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The purpose of this paper is to provide empirical information about the past loss experience in major US crop insurance programs, and documents the impacts of ratings changes through time on the premiums and exposure to participants. The losses are also examined within the structure of the current SRA to identify impacts on insurance companies and the government by fund designation.

- The study uses RMA Summary of Business data and methods consistent with the use of loss-cost ratemaking to analyze loss performance across years with different starting prices and volatilities. Additionally, the RMA premium quoting system was replicated across years with the ability to adjust only one feature at a time to isolate the impacts of changes in individual rating elements from changes in market conditions. Tabulations are provided in map and table form to present the loss ratios through time, in aggregate across time, and within each of the possible funds in which exposures are held. Additionally, the tools developed allow a direct tabulation of the farmer-level premium impacts of individual changes in the policy premium system, and of changing conditions over time.

Corn and soybeans represent dominant shares of aggregate policy premiums and liability, and also are the crops that underwent the greatest degree of revision in rates over the recent past both due to rate study implications, and to loss rate experience. Despite commonly made arguments that payments associated with the drought of 2012 “more than wiped out all historic gains,” it appears that insurance worked very much as intended and that the loss ratios through time are within reasonable ranges of targets. Fund designation, and the separation under the most recent SRA of Group 1 and Group 2 states substantially dampened the loss sharing and ability to capture gains by private companies, and leads to fairly low rates of return on a pure fund-loss sharing basis for insurance companies. Finally, despite the extreme losses of 2012, the aggregate performance of corn relative to the remainder of the program exhibits lower than average loss rates both in aggregate and on a scale-adjusted basis.

The study provides an important means to isolate and assess implications of rate changes, and to associate causes of losses with rate charges. Additionally, the structure of the SRA, and possible future versions of the SRA are informed by both the aggregate, and the normalized performance results provided. And, the relative performance of major row, crops even with recent extreme losses, appears appropriate or positive to insurance companies after considering the impacts of the SRA on company exposure. In total, the evidence points toward appropriate movement toward target overall loss ratios in the US crop insurance program.

This paper provides an extensive empirical evaluation of ratings for major crop insurance policies and provides a unique means to decompose sources of changes in premiums and rates across locations and through time. It also provides an evaluation of the performance of crop insurance post-SRA in a manner that allows both totals and scale-adjusted performance to be assessed.

The business model of monoline insurers is to guarantee payments of debt issues in case of defaults by the issuer. Although sparse attention is given to monolines in literature, they play an important role in enabling municipalities and firms in refinancing. This study aims to conduct a systematic review of 181 articles from 1990 to 2020 from 23,130 records and a case study on the key monoline insurers. Key failure, success factors and demand for future monoline insurance are identified. Finally, the study explores monolines’ potential during COVID-19 and develops a framework for monoline governance and regulation.

The study follows Briner and Denyer and Moher et al. to implement the systematic review. The methodology involves ascertaining the motivation behind the review, and formulating research questions; aggregating relevant prior literature from scientific databases, conducting quality assessment and synthesising the data; and conducting extensive analysis for framework development. Case study methodology foundation phase focuses on understanding the research philosophy. The second phase involves documenting the procedures involved. The final phase involves collecting the relevant quantitative and qualitative material. In addition, collecting empirical data from numerous sources allows triangulation.

The review results of 181 articles from 1990 to 2020 show that peak article counts occur in 2010 and 2013 (nine academic studies) and in 2008 and 2010 (six industry studies). Over- and under-explored domains happen to be bond pricing (86 academic studies) and bond markets (36 industry studies) and corporate bonds (19 academic studies), respectively. The study highlights failure factors such as adverse selection, premiums mispricings, inadequate capital and regulation, untimely downgrades and governance issues; and identifies success factors such as conservative underwriting, early financing, competitor business acquisitions and obtaining put-back claims. Potential during COVID-19 is discussed and a monoline governance framework is developed.

Search and selection criteria distortions may lead to sample selection bias in systematic reviews. Issue is addressed by using different permutations of the search key words to refine the search criteria. Reference list of collected final sample of articles are perused to identify additional articles. It is difficult to obtain verifiable empirical data on the bond/monoline insurers or their insured products, especially for the structured finance sector. Most of the information available on data stream and firm’s quarterly financial reports for publicly traded monoline/bond insurers and credit rating reports are included to overcome this issue.

