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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| 1045 downloads | 1.0 | Dana Glass | 2018-06-21 12:24 | ||
| 1366 downloads | 1.0 | Dana Glass | 2018-06-21 12:23 | ||
| 935 downloads | 1.0 | Dana Glass | 2018-05-15 12:23 | ||
| 1238 downloads | 1.0 | Dana Glass | 2018-05-03 12:17 | ||
| 1066 downloads | 1.0 | Dana Glass | 2018-04-06 11:52 | ||
| 919 downloads | 1.0 | Dana Glass | 2018-04-06 11:50 | ||
| 1054 downloads | 1.0 | Dana Glass | 2018-03-20 11:53 | ||
| 858 downloads | 1.0 | Dana Glass | 2018-03-07 11:47 | ||
| 897 downloads | 1.0 | Dana Glass | 2018-03-01 12:21 | ||
| 1250 downloads | 1.0 | Dana Glass | 2018-03-01 12:18 | ||
| 923 downloads | 1.0 | Dana Glass | 2017-12-03 20:55 | ||
| 932 downloads | 1.0 | Dana Glass | 2017-09-21 20:57 | ||
| 965 downloads | 1.0 | Dana Glass | 2017-09-18 20:58 | ||
| 991 downloads | 1.0 | Dana Glass | 2017-09-10 20:56 | ||
| 859 downloads | 1.0 | Dana Glass | 2017-08-15 21:00 | ||
| 890 downloads | 1.0 | Dana Glass | 2017-08-14 20:59 | ||
| 1012 downloads | 1.0 | Dana Glass | 2017-08-08 21:01 | ||
| 1013 downloads | 1.0 | Dana Glass | 2017-08-06 20:57 | ||
| 802 downloads | 1.0 | Dana Glass | 2017-05-25 14:36 | ||
| 864 downloads | 1.0 | Dana Glass | 2017-05-24 14:33 | ||
| 913 downloads | 1.0 | Dana Glass | 2017-04-28 14:47 | ||
| 905 downloads | 1.0 | Dana Glass | 2017-04-24 15:04 | ||
| 943 downloads | 1.0 | Dana Glass | 2017-04-08 15:26 | ||
| 1046 downloads | 1.0 | Dana Glass | 2017-04-08 15:25 | ||
| 916 downloads | 1.0 | Dana Glass | 2017-03-03 15:13 | ||
| 878 downloads | 1.0 | Dana Glass | 2017-01-05 14:52 | ||
| 842 downloads | 1.0 | Dana Glass | 2016-10-25 15:27 | ||
| 970 downloads | 1.0 | Dana Glass | 2016-10-13 15:30 | ||
| 961 downloads | 1.0 | Dana Glass | 2016-09-27 15:12 | ||
| 929 downloads | 1.0 | Dana Glass | 2016-08-28 14:41 | ||
| 833 downloads | 1.0 | Dana Glass | 2016-08-19 15:28 | ||
| 912 downloads | 1.0 | Dana Glass | 2016-08-08 15:05 | ||
| 894 downloads | 1.0 | Dana Glass | 2016-08-08 14:46 | ||
| 952 downloads | 1.0 | Dana Glass | 2016-08-01 15:29 | ||
| 846 downloads | 1.0 | Dana Glass | 2016-05-09 15:18 | ||
| 916 downloads | 1.0 | Dana Glass | 2016-05-04 15:19 | ||
| 915 downloads | 1.0 | Dana Glass | 2016-04-03 14:38 | ||
| 982 downloads | 1.0 | Dana Glass | 2016-02-01 15:15 | ||
| 914 downloads | 1.1 | Dana Glass | 2015-12-10 15:33 | ||
| 985 downloads | 1.0 | Dana Glass | 2015-11-01 13:50 | ||
| 891 downloads | 1.0 | Dana Glass | 2015-07-21 13:48 | ||
| 866 downloads | 1.0 | Dana Glass | 2015-07-20 13:54 | ||
| 966 downloads | 1.0 | Dana Glass | 2015-07-03 14:37 | ||
| 947 downloads | 1.0 | Dana Glass | 2015-06-29 15:22 | ||
| 910 downloads | 1.1 | Dana Glass | 2015-05-27 14:51 | ||
| 892 downloads | 1.0 | Dana Glass | 2014-08-16 15:09 | ||
| 839 downloads | 1.0 | Dana Glass | 2012-03-19 15:21 | ||
