大數據時代下保險監理之新規範：以消費者保護與社會效用為核心

The New Rules for Insurance Regulation in the Age of Big Data：Focusing on Consumer Protection and Social Utility

資訊科技的發展進步到得以記錄有關個人資訊，並大量蒐集個人資訊形成數據集；人們藉由使用演算法對其進行相關分析，以作為預測未來事務之用。此等大數據驅動之預測性分析的使用，正在改變社會上所有產業及參與者之實務行為。保險乃是對於未來損失之風險分散與移轉制度，正確的大數據分析，能妥適地達到保險的核心功能，使得保險業的行銷、核保與定價及理賠的管理，都能更有效率，使其獲利能力增加。雖然，目前支持者對於大數據分析的宣傳都是好的面向，但其亦有潛在的負面影響，此部分卻很少受到注意。保險業使用大數據分析，對精算公平、損失預防、隱私保障、個人自主、反歧視、公平、社會效用最大化，不僅有正面的影響，亦可能有反面的效果並因此造成現行監理規則的失靈，而導致對消費者保護不足。藉由參酌國際上及美國之最新發展，本文將建構大數據分析於保險業運用產生之正、反面影響之理論基礎，並參酌國際保險監理官協會所提出之報告、建議，以及美國保險監理官協會所頒布之模範法，提出適合我國之相關建議，以使得我國保險監理之規範，能夠因應大數據時代之預測性分析的發展，不僅使得保險消費者得到適當的保護，亦使保險發揮社會效用最大化之功能。

The development of information technology advances it possible to record information about individuals and collect a large amount of individual information to form a dataset; people analyze data by algorithms for the purpose of predicting the affairs in the future. The uses of big data-driven predictive analytics are transforming the way that practical behaviors are conducted by all sectors of the economy and participants in society. Insurance is a system to transfer and diversify the exposure of future loss. The correct big data analytics can properly achieve the core functions of insurance and increase the efficiency of the operations by the insurance industry in marketing, underwriting and pricing and claims management to enhance its profitability. Although the advocates of big data analytics have touted its potential benefits, there are as well potential negative impacts which have received less attention. Insurers’uses of big data analytics will have impacts on the following aspects, such as actuarial fairness, loss prevention, individual autonomy, non-discrimination, justice, and social utility maximization. It will not only have a positive impact but may also have a negative effect which leads to the failure of current regulatory rules and insufficiency of consumer protection. With references of the latest developments in the world and the United States, the author constructs a theoretical basis for the positive and negative effects of big data analytics in insurance industry. In addition, by taking into the related papers and recommendations issued by International Association of Insurance Supervisors and the Model Law drafted by National Association of Insurance Commissioners in the United States, some suggestions fit to our legal system will be indicated so that the legal system of insurance regulation in Taiwan can respond to the development of big data predictive analytics, which will not only provide proper protection to insurance consumers but also achieve the function of social utility maximization in insurance.