Data brokers - Revision history

Rudxain: wanted: cookies

2026-03-15T14:15:07Z

wanted: cookies

← Older revision		Revision as of 14:15, 15 March 2026
Line 9:		Line 9:
	*Scraping of publicly available information from websites and social media		*Scraping of publicly available information from websites and social media
	*Inference of additional data points through analysis and algorithms		*Inference of additional data points through analysis and algorithms
	*Tracking of online behavior through cookies, device fingerprinting, and other technologies		*Tracking of online behavior through [[Web cookie\|cookies]], device fingerprinting, and other technologies

	Once collected, this data is processed, combined, and categorized to create detailed consumer profiles. These profiles are then sold or licensed to third parties for various purposes, including targeted advertising, credit decisioning, insurance underwriting, and fraud prevention.		Once collected, this data is processed, combined, and categorized to create detailed consumer profiles. These profiles are then sold or licensed to third parties for various purposes, including targeted advertising, credit decisioning, insurance underwriting, and fraud prevention.

Rudxain: Social Cooling is about reactions to algorithms, not just discrimination

2026-02-26T18:34:03Z

Social Cooling is about reactions to algorithms, not just discrimination

← Older revision		Revision as of 18:34, 26 February 2026
Line 22:		Line 22:

	===Potential for discrimination===		===Potential for discrimination===
	Data broker profiles can potentially enable discriminatory practices when used for decisions regarding credit, insurance, employment, or housing. By categorizing consumers based on various attributes, data brokers create segments that can serve as proxies for protected characteristics like race, religion, or socioeconomic status, even when those characteristics aren't explicitly identified.<ref>{{cite web \|url=https://epic.org/issues/consumer-privacy/data-brokers/ \|title=Data Brokers \|publisher=Electronic Privacy Information Center \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260201001608/https://epic.org/issues/consumer-privacy/data-brokers/ \|archive-date=1 Feb 2026}}</ref><ref>{{Cite web \|title=Social Cooling - Big Data's unintended side effect \|url=https://www.socialcooling.com/ \|url-status=live \|archive-url=https://web.archive.org/web/20260220030934/https://www.socialcooling.com/ \|archive-date=2026-02-20 \|access-date=2026-02-26 \|website=Social Cooling}}</ref>		Data broker profiles can potentially enable discriminatory practices when used for decisions regarding credit, insurance, employment, or housing. By categorizing consumers based on various attributes, data brokers create segments that can serve as proxies for protected characteristics like race, religion, or socioeconomic status, even when those characteristics aren't explicitly identified.<ref>{{cite web \|url=https://epic.org/issues/consumer-privacy/data-brokers/ \|title=Data Brokers \|publisher=Electronic Privacy Information Center \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260201001608/https://epic.org/issues/consumer-privacy/data-brokers/ \|archive-date=1 Feb 2026}}</ref> This leads to people reluctantly changing their behavior in order to pander to the algorithms.<ref>{{Cite web \|title=Social Cooling - Big Data's unintended side effect \|url=https://www.socialcooling.com/ \|url-status=live \|archive-url=https://web.archive.org/web/20260220030934/https://www.socialcooling.com/ \|archive-date=2026-02-20 \|access-date=2026-02-26 \|website=Social Cooling}}</ref>

	===Security vulnerabilities===		===Security vulnerabilities===

Rudxain: add Social-Cooling as ref to discrimination section

2026-02-26T18:23:52Z

add Social-Cooling as ref to discrimination section

← Older revision		Revision as of 18:23, 26 February 2026
Line 22:		Line 22:

