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Digital transformation and total factor productivity in insurance companies: a catalyst or inhibitor?
Abstract
Using data on 76 Chinese insurance companies from 2011 to 2020, this study investigates the impact of digital transformation (DT) on total factor productivity (TFP). We use the latent Dirichlet allocation (LDA) method to quantify the DT index within sample firms. Our analysis reveals a U-shaped relationship between the DT index and TFP, suggesting that insurance companies experience an initial decline in TFP at low levels of DT, followed by an eventual increase as the benefits of DT are realized. We also find the DT of most insurance companies is at the initial stage and they suffer poor efficiency. Our findings appear to be robust with respect to alternative reference documents, instrumental variable analysis, number of topics, and various subsamples. Furthermore, we identify and find three channels (management expenses, financial costs, and intangible assets) are statistically significant.
Risk attitude toward on-demand insurance: an experimental study
Abstract
On-demand insurance products cover risks for short periods of time via a smartphone or other electronic device. Such insurance contracts give policyholders the freedom to choose when to be insured in a flexible way. On-demand contracts may change the way risk is perceived. Therefore, we conduct an experiment and show that individuals can become exceptionally risk-averse when offered short-term insurance. We show two main reasons for this result: first, the underlying risk is often overestimated by the subjects due to a miscalculation of the loss probabilities. Second, the shorter valuation horizon of on-demand insurance contracts leads to myopic loss aversion.
A novel blockchain-based charitable model combined with insurance
Abstract
Existing blockchain-based charitable models face multiple challenges, like authenticating information uploaded to the blockchain, a lack of dispute resolution and corresponding execution mechanisms, legal barriers and low public engagement. To this end, we propose a novel blockchain-based charity model that introduces an insurance mechanism, which aims to enhance accountability, efficiency, availability and public participation. Specifically, our solution combines consortium blockchain with a semi-decentralised architecture (SDA), which enables more democratic supervision of charitable projects by dispersing verification data to all clients while maintaining the high efficiency, convenience and accountability of centralisation as well as the security and transparency of decentralisation. The model also incorporates smart contracts to automate the execution of insurance claims in case of disputes, significantly enhancing the efficiency and fairness of the claims process.
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Catastrophe insurance and solvency regulation
Abstract
Solvency regulation can prevent insurers from making decisions that are detrimental to policyholders. However, it can also discourage the purchase of insurance for catastrophic risks by causing prohibitive insurance loading due to high reinsurance coverage constraints. This paper examines this delicate trade-off. We show that a solvency regulation allowing some level of insurer default in catastrophic states can be a first-best policy. The default rate of this first-best policy varies depending on the risk line and market conditions. Our numerical simulations indicate that it is possible to closely approximate the first-best policy by implementing a straightforward solvency regulation, considering insurers’ Expected Shortfall and Value at Risk, the reinsurance loading, and policyholders’ risk aversion. Therefore, reforming current solvency regulations in this direction could improve policyholders’ welfare.
Adverse selection in tontines
Abstract
Several recent studies have cited the theoretical work of Valdez et al. [Insur: Math Econ 39(2):251–266, 2006] as evidence that there is less adverse selection in tontine-style products than in conventional life annuities. We argue that the modeling work and results of Valdez et al. [Insur: Math Econ 39(2):251–266, 2006] do not unconditionally support such a claim. Conducting our own analyses structured in a similar way but focusing on the relative instead of absolute change in annuity vs. tontine investments, we find that an individual with private information about their own survival prospect can potentially adversely select against tontines at the same, or even higher levels than against annuities. Our results suggest that the investor’s relative risk aversion is the driving factor of the relative susceptibility of the two products to adverse selection.
The Riccati tontine: how to satisfy regulators on average
Abstract
This paper introduces a novel accumulation-based tontine, which we have called the Riccati tontine, named after two Italians: mathematician Jacobo Riccati (b. 1676, d. 1754) and financier Lorenzo di Tonti (b. 1602, d. 1684). The Riccati tontine is another way of pooling and sharing longevity risk, but is different from competing designs and historical tontines in two key ways: First, in the Riccati tontine, the representative investor is expected—although not guaranteed—to receive their money back, if they die or lapse. This design feature, in which an investor exiting early will receive their initial deposit back on average, is also strongly encouraged by regulators. The second innovation in a Riccati tontine is that the underlying funds within the pool are deliberately not indexed to the market. Instead, the underlying investments are selected so that portfolio return shocks are negatively correlated with stochastic mortality. This negative correlation to mortality and positive correlation to longevity reduces the volatility of outcomes and typically will improve utility. In addition to explaining the rationale for non-indexed investments, or effectively active management, the paper provides a mathematical proof that the required recovery schedule satisfies a first-order ODE that is quadratic in the unknown function, which (yes) is known as a Riccati equation.