Demand for bond/monoline insurance still persists even in the USA. Although borrowing costs are low, obtaining bank loans would be challenging for municipalities and corporates with increased risks. Especially, given worldwide government stimulus on wages, most municipalities would possess reduced budgets for public finance. Monoline insurance can play a key role in financing such projects. Thus, it is important to understand their unique traditional and transformed business model and applicability during and post-COVID-19. Given the near extinction of bond/monoline insurers during the 2008 global financial crisis (GFC), an adequate framework for bond/monoline insurers as developed in this study is key for future business continuity.

There is significant interest, especially, from the industry on monolines as identified in our systematic review. Monoline insurance has major effects on taxpayers, government policies and bond investors. They aid in financing public finance projects that have significant societal impact. This study contributes by filling existing gaps in the literature, especially, from a behavioural, ethical and social perspective of the monolines, regulators, other stakeholders and new entrants to the industry during COVID-19. This study links prior finance theories to the impact of bond/monoline insurer’s during the 2008 GFC and their stakeholders involved that has societal implications.

This study can be differentiated from prior research on monoline insurers as follows: The study identifies, gaps, similarities, trends between prior academic and industry literature and develop a bond/monoline governance framework; identifies key failure and success factors during the 2008 GFC crisis to develop the governance framework and identify monolines’ potential during COVID-19; as opposed to most prior literature that only focus on one (Drake and Neal, 2011 analyse MBIA) or two key bond/monoline insurers, this study focuses on five key bond/monoline insurers in detail and all other key insurers as well in the empirical analysis section.

Deposit insurance is a key element in modern banking, as it guarantees the financial safety of deposits at depository financial institutions. It is necessary to have at least a dual fair premium rate system based on creditworthiness of financial institutions, as considering singular premium system for all banks will have moral hazard. This paper aims to develop theoretical and empirical model for calculating dual fair premium rates.

The definition of a fair premium rate in this paper is a rate that covers the operational expenditures of the deposit insuring organization, provides it with sufficient funds to enable it to pay a certain percentage share of deposit amounts to depositors in case of bank default and provides it with sufficient funds as precautionary reserves. To identify and classify healthier and more stable banks, the authors use credit rating methods that use two major dimensional reduction techniques. For forecasting nonperforming loans (NPLs), the authors develop a model that can capture both macro shocks and idiosyncratic shocks to financial institutions in a vector error correction model.

The response of NPLs/loans to macro shocks and idiosyncratic innovations shows that using a model with macro variables only is insufficient, as it is possible that under favorable economic conditions, some banks show negative performance due to bank level reasons such as mismanagement or vice versa. The final results show that deposit insurance premium rate needs to be vary based on banks’ creditworthiness.

The results provide interesting insight for financial authorities to set fair deposit insurance premium rate. A high premium rate reduces the capital adequacy of individual financial institutions, which endangers the stability of the financial system; a low premium rate will reduce the security of the financial system.

The purpose of this paper is to develop a model to hedge annuity portfolios against increases in life expectancy. Across the globe, and in the industrial nations in particular, people have seen an unprecedented increase in their life expectancy over the past decades. The benefits of this apply to the individual, but the dangers apply to annuity providers. Insurance companies often possess no effective tools to address the longevity risk inherent in their annuity portfolio. Securitization can serve as a substitute for classic reinsurance, as it also transfers risk to third parties.

This paper extends on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. Future mortality rates with the Lee-Carter-model and use the Wang-transformation to incorporate insurance risk are forecasted. Based on the percentile tranching method, where individual tranches are aligned to Standard & Poor's ratings, we price an inverse survivor bond. This bond offers fix coupon payments to investors, while the principal payments are at risk and depend on the survival rate within the underlying portfolio.

The contribution to the academic literature is threefold. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. Putting the principal at risk instead of the coupon payments, the insurer is supplied with sufficient capital to cover additional costs due to longevity. On the empirical side, the method for the German market is specified. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed. Finally, in a case study, the procedure to the annuity portfolio of a large German life insurer is applied and the price of hedging longevity risk is calculated.

To illustrate the implication of this bond structure, several sensitivity tests were conducted before applying the pricing model to the retail sample annuity portfolio from a leading German life insurer. The securitization structure was applied to calculate the securitization prices for a sample portfolio from a large life insurance company.

