在开放金融的世界里,客户愿意共享数据吗?对数据驱动型保险业务的分析

IF 4 3区 管理学 Q2 BUSINESS Eurasian Business Review Pub Date : 2024-03-18 DOI:10.1007/s40821-024-00263-w
Laura Grassi
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引用次数: 0

摘要

在金融系统中,客户共享数据的意愿至关重要,否则银行和保险公司就无法利用客户数据。现在的关键步骤是了解客户是否愿意共享数据以及共享数据的形式。在本研究中,我们调查了客户与保险公司分享各种数据(关于身体健康、家庭、驾驶风格、旅行、家庭、社交网络)以换取不同回报(定制产品和服务、降低保险理赔风险以及根据个人习惯和行为调整保险费)的意愿。通过对网络调查中的 1501 个回答应用隐私计算框架,我们发现,奖励(尤其是经济奖励,如保险费优惠)在推动客户决定是否共享数据方面发挥着关键作用。此外,客户会将要求他们共享的数据与不同程度的隐私联系起来,从而影响他们共享数据的意愿。我们还发现,当客户被要求分享各种数据以换取不同回报时,他们的个人创新能力也会发挥作用。我们的研究结果表明,在数据驱动的保险业务中,以不同的奖励换取特定类型的数据可以帮助公司最大限度地降低 "数据获取成本",并最大限度地收集数据。在开放数据时代,保险公司可以探索细分市场的许多机会,但如果分析和人工智能模型建立在这些前提之上,可能会出现新的金融排斥,从而导致潜在的偏见和误读。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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In a world of Open Finance, are customers willing to share data? An analysis of the data-driven insurance business

In the financial system, the customers’ willingness to share their data is pivotal, because otherwise, banks and insurance companies are powerless to build on customer data. The key step now is to understand whether there is such willingness and what form it takes. In this study, we investigate how willing customers are to share various kinds of data (on physical health, home, driving style, travel, family, social networks) with their insurance company, in return for different rewards (customised products and services, reduced insurance claims risk and insurance premiums adjusted to personal habits and behaviour). Applying the privacy calculus framework to 1501 responses in a web-based survey, we found that rewards, especially when financial, such as insurance premium benefits, play a pivotal role in driving customer decisions about sharing data. Furthermore, customers associate the data they are asked to share with different levels of privacy, influencing their willingness to share. We also found that, when customers are asked to share various kinds of data in return for different rewards, their own personal innovativeness comes into play. Our findings suggest that, in the data-driven insurance business, different rewards offered in return for specific types of data could help companies minimise the “data acquisition cost” and maximise the data collected. In the era of open data, insurers can explore the many opportunities for segmentation, but new kinds of financial exclusion could emerge, resulting in potential biases and thus misinterpretations should analytics and artificial intelligence models be built upon these premises.

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来源期刊
CiteScore
6.90
自引率
11.40%
发文量
32
期刊介绍: The Eurasian Business Review (EABR) publishes articles in Industrial Organization, Innovation and Management Science. In particular, EABR is committed to publishing empirical articles which provide significant contributions in the fields of the economics and management of innovation, industrial and business economics, corporate governance and corporate finance, entrepreneurship and organizational change, strategic management, accounting, marketing, human resources management, and information systems. While the main focus of EABR is on Europe and Asia, papers in the fields listed above on any region or country are highly encouraged. The Eurasian Business Review is one of the two official journals of the Eurasia Business and Economics Society (EBES) and is published quarterly.
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