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The purpose of this paper is to develop a loan insurance pricing model allowing for the skewness and kurtosis existing in underlying asset returns.

Using the theory of Gram-Charlier option, the authors first derive a closed-form solution of the Gram-Charlier pricing model. To address the difficulties in implementing the pricing model, the authors subsequently propose an iterative method to estimate skewness and kurtosis in practical application, which shows a relatively fast convergence rate in the empirical test.

Not only the theoretical analysis but also the empirical evidence shows that the effects of skewness and kurtosis on loan insurance premium tend to be negative and positive, respectively. Furthermore, the actual values of skewness and kurtosis are usually negative and positive, respectively, which leads to the empirical result that the pricing model ignoring skewness and kurtosis substantially underestimates loan insurance premium.

This paper proposes a loan insurance pricing model considering the skewness and kurtosis of asset returns, in which the authors use the theory of Gram-Charlier option. More importantly, the authors further propose a novel iterative method to estimate skewness and kurtosis in practical application. The empirical evidence suggests that the Gram-Charlier pricing model captures the information content of skewness and kurtosis.

This study aims to investigate insurance policy loan applicant characteristics. Additionally, it reveals the behaviour patterns of heavy users who have applied for at least two loans. A policy loan prediction model is established which is designed to increase loan application rates.

The proposed model is implemented using data‐mining techniques and comprises two mechanisms: a business rule generator and a recommendation mechanism. Two analytical approaches, the C.5 and Apriori algorithm, are employed to analyse the profile and browsing log DBs of insured individuals. The prediction model is verified by actual data from a Taiwanese insurance company.

The data‐mining results reveal that five attributes are ultimately used to establish the prediction model, namely: gender, marketing channel, insurance type, area of policy owner, and assumed interest rate. Additionally, the analytical results also indicate that insured individuals apply for loans as a result of arbitrage inducement. The accuracy of loan applicant prediction can exceed 70 per cent. Finally, some interesting patterns emerge for heavy users, such as the finding that loan applicants are used to applying for loans continuously (loan application repetition is on average two to three times).

Some policy owners who are unfamiliar with the web interface prefer to contact insurance personnel directly to discuss their insurance needs, and thus no browsing records are available for such users. In such cases only the profile could be collected and analysed.

The proposed model enables insurance firms to locate potential loan applicants according to the data‐mining results. As in the illustration scenario in the paper, insurance personnel can contact these potential loan applicants before they submit loan applications to the bank. Additionally, loan‐related information is provided for online insurance users based on their browsing logs. The loan application rate is thus expected to increase, along with interest revenue.

As long as the policy proceeds, the interest income from the policy loan seems to be a good option for extending insurance company operational earnings. Understanding the characteristics of loan applicants will provide helpful information. Besides, the proposed mechanism will be more appropriate to online users, who are unwilling to deal with unwanted information.

The assets of bankrupt firms are usually sold to unsuitable buyers at an extremely discounted price. Aiming to reduce the bankruptcy cost, the purpose of this paper is to propose a novel insurance system for associated loans.

In this insurance system, the joined firms are from the same industry and have a responsibility to buy the assets of potentially bankrupt firms at a relatively high price, because they could make better use of the assets than the buyers outside the industry. Further, the authors use the Shapley value to address the problem of bankruptcy cost allocation and additionally employ the method of Monte Carlo simulation to derive the numerical solution of the insurance premium of bankruptcy cost.

First, the relatively healthy and solvent firms in the insurance system could gain a larger proportion of benefits derived from the reduced cost of default, interestingly, the more so when the external cost of default is larger. Second, given the positive relationship between bankruptcy cost and asset correlation in practice, lenders and insurers face a trade-off to balance the cost against the benefit of asset correlation. Third, insurance premiums and bankruptcy costs decrease with the number of firms participating in this insurance system.

This paper proposes a novel insurance for associated loans, in which joined firms can pay a relatively low insurance premium due to the realization of reducing bankruptcy cost.