The findings contribute to the current discussion about how insurers can face longevity risk within their annuity portfolios. The fact that the rating structure has such a severe impact on the overall hedging costs for the insurer implies that companies that are willing to undergo an annuity securitization should consider their deal structure very carefully. In addition, we have pointed out that in imperfect markets, the retention of the equity tranche by the originator might be advantageous. Nevertheless, one has to bear in mind that by this behavior, the insurer is able to reduce the overall default risk in his balance sheet by securitizing a life insurance portfolio; however, the fraction of first loss pieces from defaults increases more than proportionally. The insurer has to take care to not be left with large, unwanted remaining risk positions in his books.

In this paper, we extend on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. To do so, we take the perspective of the issuing insurance company and calculate the costs of hedging in a four-step process. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. On the empirical side, we specify the method for the German market. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed.

The purpose of this paper is to investigate the effects of crop insurance premiums being determined by small samples of yields that are spatially correlated. If spatial autocorrelation and small sample size are not properly accounted for in premium ratings, the premium rates may inaccurately reflect the risk of a loss.

The paper first examines the spatial autocorrelation among county-level yields of corn and soybeans in the Corn Belt by calculating Moran's I and the effective spatial degrees of freedom. After establishing the existence of spatial autocorrelation, copula models are used to estimate the joint distribution of corn yields and the joint distribution of soybean yields for a group of nine counties in Illinois. Bootstrap samples of the corn and soybean yields are generated to estimate copula models with the purpose of creating sampling distributions.

The estimated bootstrap confidence intervals demonstrate that the copula parameter estimates and the premium rates derived from the parameter estimates can vary greatly. There is also evidence of bias in the parameter estimates.

Although small samples will always be an issue in crop insurance ratings and assumptions must be made for the federal crop insurance program to operate at its current scale, this analysis sheds light on some of the issues caused by using small samples and will hopefully lead to the mitigation of these small sample issues.

This article seeks to examine the reference yield calculation method used in crop insurance rating and provides recommendations that could potentially improve actuarial performance of the Federal crop insurance program.

Conceptual, numerical, and statistical analysis is utilized to evaluate the reference yield calculation method used in the US Federal crop insurance program.

The results suggest that reference yields, which at the time of this study are calculated using National Agricultural Statistics Service (NASS) data, do not accurately represent the average actual yields of the insured pool of producers in the Federal crop insurance program. In addition, it is found that not regularly updating these NASS‐based reference yields exacerbates this problem because these reference yields do not appropriately represent the current state of technological progress.

The empirical analysis leads this paper to recommend a reference yield calculation procedure that utilizes county‐average yields from the risk management agency (RMA) participation database and an approach that uses spatially aggregated average yields in cases when data for a particular county are sparse.

No previous study has investigated the reference yield calculation method in the Federal crop insurance program using both RMA and NASS data sets. Moreover, this study contributes to the small literature that examines various aspects of the actual production history (APH) rating platform and suggests refinements to improve actuarial performance.

The purpose of this paper is to examine the emerging Chinese credit rating agencies (CRAs), and their development, regulatory regime and challenges. The Chinese financial system has made many improvements; in particular, the regulatory regime has reached a more effective level. However, it should be admitted that some aspects still require further development. Compared with other developed markets, the Chinese credit rating industry is still young. Under these circumstances, questions are raised about the performance of the CRAs in China. Whether the legal framework is effective enough? A further point, in terms of the development, is what are the major obstacles lying ahead for the Chinese CRAs?

This paper will concentrate on the study of Chinese CRAs. Starting with a brief introduction and analysis on the Chinese CRAs, it will further examine the rating methodologies of the Chinese CRAs. Following this, the regulatory regimes will be analyzed in detail, from the perspectives of the securities, banking and insurance market. Moreover, the paper will identify the key problems under the current regulatory regime. Last but not least, a conclusion and some future suggestions for the development of the regulatory regime will also be made based on the earlier observations and study.

The current development stage and future reform requirement of the Chinese credit rating industry.

Provide a full dimension and in depth analysis on the Chinese credit rating industry.

The purpose of this research study is to determine whether flood-damaged residences located in the USA are remaining unrepaired because of the lack of flood insurance coverage. Unrepaired flooded dwellings are subsequently being foreclosed with mortgage-insurance claims being paid to lenders. This paper aims to examine if weather events that cause flooding impact the losses suffered by mortgage insurers and homeowners.

