Big Data refers to massive databases of information about (millions) of individual consumers, and data mining (rooting around the data looking for any type of pattern)—all packaged into some kind of scoring model. An insurer might use all types of non-insurance databases of personal consumer information for marketing, pricing, and claims settlement.
Insurers have always been in the data collection and data management business, but historically the data collected was limited. In the past decade, insurers started utilizing credit information and data mining, collecting social security numbers and non-insurance data such as web browsing history or online shopping habits, and using new categories of insurance data such as more granular claims data, drones, or telematics. The Center for Economic Justice has advocated for greater consumer disclosure and control over the personal data collected by insurers, for greater security and protection of these personal data by insurers and for meaningful disclosure and redress if the personal data are lost by or stolen from insurers.
Insurer’s use of big data has huge implications for fairness, access, and affordability of insurance. Despite insurers’ claims that algorithms are “objective,” Big Data algorithms can easily reflect and perpetuate historic unfair discrimination. In a 2004 study, the Missouri Department of Insurance found that the single best predictor of the average insurance credit score in a zip code was the size of the minority population in the ZIP code.
The Center for Economic Justice believes that insurers’ use of Big Data holds great opportunities to improve availability and affordability of insurance, to improve transparency in insurance sales and claims settlement, and to promote partnership between consumers and insurers to prevent losses and promote resiliency and sustainability. But such outcomes are not automatic. Without public policy guardrails, insurers will use Big Data in the opposite direction—resulting in less transparency and less accountability to consumers.
Insurer’s use of Big Data poses a huge challenge to state insurance regulation. Big Data and associated algorithms radically increases the market power of insurers, both versus regulators and versus consumers. Regulators face huge challenges in their ability to keep up with changes and protect consumers from unfair practices. CEJ continues to hold insurers accountable for their practices, to improve the available market monitoring tools for insurance regulators, and to increase disclosure of insurer Big Data practices. We aim to stop unfair practices that undermine insurance availability and affordability.
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| 947 downloads | 1.0 | Dana Glass | 2018-06-21 12:24 | ||
| 1230 downloads | 1.0 | Dana Glass | 2018-06-21 12:23 | ||
| 848 downloads | 1.0 | Dana Glass | 2018-05-15 12:23 | ||
| 1130 downloads | 1.0 | Dana Glass | 2018-05-03 12:17 | ||
| 955 downloads | 1.0 | Dana Glass | 2018-04-06 11:52 | ||
| 836 downloads | 1.0 | Dana Glass | 2018-04-06 11:50 | ||
| 918 downloads | 1.0 | Dana Glass | 2018-03-20 11:53 | ||
| 781 downloads | 1.0 | Dana Glass | 2018-03-07 11:47 | ||
| 789 downloads | 1.0 | Dana Glass | 2018-03-01 12:21 | ||
| 1130 downloads | 1.0 | Dana Glass | 2018-03-01 12:18 | ||
| 837 downloads | 1.0 | Dana Glass | 2017-12-03 20:55 | ||
| 848 downloads | 1.0 | Dana Glass | 2017-09-21 20:57 | ||
| 835 downloads | 1.0 | Dana Glass | 2017-09-18 20:58 | ||
| 880 downloads | 1.0 | Dana Glass | 2017-09-10 20:56 | ||
| 766 downloads | 1.0 | Dana Glass | 2017-08-15 21:00 | ||
| 804 downloads | 1.0 | Dana Glass | 2017-08-14 20:59 | ||
| 885 downloads | 1.0 | Dana Glass | 2017-08-08 21:01 | ||
| 910 downloads | 1.0 | Dana Glass | 2017-08-06 20:57 | ||
| 724 downloads | 1.0 | Dana Glass | 2017-05-25 14:36 | ||
| 796 downloads | 1.0 | Dana Glass | 2017-05-24 14:33 | ||
| 816 downloads | 1.0 | Dana Glass | 2017-04-28 14:47 | ||
| 818 downloads | 1.0 | Dana Glass | 2017-04-24 15:04 | ||
| 836 downloads | 1.0 | Dana Glass | 2017-04-08 15:26 | ||
| 914 downloads | 1.0 | Dana Glass | 2017-04-08 15:25 | ||
| 786 downloads | 1.0 | Dana Glass | 2017-03-03 15:13 | ||
| 781 downloads | 1.0 | Dana Glass | 2017-01-05 14:52 | ||
| 761 downloads | 1.0 | Dana Glass | 2016-10-25 15:27 | ||
| 857 downloads | 1.0 | Dana Glass | 2016-10-13 15:30 | ||
| 878 downloads | 1.0 | Dana Glass | 2016-09-27 15:12 | ||
| 824 downloads | 1.0 | Dana Glass | 2016-08-28 14:41 | ||
| 745 downloads | 1.0 | Dana Glass | 2016-08-19 15:28 | ||
| 798 downloads | 1.0 | Dana Glass | 2016-08-08 15:05 | ||
| 797 downloads | 1.0 | Dana Glass | 2016-08-08 14:46 | ||
| 862 downloads | 1.0 | Dana Glass | 2016-08-01 15:29 | ||
| 758 downloads | 1.0 | Dana Glass | 2016-05-09 15:18 | ||
| 817 downloads | 1.0 | Dana Glass | 2016-05-04 15:19 | ||
| 807 downloads | 1.0 | Dana Glass | 2016-04-03 14:38 | ||
| 893 downloads | 1.0 | Dana Glass | 2016-02-01 15:15 | ||
| 826 downloads | 1.1 | Dana Glass | 2015-12-10 15:33 | ||
| 889 downloads | 1.0 | Dana Glass | 2015-11-01 13:50 | ||
| 781 downloads | 1.0 | Dana Glass | 2015-07-21 13:48 | ||
| 756 downloads | 1.0 | Dana Glass | 2015-07-20 13:54 | ||
| 877 downloads | 1.0 | Dana Glass | 2015-07-03 14:37 | ||
| 853 downloads | 1.0 | Dana Glass | 2015-06-29 15:22 | ||
| 813 downloads | 1.1 | Dana Glass | 2015-05-27 14:51 | ||
| 783 downloads | 1.0 | Dana Glass | 2014-08-16 15:09 | ||
| 728 downloads | 1.0 | Dana Glass | 2012-03-19 15:21 | ||