	===Potential for discrimination===		===Potential for discrimination===
	Data broker profiles can potentially enable discriminatory practices when used for decisions regarding credit, insurance, employment, or housing. By categorizing consumers based on various attributes, data brokers create segments that can serve as proxies for protected characteristics like race, religion, or socioeconomic status, even when those characteristics aren't explicitly identified.<ref>{{cite web \|url=https://epic.org/issues/consumer-privacy/data-brokers/ \|title=Data Brokers \|publisher=Electronic Privacy Information Center \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260201001608/https://epic.org/issues/consumer-privacy/data-brokers/ \|archive-date=1 Feb 2026}}</ref>		Data broker profiles can potentially enable discriminatory practices when used for decisions regarding credit, insurance, employment, or housing. By categorizing consumers based on various attributes, data brokers create segments that can serve as proxies for protected characteristics like race, religion, or socioeconomic status, even when those characteristics aren't explicitly identified.<ref>{{cite web \|url=https://epic.org/issues/consumer-privacy/data-brokers/ \|title=Data Brokers \|publisher=Electronic Privacy Information Center \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260201001608/https://epic.org/issues/consumer-privacy/data-brokers/ \|archive-date=1 Feb 2026}}</ref><ref>{{Cite web \|title=Social Cooling - Big Data's unintended side effect \|url=https://www.socialcooling.com/ \|url-status=live \|archive-url=https://web.archive.org/web/20260220030934/https://www.socialcooling.com/ \|archive-date=2026-02-20 \|access-date=2026-02-26 \|website=Social Cooling}}</ref>

	===Security vulnerabilities===		===Security vulnerabilities===

Bananabot: Added archive URLs for 1 citation(s) using CRWCitationBot

2026-02-23T03:52:46Z

Added archive URLs for 1 citation(s) using CRWCitationBot

← Older revision		Revision as of 03:52, 23 February 2026
Line 40:		Line 40:

	===LexisNexis===		===LexisNexis===
	[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20260203045159/https://risk.lexisnexis.com/ \|archive-date=3 Feb 2026}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09 \|archive-url=http://web.archive.org/web/20250712050854/https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|archive-date=12 Jul 2025}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>		[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20260203045159/https://risk.lexisnexis.com/ \|archive-date=3 Feb 2026}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09 \|archive-url=http://web.archive.org/web/20250712050854/https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|archive-date=12 Jul 2025}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09 \|archive-url=http://web.archive.org/web/20260217134807/https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|archive-date=17 Feb 2026}}</ref>

	On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20250708191619/https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|archive-date=8 Jul 2025}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>		On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20250708191619/https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|archive-date=8 Jul 2025}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>

Banana: Removed 1 duplicate url-status parameter(s) from 1 citation(s) using CRWCitationBot

2026-02-16T06:23:13Z

Removed 1 duplicate url-status parameter(s) from 1 citation(s) using CRWCitationBot

← Older revision		Revision as of 06:23, 16 February 2026
Line 40:		Line 40:

	===LexisNexis===		===LexisNexis===
	[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20260203045159/https://risk.lexisnexis.com/ \|archive-date=3 Feb 2026}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09 ~~\|url-status=live~~ \|archive-url=http://web.archive.org/web/20250712050854/https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|archive-date=12 Jul 2025}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>		[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20260203045159/https://risk.lexisnexis.com/ \|archive-date=3 Feb 2026}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09 \|archive-url=http://web.archive.org/web/20250712050854/https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|archive-date=12 Jul 2025}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>

	On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20250708191619/https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|archive-date=8 Jul 2025}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>		On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20250708191619/https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|archive-date=8 Jul 2025}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>

Banana: Added archive URLs for 12 citation(s) using CRWCitationBot

2026-02-16T04:00:23Z

Added archive URLs for 12 citation(s) using CRWCitationBot

← Older revision		Revision as of 04:00, 16 February 2026
Line 1:		Line 1:
	'''[[wikipedia:Data_broker\|Data brokers]]''' are companies that collect, aggregate, analyze, and sell personal information about consumers without having a direct relationship with those individuals.<ref>{{cite web \|url=https://www.ftc.gov/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014 \|title=Data Brokers: A Call for Transparency and Accountability: A Report of the Federal Trade Commission \|publisher=Federal Trade Commission \|date=May 2014 \|access-date=2025-05-07}}</ref> These companies operate largely behind the scenes of the digital economy, accumulating vast databases of consumer information from both public and private sources to create detailed profiles used primarily for marketing, risk assessment, and other business purposes.		'''[[wikipedia:Data_broker\|Data brokers]]''' are companies that collect, aggregate, analyze, and sell personal information about consumers without having a direct relationship with those individuals.<ref>{{cite web \|url=https://www.ftc.gov/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014 \|title=Data Brokers: A Call for Transparency and Accountability: A Report of the Federal Trade Commission \|publisher=Federal Trade Commission \|date=May 2014 \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20251029193058/https://www.ftc.gov/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014 \|archive-date=29 Oct 2025}}</ref> These companies operate largely behind the scenes of the digital economy, accumulating vast databases of consumer information from both public and private sources to create detailed profiles used primarily for marketing, risk assessment, and other business purposes.