Two fully modified least squares regression models are done using losses experienced by two mortgage insurance companies. The AM Best insurance rating information for a 16-year period or years 2002–2017 is used to study whether the loss ratios experienced by two companies underwriting private mortgage insurance (PMI) are statistically correlated to National Flood Insurance Program (NFIP) claim levels. The assumption is that higher flood insurance claims are a proxy for more severe weather events during a particular year which results in flooding that damage residences.

The NFIP claims coefficient is positive and significant for both companies being examined. This indicates that the more serious the flooding event during a specific year, the higher the losses experienced by the private mortgage insurer. The R² results for the regression models were 0.673–0.695. The income variable has a negative coefficient which was significant. It indicates that falling income lead to rising mortgage insurer losses. The NFIP variable was significant with a positive coefficient.

The mortgage insurance industry is dominated by several companies at any point in time. During the 16-year study period, some companies have become insolvent, merged with other companies or recently started underwriting mortgage insurance. One company was diversified writing multiple lines of property insurance. There were only two insurers with complete financial information for the specified study period.

There are currently five mortgage insurers operating in the USA. A serious flood event could cause the insolvency of some of these companies. This would reduce the competition existing in the default insurance market. The financial markets for real estate loans price mortgages based on the availability and the ability to secure mortgage insurance for high loan-to-value properties. There is federal mortgage insurance available for certain types of residential loans.

There are a limited number of insurers writing flood insurance. These companies can pick or reject dwellings and/or commercial properties to underwrite for insurance. The goal of phasing out insurance through the NFIP may prove impossible to achieve. A flood event without insurance would cause serious financial consequences to property owners, loan delinquencies and could depress the local economy for years. Competition from private mortgage insurers may intensify the adverse selection already being experienced by the NFIP. Private insurers would select the lower risk flood applications leaving the more risky insurance to be covered by the NFIP.

Prior research focused on financial variables impacting PMI and weather factors affecting flood insurance claims. Financial ratios published in the AM Best rating guide for the USA and Canada were used to examine whether or not PMI losses are indirectly affected by flooding events as measured by NFIP variable. Comparing two separate lines of insurance and their impact on each other has not been studied by prior researchers.

The second major area of the so-called risk treatment is risk financing. Risk financing includes measures to finance the costs of losses, risks, and uncertainties. Historically, risk financing has been virtually synonymous with buying insurance. However, over time alternatives to insurance have evolved – self-insurance, pools, captives, large deductible programmes, finite insurance programmes, banking arrangements, and capital market-based solutions. The concept of risk financing has expanded to include products that address a range of financial risks such as interest rate and credit risk. These products include derivatives and some new innovative securities.

Today, the rapid development of the risk financing market has created several practical problems. Notably, regulatory and legal structures have not always kept pace with change, leading to much confusion about risk financing alternatives. Many products look and function almost identically to others, and yet history and custom have dictated very different treatment by regulators, tax authorities, and others. There is growing pressure for significant legal and regulatory realignment.

For newcomers to the field, risk financing measures can be thought of as existing on a continuum, ranging from pure retention (all losses paid directly out of pocket) to pure transfer (where a third party accepts and bears the full costs of risk). An important recognition of the continuum of risk financing is that there are no products that are fully retention or transfer, but rather a varying blend of the two. Hedging of risk, for example, is arguably here a near perfect blending of a retention and a transfer of risk.

The USDA’s Risk Management Agency (RMA) made several changes to the crop insurance products available to organic growers for the 2014 crop year. Most notably, a 5 percent premium surcharge was removed and organic-specific transitional yields (t-yields) were issued for the first time. The purpose of this paper is to use farm-level organic crop yield data to analyze the impact of these reforms on producer insurance outcomes and compare the insurance options for new organic growers.

This study uses a unique panel data set of organic corn and soybean yields to analyze the impact of organic crop insurance reforms. Actual Production History values and premium rates are calculated for each farm and crop yield sequence. Producer loss ratios and subsidized premium wedges are compared for yield, revenue and area-risk products before and after the instituted reforms.

Results indicate that RMA succeeded in improving the actuarial soundness of the organic insurance program, though further refinement of organic t-yields may be necessary to accurately reflect the yield potential of organic producers and avoid reductions in program participation.

This paper provides insight into the effectiveness of reforms intended to improve the actuarial soundness of organic crop insurance and demonstrates the effect that the reforms are likely to have on new and existing organic farms. Because this analysis uses data collected independently of RMA and includes farms that may or may not have purchased crop insurance, it avoids the self-selection problems that might affect analyses using crop insurance program data.