Studies of Depression-era financial remediation have generally focused on federal deposit insurance and the provision of equity to banks by the Reconstruction Finance Corporation (RFC). This paper broadens the concept of financial remediation to include other programs – RFC lending, federal guarantees of farm and home mortgages, and the elimination of interest on demand deposits – and other intermediaries – savings and loans, mutual savings banks, and life insurance companies. The benefits of remediation or the amounts potentially at risk to the government in these programs are calculated annually and allocated to the various intermediaries. The slow remediation of real estate loans (two-thirds of these intermediaries' loans) needs further study with respect to the slow economic recovery. The paper compares Depression-era remediation with efforts during the 2008–2009 crisis. Today's remediation contrasts with the 1930s in its speed, magnitude relative to GDP or private sector nonfinancial debt, the share of remediation going to nonbanks, and emphasis on securities markets.

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.

Many governments are taking measures in support of small and medium-sized enterprises (SMEs) to mitigate the economic impact of the COVID-19 outbreak. This paper presents a theoretical model for evaluating various government measures, including insurance for bank loans, interest rate subsidy, bridge loans and relief of tax burdens.

This paper distinguishes a firm's intrinsic value and book value, where a firm can lose its intrinsic value when it encounters cash-flow crunch. Wang transform is applied to (1) calculating the appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs, (2) describing the frailty distribution for SMEs and (3) defining banks' underwriting capability and overlap index in risk selection.

Government support for SMEs can be in the form of an appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs.

More available data on bank loans would have helped strengthen the empirical studies.

This paper makes policy recommendations of establishing policy-oriented banks or investment funds dedicated to supporting SMEs, developing risk indices for SMEs to facilitate refined risk underwriting, providing SMEs with long-term tax relief and early-stage equity-type investments.

The model highlights the importance of providing bridge loans to SMEs during the COVID-19 disruption to prevent massive business closures.

This paper provides an analytical framework using Wang transform for analyzing the most effective form of government support for SMEs.

The purpose of this study was to, using a case study research design informed by organizational economics theory, to examine the prospects for micro-insurance in promoting micro-credit in a low-income Anglophone country in sub-Saharan Africa – The Gambia. Two main research questions are addressed: first, what is the most appropriate micro-finance institution (MFI) organizational structure to maximize the economic benefits of micro-insurance? Second, what are the financial management and wider economic benefits of the use of micro-insurance by MFIs?

To address our two research questions, we used a semi-structured interview protocol, informed by the organizational economics literature, to interpret the data collected from our field cases. We believe that these intrinsic qualities of case study methodology are particularly apt in the present study, given the complex and emergent nature of micro-finance and micro-insurance in low-income countries such The Gambia. By focusing on case studies in a single country, we also to some extent help control for variations in business environment that could confound interpretations of field data obtained from different jurisdictions.

The results of our study suggest that the mutual (cooperative) structure of credit unions is likely to be the most cost-efficient and effective organizational form for reducing information asymmetries, agency problems and transaction costs. We also observe that micro-insurance can help reduce the risk of loan defaults, thereby increasing returns on savings and lowering the costs of debt. As such, micro-insurance stimulates the demand–supply of financial intermediation in less developed countries and so helps promote economic development. In addition to contributing new insights, our findings have potentially important commercial and public policy implications.

We acknowledge that our research is subject to inherent limitations such as the focus on three interviews in three different types of MFI organization while excluding other structural forms of organization such as government-owned/sponsored organizations. Nonetheless, the organizational characteristics of the cases examined in the present study are representative of most MFIs in developing countries. Given the prevalent hierarchical nature of corporate systems in sub-Saharan Africa, the views of the interviewees are also deemed to reflect those of other board members. Nonetheless, we acknowledge that the conclusions from our research may need to be tempered in line with these inherent limitations with the research approach adopted.

The insights obtained from our Gambia-based research could be generalized to developing countries elsewhere in sub-Saharan Africa, and indeed, other parts of the developing world. Consequently, the study could be of interest and relevance to international financiers (e.g. the World Bank), aid agencies, governments and other development organizations.

Despite its evident business and development potential, academic management research on micro-insurance, and in particular, its role in supporting micro-finance initiatives, is still very much at an embryonic stage. Our study thus seeks to fill this knowledge gap.

The purpose of this paper is to review the most recent scientific literature on the determinants explaining the demand for index-insurance, the impact of index-insurance and the existing links between insurance and credit. In this meta-analysis, the authors identify key discoveries on the potential of index-insurance in enhancing credit supply for smallholders and thus farm productivity.