	==How they work==		==How they work==

	Data brokers obtain personal information through various channels:<ref>{{cite web \|url=https://privacyrights.org/data-brokers \|title=Data Brokers \|publisher=Privacy Rights Clearinghouse \|access-date=2025-05-07}}</ref>		Data brokers obtain personal information through various channels:<ref>{{cite web \|url=https://privacyrights.org/data-brokers \|title=Data Brokers \|publisher=Privacy Rights Clearinghouse \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260201012510/https://privacyrights.org/data-brokers \|archive-date=1 Feb 2026}}</ref>

	*Collection from public records (court records, property records, voter registrations)		*Collection from public records (court records, property records, voter registrations)
Line 16:		Line 16:

	===Privacy erosion===		===Privacy erosion===
	Data brokers collect and process vast amounts of personal information, often without consumers' knowledge or meaningful consent. Many consumers are unaware of the extent of information being collected about them, who has access to it, or how it's being used.<ref>{{cite web \|url=https://www.technologyreview.com/2024/01/15/1086513/the-ftcs-unprecedented-move-against-data-brokers-explained/ \|title=The FTC's unprecedented move against data brokers, explained \|publisher=MIT Technology Review \|date=January 15, 2024 \|access-date=2025-05-07}}</ref> This creates a fundamental asymmetry of information and power between data brokers and consumers.		Data brokers collect and process vast amounts of personal information, often without consumers' knowledge or meaningful consent. Many consumers are unaware of the extent of information being collected about them, who has access to it, or how it's being used.<ref>{{cite web \|url=https://www.technologyreview.com/2024/01/15/1086513/the-ftcs-unprecedented-move-against-data-brokers-explained/ \|title=The FTC's unprecedented move against data brokers, explained \|publisher=MIT Technology Review \|date=January 15, 2024 \|access-date=2025-05-07 \|url-status=live \|archive-url=https://web.archive.org/web/20260216035819/https://www.technologyreview.com/2024/01/15/1086513/the-ftcs-unprecedented-move-against-data-brokers-explained/ \|archive-date=16 Feb 2026}}</ref> This creates a fundamental asymmetry of information and power between data brokers and consumers.

	===Limited transparency and choice===		===Limited transparency and choice===
	Consumers typically have minimal visibility into data broker practices and limited ability to control the collection and use of their personal information. Unlike direct business relationships where consumers can choose to engage with a company, data brokers collect information about consumers without establishing a direct relationship, making it difficult for individuals to exercise choice regarding their data.<ref>{{cite web \|url=https://privacyrights.org/resources/tutorial-data-brokers-and-people-search-sites \|title=Tutorial: Data Brokers and People Search Sites \|publisher=Privacy Rights Clearinghouse \|access-date=2025-05-07}}</ref>		Consumers typically have minimal visibility into data broker practices and limited ability to control the collection and use of their personal information. Unlike direct business relationships where consumers can choose to engage with a company, data brokers collect information about consumers without establishing a direct relationship, making it difficult for individuals to exercise choice regarding their data.<ref>{{cite web \|url=https://privacyrights.org/resources/tutorial-data-brokers-and-people-search-sites \|title=Tutorial: Data Brokers and People Search Sites \|publisher=Privacy Rights Clearinghouse \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20241207172106/https://privacyrights.org/resources/tutorial-data-brokers-and-people-search-sites \|archive-date=7 Dec 2024}}</ref>

