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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| 783 downloads | 1.0 | Dana Glass | 2018-06-21 12:24 | ||
| 1073 downloads | 1.0 | Dana Glass | 2018-06-21 12:23 | ||
| 697 downloads | 1.0 | Dana Glass | 2018-05-15 12:23 | ||
| 966 downloads | 1.0 | Dana Glass | 2018-05-03 12:17 | ||
| 822 downloads | 1.0 | Dana Glass | 2018-04-06 11:52 | ||
| 676 downloads | 1.0 | Dana Glass | 2018-04-06 11:50 | ||
| 752 downloads | 1.0 | Dana Glass | 2018-03-20 11:53 | ||
| 649 downloads | 1.0 | Dana Glass | 2018-03-07 11:47 | ||
| 643 downloads | 1.0 | Dana Glass | 2018-03-01 12:21 | ||
| 963 downloads | 1.0 | Dana Glass | 2018-03-01 12:18 | ||
| 702 downloads | 1.0 | Dana Glass | 2017-12-03 20:55 | ||
| 712 downloads | 1.0 | Dana Glass | 2017-09-21 20:57 | ||
| 683 downloads | 1.0 | Dana Glass | 2017-09-18 20:58 | ||
| 727 downloads | 1.0 | Dana Glass | 2017-09-10 20:56 | ||
| 688 downloads | 1.0 | Dana Glass | 2017-08-15 21:00 | ||
| 661 downloads | 1.0 | Dana Glass | 2017-08-14 20:59 | ||
| 716 downloads | 1.0 | Dana Glass | 2017-08-08 21:01 | ||
| 748 downloads | 1.0 | Dana Glass | 2017-08-06 20:57 | ||
| 590 downloads | 1.0 | Dana Glass | 2017-05-25 14:36 | ||
| 666 downloads | 1.0 | Dana Glass | 2017-05-24 14:33 | ||
| 669 downloads | 1.0 | Dana Glass | 2017-04-28 14:47 | ||
| 675 downloads | 1.0 | Dana Glass | 2017-04-24 15:04 | ||
| 685 downloads | 1.0 | Dana Glass | 2017-04-08 15:26 | ||
| 754 downloads | 1.0 | Dana Glass | 2017-04-08 15:25 | ||
| 614 downloads | 1.0 | Dana Glass | 2017-03-03 15:13 | ||
| 635 downloads | 1.0 | Dana Glass | 2017-01-05 14:52 | ||
| 627 downloads | 1.0 | Dana Glass | 2016-10-25 15:27 | ||
| 710 downloads | 1.0 | Dana Glass | 2016-10-13 15:30 | ||
| 723 downloads | 1.0 | Dana Glass | 2016-09-27 15:12 | ||
| 673 downloads | 1.0 | Dana Glass | 2016-08-28 14:41 | ||
| 588 downloads | 1.0 | Dana Glass | 2016-08-19 15:28 | ||
| 646 downloads | 1.0 | Dana Glass | 2016-08-08 15:05 | ||
| 641 downloads | 1.0 | Dana Glass | 2016-08-08 14:46 | ||
| 712 downloads | 1.0 | Dana Glass | 2016-08-01 15:29 | ||
| 622 downloads | 1.0 | Dana Glass | 2016-05-09 15:18 | ||
| 671 downloads | 1.0 | Dana Glass | 2016-05-04 15:19 | ||
| 667 downloads | 1.0 | Dana Glass | 2016-04-03 14:38 | ||
| 751 downloads | 1.0 | Dana Glass | 2016-02-01 15:15 | ||
| 679 downloads | 1.1 | Dana Glass | 2015-12-10 15:33 | ||
| 739 downloads | 1.0 | Dana Glass | 2015-11-01 13:50 | ||
| 644 downloads | 1.0 | Dana Glass | 2015-07-21 13:48 | ||
| 596 downloads | 1.0 | Dana Glass | 2015-07-20 13:54 | ||
| 722 downloads | 1.0 | Dana Glass | 2015-07-03 14:37 | ||
| 705 downloads | 1.0 | Dana Glass | 2015-06-29 15:22 | ||
| 674 downloads | 1.1 | Dana Glass | 2015-05-27 14:51 | ||
| 627 downloads | 1.0 | Dana Glass | 2014-08-16 15:09 | ||
| 601 downloads | 1.0 | Dana Glass | 2012-03-19 15:21 | ||
