency II system. For the supervision of solvency and prediction of insurer insolvency random coefficient regression (RCR) models are applied. Robust RCR models are also applied to remedy the effect of outliers and produce a more reliable parameter estimation. Based on the above-mentioned, models confidence intervals for the value at risk (VaR) are also provided. The techniques are implemented using data provided by private insurance companies.

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Using Best's Ratings in Life Insurer Insolvency Prediction

Cited by 39 publications

References 10 publications

Distributional Properties of Some Financial Ratios in Insurance

Distributional Properties of Some Financial Ratios in Insurance

An Analysis of the Difference in Solvency Experience of U.S. and Canadian Life Insurers

Robust Eligible Own Funds and Value at Risk Under Solvency II System

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