	===Potential for discrimination===		===Potential for discrimination===
	Data broker profiles can potentially enable discriminatory practices when used for decisions regarding credit, insurance, employment, or housing. By categorizing consumers based on various attributes, data brokers create segments that can serve as proxies for protected characteristics like race, religion, or socioeconomic status, even when those characteristics aren't explicitly identified.<ref>{{cite web \|url=https://epic.org/issues/consumer-privacy/data-brokers/ \|title=Data Brokers \|publisher=Electronic Privacy Information Center \|access-date=2025-05-07}}</ref>		Data broker profiles can potentially enable discriminatory practices when used for decisions regarding credit, insurance, employment, or housing. By categorizing consumers based on various attributes, data brokers create segments that can serve as proxies for protected characteristics like race, religion, or socioeconomic status, even when those characteristics aren't explicitly identified.<ref>{{cite web \|url=https://epic.org/issues/consumer-privacy/data-brokers/ \|title=Data Brokers \|publisher=Electronic Privacy Information Center \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260201001608/https://epic.org/issues/consumer-privacy/data-brokers/ \|archive-date=1 Feb 2026}}</ref>

	===Security vulnerabilities===		===Security vulnerabilities===
	The consolidation of large volumes of personal data creates security risks. Data brokers become attractive targets for hackers, and breaches of these vast repositories can expose sensitive personal information of millions of consumers, leading to identity theft and other forms of fraud.<ref>{{cite web \|url=https://www.brennancenter.org/our-work/research-reports/closing-data-broker-loophole \|title=Closing the Data Broker Loophole \|publisher=Brennan Center for Justice \|access-date=2025-05-07}}</ref>		The consolidation of large volumes of personal data creates security risks. Data brokers become attractive targets for hackers, and breaches of these vast repositories can expose sensitive personal information of millions of consumers, leading to identity theft and other forms of fraud.<ref>{{cite web \|url=https://www.brennancenter.org/our-work/research-reports/closing-data-broker-loophole \|title=Closing the Data Broker Loophole \|publisher=Brennan Center for Justice \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260209012812/https://www.brennancenter.org/our-work/research-reports/closing-data-broker-loophole \|archive-date=9 Feb 2026}}</ref>
	And with the search for indemnification related to being held harmless for such breaches, it is becoming harder and harder to hold these companies accountable.		And with the search for indemnification related to being held harmless for such breaches, it is becoming harder and harder to hold these companies accountable.

Line 31:		Line 31:

	===Acxiom/LiveRamp===		===Acxiom/LiveRamp===
	[[LiveRamp]] (formerly Acxiom) is one of the largest data brokers globally, maintaining detailed profiles on hundreds of millions of consumers. The company's data onboarding services connect offline customer data with online identifiers, enabling cross-device tracking and targeted advertising.<ref>{{cite web \|url=https://partner-directory.liveramp.com/partners/oracle-data-cloud-bluekai \|title=Oracle Data Cloud (BlueKai) \|website=LiveRamp \|access-date=2025-05-07}}</ref> LiveRamp has faced criticism for its extensive data collection practices and the creation of unique identifiers called "RampIDs" that connect individuals' online and offline identities without transparent consumer consent.		[[LiveRamp]] (formerly Acxiom) is one of the largest data brokers globally, maintaining detailed profiles on hundreds of millions of consumers. The company's data onboarding services connect offline customer data with online identifiers, enabling cross-device tracking and targeted advertising.<ref>{{cite web \|url=https://partner-directory.liveramp.com/partners/oracle-data-cloud-bluekai \|title=Oracle Data Cloud (BlueKai) \|website=LiveRamp \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20250708191618/https://partner-directory.liveramp.com/partners/oracle-data-cloud-bluekai \|archive-date=8 Jul 2025}}</ref> LiveRamp has faced criticism for its extensive data collection practices and the creation of unique identifiers called "RampIDs" that connect individuals' online and offline identities without transparent consumer consent.

	===Experian===		===Experian===
	Beyond its role as a credit reporting agency, [[Experian]] operates as a major data broker, offering marketing services that leverage vast amounts of consumer information. Through its Experian Marketing Services division, the company provides audience segmentation, targeting, and identity resolution products based on consumer data.<ref>{{cite web \|url=https://builtin.com/articles/top-data-broker-companies \|title=10 Top Data Broker Companies \|website=Built In \|date=November 12, 2024 \|access-date=2025-05-07}}</ref>		Beyond its role as a credit reporting agency, [[Experian]] operates as a major data broker, offering marketing services that leverage vast amounts of consumer information. Through its Experian Marketing Services division, the company provides audience segmentation, targeting, and identity resolution products based on consumer data.<ref>{{cite web \|url=https://builtin.com/articles/top-data-broker-companies \|title=10 Top Data Broker Companies \|website=Built In \|date=November 12, 2024 \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20250827181051/https://builtin.com/articles/top-data-broker-companies \|archive-date=27 Aug 2025}}</ref>

