IAIS is seeking feedback on the draft Issues Paper on the use of big data analytics in insurance. The paper focuses on the use of algorithms and advanced analytics capabilities by insurers to make decisions based on patterns, trends, and linkages and examines the availability of new alternative data sources (collectively referred to as big data analytics) to insurers. The paper builds on the IAIS Issues Paper (published in November 2018) on the increasing digitalization in insurance and the potential impact of this digitalization on consumer outcomes by focusing more on issues related to the use of personal and other data by insurers. Feedback on this consultative document is invited by October 16, 2019.
To help understand the potential benefits and risks to consumers associated with the use of big data analytics by insurers, the paper considers the manner in which insurers are now able to collect, process, and use data across various stages of the insurance product lifecycle, namely product design, marketing, sales and distribution, pricing and underwriting, and claims handling. The paper also makes certain observations about the potential implications of the use of big data analytics in insurance, for supervisors. Furthermore, in light of the outcomes for the fair treatment of customers described in the Insurance Core Principles (ICPs) 18 and 19, this paper makes certain observations about the potential implications for supervisors as a result of the use of big data analytics in insurance.
The paper observes that the increased availability of data and enhanced processing capabilities now accessible to insurers can result in a number of benefits. On the other hand, the paper also highlights that the complexity and opacity of algorithm technology and the ability of insurers to customize product offerings to an individual level could potentially result in risks to individual customers as well as to the insurance sector, for which supervisors may need to devise appropriate responses. Additionally, the paper suggests that supervisors think about whether there is a need to enhance governance, oversight, and third-party risk management requirements specific to the use of algorithms for big data analytics purposes.
Comment Due Date: October 16, 2019
Keywords: International, Insurance, BDA, Big Data, ICPs, Suptech, Insurtech, IAIS
Previous ArticlePRA to Amend Supervisory Statement on Counterparty Credit Risk
HKMA announced that enhancements will be made to the Special 100% Loan Guarantee of the SME Financing Guarantee Scheme (SFGS) and the application period will be extended to December 31, 2021.
EBA launched consultations on the regulatory and implementing technical standards on cooperation and information exchange between competent authorities involved in prudential supervision of investment firms.
BoE has set out a three-phased plan to transform data collection from the UK financial sector over the next decade.
BIS recently made a couple of announcements with respect to the planned and ongoing work in the area of financial technology.
ESRB updated the list of national macro-prudential measures applied by each member state in the European Economic Area.
BoE has set out results of a survey on the impact of COVID-19 events on the use of machine learning and data science.
In response to a request from the European Council and Parliament, ECB published an opinion on the proposed regulation on markets in crypto-assets.
APRA announced the updated aggregate amounts for the 2021 Committed Liquidity Facility (CLF) established between the Reserve Bank of Australia (RBA) and certain locally incorporated authorized deposit-taking institutions that are subject to the Liquidity Coverage Ratio (LCR).
ECB published supervisory Memorandums of Understanding (MoUs) with UK as well as other European and non-European authorities.
EIOPA identified business model sustainability and adequate product design as the two EU-wide strategic supervisory priorities.