Pricing in Microinsurance Markets

This paper discusses the adequacy of insurance for managing cyber risk. To this end, we extract 994 cases of cyber losses from an operational risk database and analyze their statistical properties. Based on the empirical results and recent literature, we investigate the insurability of cyber risk by systematically reviewing the set of criteria introduced by Berliner (1982). Our findings emphasize the distinct characteristics of cyber risks compared to other operational risks and bring to light significant problems resulting from highly interrelated losses, lack of data, and severe information asymmetries. These problems hinder the development of a sustainable cyber insurance market. We finish by discussing how cyber risk exposure may be better managed and make several suggestions for future research.

show abstract

“…Detailed results are available from the authors upon request. 46 See, e.g., Böhme (2005), Biener (2013). 47 See Baer and Parkinson (2007).…”

Section: Ddosmentioning

confidence: 99%

Insurability of Cyber Risk: An Empirical Analysis

Biener

Eling

Wirfs

2014

Geneva Pap Risk Insur Issues Pract

Self Cite

260

148

View full text Add to dashboard Cite

show abstract

“…Second, plant growth models have been employed to simulate the impact of risk factors on crop yields (Deng et al 2008); however, these models are complex and difficult to calibrate and also contain a lot of parameters which have to be estimated for each region separately. Third, the use of expert knowledge has been proposed as a general response to cope with poor statistical data in bank risk management and insurance pricing (Alderweireld, Garcia, and Léonard 2006;Biener 2013). In the past, expert knowledge for the quantification of insurance risk was mainly used on an ad hoc basis without invoking a formal mathematical framework (Shevchenko and Wüthrich 2006).…”

Section: Introductionmentioning

confidence: 99%

Can expert knowledge compensate for data scarcity in crop insurance pricing?

2015

View full text Add to dashboard Cite

Abstract:Although there is an increasing interest in index-based insurances in many developing countries, crop data scarcity hinders its implementation by forcing insurers to charge higher premiums. Expert knowledge has been considered a valuable information source to augment limited data in insurance pricing. This article investigates whether the use of expert knowledge can mitigate model risk which arises from insufficient statistical data. We adopt the Bayesian framework that allows for the combination of scarce data and expert knowledge, to estimate the risk parameter and buffer load. In addition, a benchmark for the evaluation of expert information is created by using a richer dataset generated from resampling. We find that expert knowledge reduces the parameter uncertainty and changes the insurance premium in the correct direction, but that the effect of the correction is sensitive to different strike levels of insurance indemnity.

show abstract

“…These discussions also set the “rules of the game”, based on adherence to transparent insurance principles (Wrede and Phily, n.d., pp. 11–12), and enable negotiations of the scope of the package to suit the price, when the rate‐making techniques use clear macro‐level, meso‐level and micro‐level data (Biener, ).…”

Section: Lessons Learned During Twenty Years Of Implementing Microinsmentioning

confidence: 99%

Microinsurance: A short history

Dror

2019

Int Social Security Review

View full text Add to dashboard Cite

Twenty years ago, the International Social Security Review published an article that introduced a new term to the vocabulary of development and social protection: Microinsurance. Now, twenty years later, it is suitable to take stock of the contribution of microinsurance towards promoting coverage and social security. The article reviews the main insights gained from 20 years of implementation, including a clear expression of the value proposition of health microinsurance, understanding the demand for microinsurance, the business process for successful implementation, and conditions that must be satisfied for scaling and sustainable operations. It also explains the context that led to a considerable divergence in the microinsurance space. The article offers a discussion of unresolved issues and thoughts about the future of microinsurance. The conclusion of this article is that microinsurance can flourish when the necessary four pillars for its implementation exist, namely mainstreaming through political support, enhanced insurance literacy of the customers, technical assistance to self‐administer the schemes, and availability of seed capital. The sufficient additional condition is that customers perceive microinsurance as offering welfare gains that cannot be obtained by other means.

show abstract

Pricing in Microinsurance Markets

Cited by 21 publications

References 59 publications

Insurability of Cyber Risk: An Empirical Analysis

Insurability of Cyber Risk: An Empirical Analysis

Can expert knowledge compensate for data scarcity in crop insurance pricing?

Microinsurance: A short history

Contact Info

Product

Resources

About