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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| 834 downloads | 1.0 | Dana Glass | 2018-06-21 12:24 | ||
| 1125 downloads | 1.0 | Dana Glass | 2018-06-21 12:23 | ||
| 749 downloads | 1.0 | Dana Glass | 2018-05-15 12:23 | ||
| 1021 downloads | 1.0 | Dana Glass | 2018-05-03 12:17 | ||
| 876 downloads | 1.0 | Dana Glass | 2018-04-06 11:52 | ||
| 728 downloads | 1.0 | Dana Glass | 2018-04-06 11:50 | ||
| 808 downloads | 1.0 | Dana Glass | 2018-03-20 11:53 | ||
| 700 downloads | 1.0 | Dana Glass | 2018-03-07 11:47 | ||
| 696 downloads | 1.0 | Dana Glass | 2018-03-01 12:21 | ||
| 1016 downloads | 1.0 | Dana Glass | 2018-03-01 12:18 | ||
| 750 downloads | 1.0 | Dana Glass | 2017-12-03 20:55 | ||
| 761 downloads | 1.0 | Dana Glass | 2017-09-21 20:57 | ||
| 733 downloads | 1.0 | Dana Glass | 2017-09-18 20:58 | ||
| 784 downloads | 1.0 | Dana Glass | 2017-09-10 20:56 | ||
| 724 downloads | 1.0 | Dana Glass | 2017-08-15 21:00 | ||
| 713 downloads | 1.0 | Dana Glass | 2017-08-14 20:59 | ||
| 768 downloads | 1.0 | Dana Glass | 2017-08-08 21:01 | ||
| 802 downloads | 1.0 | Dana Glass | 2017-08-06 20:57 | ||
| 640 downloads | 1.0 | Dana Glass | 2017-05-25 14:36 | ||
| 715 downloads | 1.0 | Dana Glass | 2017-05-24 14:33 | ||
| 718 downloads | 1.0 | Dana Glass | 2017-04-28 14:47 | ||
| 728 downloads | 1.0 | Dana Glass | 2017-04-24 15:04 | ||
| 741 downloads | 1.0 | Dana Glass | 2017-04-08 15:26 | ||
| 805 downloads | 1.0 | Dana Glass | 2017-04-08 15:25 | ||
| 666 downloads | 1.0 | Dana Glass | 2017-03-03 15:13 | ||
| 688 downloads | 1.0 | Dana Glass | 2017-01-05 14:52 | ||
| 678 downloads | 1.0 | Dana Glass | 2016-10-25 15:27 | ||
| 760 downloads | 1.0 | Dana Glass | 2016-10-13 15:30 | ||
| 771 downloads | 1.0 | Dana Glass | 2016-09-27 15:12 | ||
| 726 downloads | 1.0 | Dana Glass | 2016-08-28 14:41 | ||
| 644 downloads | 1.0 | Dana Glass | 2016-08-19 15:28 | ||
| 700 downloads | 1.0 | Dana Glass | 2016-08-08 15:05 | ||
| 693 downloads | 1.0 | Dana Glass | 2016-08-08 14:46 | ||
| 765 downloads | 1.0 | Dana Glass | 2016-08-01 15:29 | ||
| 672 downloads | 1.0 | Dana Glass | 2016-05-09 15:18 | ||
| 719 downloads | 1.0 | Dana Glass | 2016-05-04 15:19 | ||
| 714 downloads | 1.0 | Dana Glass | 2016-04-03 14:38 | ||
| 795 downloads | 1.0 | Dana Glass | 2016-02-01 15:15 | ||
| 729 downloads | 1.1 | Dana Glass | 2015-12-10 15:33 | ||
| 793 downloads | 1.0 | Dana Glass | 2015-11-01 13:50 | ||
| 691 downloads | 1.0 | Dana Glass | 2015-07-21 13:48 | ||
| 652 downloads | 1.0 | Dana Glass | 2015-07-20 13:54 | ||
| 771 downloads | 1.0 | Dana Glass | 2015-07-03 14:37 | ||
| 756 downloads | 1.0 | Dana Glass | 2015-06-29 15:22 | ||
| 721 downloads | 1.1 | Dana Glass | 2015-05-27 14:51 | ||
| 680 downloads | 1.0 | Dana Glass | 2014-08-16 15:09 | ||
| 648 downloads | 1.0 | Dana Glass | 2012-03-19 15:21 | ||