Following a systematic literature search in Scopus and Web of Science, relevant empirical articles were identified by using the following criteria search algorithm: “insurance” and (“weather” or “micro” or “area?based” or “rain*” or “livestock” or “index”), and ((“empiric*” or “experiment” or “trial” or “RCT” or “impact”) or (“credit” or “loan*” or “debt” or “finance”)). The authors identified 1,133 related papers, 110 of which were selected as closely matching the study criteria. After removing duplicates and analysing each document, 45 papers were included in the current analysis. The framework for addressing insurance and credit issues, in the paper, entails three subsequent themes, namely, adoption of insurance, impact of insurance and links between insurance and credit.

It is not confirmed yet that demand for insurance is indeed hump-shaped in risk aversion and the functional form of this relationship should be tested in more detail. This also holds for the magnitude of the effect of trust and education on actual demand. Furthermore, it is unclear to what extent other risk mitigation strategies form complements or substitutes to index-insurance. Lastly, the interaction between basis risk and price is important to the design of index-insurance products. If basis risk and price elasticity are indeed highly correlated, products that diminish basis risk are crucial in increasing demand. On the impact of bundled products, e.g. combination of insurance and credit, limited empirical research has been conducted. For example, it is unknown to what extent credit suppliers would react to the insured status of farmers or what the preferences of farmers are when it comes to a mix of financial products. In addition, several researchers have suggested that microfinance institutions or banks could insure themselves against covariate risk, yet no empirical evidence about this insurance mechanism has been conducted so far.

The authors based the research on scientific literature uploaded in Scopus and Web of Science. Other potentially insightful grey literature was not included due to lack of accessibility. Given the research findings, there is plenty of opportunity for further research particularly with regard to the effects of bundled products, e.g. insurance plus credit, on demand for index-insurance, supply of credit, loan conditions and impact on farm productivity and farmers’ well-being.

Microfinance institutions, insurance companies, NGOs, research institutions and universities, particularly in developing countries, will be interested to learn about the systematic review of scientific research done in the area of insurance and credit for agriculture and the possibilities for application in their own practice of supplying these financial products.

A rigorous understanding of the potential of index-insurance and credit is essential for identifying the right mix of financial products that help smallholder farmers to increase farm productivity and their own well-being.

The paper is valuable due to its rigorous evaluation of existing theoretical and empirical research around issues explaining the degree of adoption and impact of index-insurance and that of bundled financial products (i.e. index-insurance plus credit). The paper has the potential to become essential reading for academics, practitioners and policy-makers interested in researching and putting in practice the best options leading to greater farm productivity and well-being in developing countries.

The purpose of this paper is to shed light on the causes of the 2007‐2009 mortgage crisis, liquidity crisis, stock market volatility in the USA and their spillover effects on the global economy.

The paper critically reviews the 2007‐2009 financial crisis from both academic and practitioners' viewpoints.

The paper explores how the liquidity crisis has evolved with the advent of poorly supervised financial products, especially the credit default swaps and subprime mortgage loans. Further, it analyzes the laxity in regulations that encouraged high financial leverages, shadow banking system and excessive stock market volatility and worsened the recent financial crisis.

The implication of this paper is to understand numerous policy reforms that will help the global capital markets to be more transparent and less vulnerable to systematic risks; the suggested policy reforms may also help to prevent such financial calamities in the future.

The purpose of this paper is to provide an insurance framework to address the challenge of managing default risk for lenders providing credit to small and micro businesses.

A theoretical model is developed showing how mircrofinance lenders can better manage the default risks of small and micro businesses, which assists lenders in sustainably providing affordable microfinance.

The model explains how to determine the feasible range of insurance premiums to advise lenders on the appropriate price for microinsurance protecting against small and micro business default. This will enable microfinance institutions to better manage default risk, and thereby provide sustainable and accessible microfinance assistance to small and micro businesses.

The need for microfinance is essential to support small and micro businesses. The insurance framework assists financial institutions in managing default risk of small and micro businesses, enhancing sustainability of these critical financing channels, and supporting the economic development of society in both the developed and developing worlds. The insurance framework proposed will help both policymakers and financial institutions to make better economic decisions, thereby serving small and micro businesses.

This is the first study in the area of microfinance to propose a way to solve the challenge of providing sustainable mircrofinance services and mitigating small and micro businesses’ difficulty in receiving the financial help they need.