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Purpose This paper aims to undertake a thematic review of academic papers on financial technology (FinTech) to identify three broad categories for the purpose of classifying extant literature. The paper summarizes the research and findings in this emerging field. Thereafter, it identifies the gaps and provides directions for further research. Simultaneously, the paper collates technical terms related to FinTech that appear repeatedly in each category and explains them. Finally, the study highlights the lessons that growing FinTech firms and their regulators can learn from the experiences of their counterparts across the globe. Design/methodology/approach A systematic review of literature consisting of 130 studies (social science research network [SSRN]-29 papers, Scopus-81, other sources-20) on FinTech is carried out in this thematic paper. Findings This thematic paper divides FinTech into three themes, i.e. financial industry, innovation/technology and law/regulation. The paper suggests that a thorough impact of FinTech on various stakeholders can be understood using three dimensions, namely, consumers, market players and regulatory front. It is noted that FinTech is in its nascent phase and is undergoing continuous development and implementation through product and process innovation, disruption and transformation. Research limitations/implications The paper reports that FinTech promises huge potential for further study by various stakeholders in the FinTech industry – from academia to practitioners to regulators. Practical implications The paper summarizes lessons that could be of significance for FinTech users, producers, entrepreneurs, investors, policy designers and regulators. Originality/value The paper is believed to add value to the understanding of FinTech in light of the emerging threats and opportunities for its various stakeholders.

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We investigate how investor protection, government quality, and contract enforcement affect risk taking and performance of insurance companies from around the world. We find that better investor protection results in less risk taking, as do higher quality government and greater contract enforceability. However, we find only limited evidence that these factors influence firm performance. We conclude that better overall operating environments result in less risk taking by insurers without the concomitant decline in performance. These results imply that better investor protection environments benefit policyholders and outside stockholders by preventing corporate insiders from expropriating wealth from policyholders and outside stockholders.

Heterogeneous distributed computing systems often must operate in an environment where system parameters are subject to uncertainty. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. We present a methodology for quantifying the robustness of resource allocations in a dynamic environment where task execution times are stochastic. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of a stochastic dynamic environment. A Bayesian regression model is fit to the combined results of the three heuristics to demonstrate the correlation between the stochastic robustness metric and the presented performance metric. The correlation results demonstrated the significant potential of the stochastic robustness metric to predict the relative performance of the three heuristics given a common objective function.

We examine corporate purchases of Directors and Officers (D&O) liability insurance and find that in addition to governance quality it contains managers' private information. In particular, we find that insider control in excess of insider share holdings is jointly associated with lower D&O coverage limits and higher firm performance. The result holds when deductibles, corporate governance characteristics and litigation risk factors are controlled for. Our finding is consistent with an asymmetric information hypothesis in financial markets which posits that managers possess private information about firm risk. Our findings differ from existing literature that shows that D&O insurance purchases primarily reflect firm's governance quality and litigation risk. The evidence supports the policy prescription advanced in earlier studies which call for mandatory public disclosure of D&O insurance purchases since it contains additional information for the market.

Heterogeneous parallel and distributed computing systems frequently must operate in environments where there is uncertainty in system parameters. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. In such an environment, the execution time of any given task may fluctuate substantially due to factors such as the content of data to be processed. Determining a resource allocation that is robust against this uncertainty is an important area of research. In this study, we define a stochastic robustness measure to facilitate resource allocation decisions in a dynamic environment where tasks are subject to individual hard deadlines and each task requires some input data to start execution. In this environment, the tasks that cannot meet their deadlines are dropped (i.e., discarded). We define methods to determine the stochastic completion times of tasks in the presence of the task dropping. The stochastic task completion time is used in the definition of the stochastic robustness measure. Based on this stochastic robustness measure, we design novel resource allocation techniques that work in immediate and batch modes, with the goal of maximizing the number of tasks that meet their individual deadlines. We compare the performance of our technique against several well-known approaches taken from the literature and adapted to our environment. Simulation results of this study demonstrate the suitability of our new technique in a dynamic heterogeneous computing system.

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