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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| 961 downloads | 1.0 | Dana Glass | 2018-06-21 12:24 | ||
| 1268 downloads | 1.0 | Dana Glass | 2018-06-21 12:23 | ||
| 860 downloads | 1.0 | Dana Glass | 2018-05-15 12:23 | ||
| 1147 downloads | 1.0 | Dana Glass | 2018-05-03 12:17 | ||
| 970 downloads | 1.0 | Dana Glass | 2018-04-06 11:52 | ||
| 855 downloads | 1.0 | Dana Glass | 2018-04-06 11:50 | ||
| 940 downloads | 1.0 | Dana Glass | 2018-03-20 11:53 | ||
| 796 downloads | 1.0 | Dana Glass | 2018-03-07 11:47 | ||
| 807 downloads | 1.0 | Dana Glass | 2018-03-01 12:21 | ||
| 1146 downloads | 1.0 | Dana Glass | 2018-03-01 12:18 | ||
| 860 downloads | 1.0 | Dana Glass | 2017-12-03 20:55 | ||
| 863 downloads | 1.0 | Dana Glass | 2017-09-21 20:57 | ||
| 860 downloads | 1.0 | Dana Glass | 2017-09-18 20:58 | ||
| 896 downloads | 1.0 | Dana Glass | 2017-09-10 20:56 | ||
| 779 downloads | 1.0 | Dana Glass | 2017-08-15 21:00 | ||
| 821 downloads | 1.0 | Dana Glass | 2017-08-14 20:59 | ||
| 908 downloads | 1.0 | Dana Glass | 2017-08-08 21:01 | ||
| 928 downloads | 1.0 | Dana Glass | 2017-08-06 20:57 | ||
| 739 downloads | 1.0 | Dana Glass | 2017-05-25 14:36 | ||
| 807 downloads | 1.0 | Dana Glass | 2017-05-24 14:33 | ||
| 830 downloads | 1.0 | Dana Glass | 2017-04-28 14:47 | ||
| 830 downloads | 1.0 | Dana Glass | 2017-04-24 15:04 | ||
| 855 downloads | 1.0 | Dana Glass | 2017-04-08 15:26 | ||
| 935 downloads | 1.0 | Dana Glass | 2017-04-08 15:25 | ||
| 812 downloads | 1.0 | Dana Glass | 2017-03-03 15:13 | ||
| 804 downloads | 1.0 | Dana Glass | 2017-01-05 14:52 | ||
| 776 downloads | 1.0 | Dana Glass | 2016-10-25 15:27 | ||
| 871 downloads | 1.0 | Dana Glass | 2016-10-13 15:30 | ||
| 891 downloads | 1.0 | Dana Glass | 2016-09-27 15:12 | ||
| 842 downloads | 1.0 | Dana Glass | 2016-08-28 14:41 | ||
| 762 downloads | 1.0 | Dana Glass | 2016-08-19 15:28 | ||
| 815 downloads | 1.0 | Dana Glass | 2016-08-08 15:05 | ||
| 812 downloads | 1.0 | Dana Glass | 2016-08-08 14:46 | ||
| 879 downloads | 1.0 | Dana Glass | 2016-08-01 15:29 | ||
| 771 downloads | 1.0 | Dana Glass | 2016-05-09 15:18 | ||
| 836 downloads | 1.0 | Dana Glass | 2016-05-04 15:19 | ||
| 822 downloads | 1.0 | Dana Glass | 2016-04-03 14:38 | ||
| 912 downloads | 1.0 | Dana Glass | 2016-02-01 15:15 | ||
| 846 downloads | 1.1 | Dana Glass | 2015-12-10 15:33 | ||
| 909 downloads | 1.0 | Dana Glass | 2015-11-01 13:50 | ||
| 799 downloads | 1.0 | Dana Glass | 2015-07-21 13:48 | ||
| 775 downloads | 1.0 | Dana Glass | 2015-07-20 13:54 | ||
| 893 downloads | 1.0 | Dana Glass | 2015-07-03 14:37 | ||
| 872 downloads | 1.0 | Dana Glass | 2015-06-29 15:22 | ||
| 830 downloads | 1.1 | Dana Glass | 2015-05-27 14:51 | ||
| 797 downloads | 1.0 | Dana Glass | 2014-08-16 15:09 | ||
| 743 downloads | 1.0 | Dana Glass | 2012-03-19 15:21 | ||