	===Oracle Data Cloud===		===Oracle Data Cloud===
	[[Oracle Data Cloud]] (formerly BlueKai) provides data services that help marketers target consumers across digital channels. The platform processes trillions of data points monthly from various online and offline sources to create detailed audience profiles. In 2020, Oracle faced scrutiny after security researchers discovered billions of records from its BlueKai database had been left exposed on an unsecured server.<ref>{{cite web \|url=https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|title=The Little-Known Data Broker Industry Is Spending Big Bucks Lobbying Congress \|website=The Markup \|date=April 1, 2021 \|access-date=2025-05-07}}</ref>		[[Oracle Data Cloud]] (formerly BlueKai) provides data services that help marketers target consumers across digital channels. The platform processes trillions of data points monthly from various online and offline sources to create detailed audience profiles. In 2020, Oracle faced scrutiny after security researchers discovered billions of records from its BlueKai database had been left exposed on an unsecured server.<ref>{{cite web \|url=https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|title=The Little-Known Data Broker Industry Is Spending Big Bucks Lobbying Congress \|website=The Markup \|date=April 1, 2021 \|access-date=2025-05-07 \|url-status=live \|archive-url=http://web.archive.org/web/20260105202006/https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|archive-date=5 Jan 2026}}</ref>

	===LexisNexis===		===LexisNexis===
	[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>		[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20260203045159/https://risk.lexisnexis.com/ \|archive-date=3 Feb 2026}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20250712050854/https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|archive-date=12 Jul 2025}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>

	On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>		On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09 \|url-status=live \|archive-url=http://web.archive.org/web/20250708191619/https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|archive-date=8 Jul 2025}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>

	==See also==		==See also==

PixelRunner: added some links, mostly wanted links though.

2025-08-18T02:13:17Z

added some links, mostly wanted links though.

← Older revision		Revision as of 02:13, 18 August 2025
Line 34:		Line 34:

	===Experian===		===Experian===
	Beyond its role as a credit reporting agency, Experian operates as a major data broker, offering marketing services that leverage vast amounts of consumer information. Through its Experian Marketing Services division, the company provides audience segmentation, targeting, and identity resolution products based on consumer data.<ref>{{cite web \|url=https://builtin.com/articles/top-data-broker-companies \|title=10 Top Data Broker Companies \|website=Built In \|date=November 12, 2024 \|access-date=2025-05-07}}</ref>		Beyond its role as a credit reporting agency, [[Experian]] operates as a major data broker, offering marketing services that leverage vast amounts of consumer information. Through its Experian Marketing Services division, the company provides audience segmentation, targeting, and identity resolution products based on consumer data.<ref>{{cite web \|url=https://builtin.com/articles/top-data-broker-companies \|title=10 Top Data Broker Companies \|website=Built In \|date=November 12, 2024 \|access-date=2025-05-07}}</ref>

	===Oracle Data Cloud===		===Oracle Data Cloud===
	Oracle Data Cloud (formerly BlueKai) provides data services that help marketers target consumers across digital channels. The platform processes trillions of data points monthly from various online and offline sources to create detailed audience profiles. In 2020, Oracle faced scrutiny after security researchers discovered billions of records from its BlueKai database had been left exposed on an unsecured server.<ref>{{cite web \|url=https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|title=The Little-Known Data Broker Industry Is Spending Big Bucks Lobbying Congress \|website=The Markup \|date=April 1, 2021 \|access-date=2025-05-07}}</ref>		[[Oracle Data Cloud]] (formerly BlueKai) provides data services that help marketers target consumers across digital channels. The platform processes trillions of data points monthly from various online and offline sources to create detailed audience profiles. In 2020, Oracle faced scrutiny after security researchers discovered billions of records from its BlueKai database had been left exposed on an unsecured server.<ref>{{cite web \|url=https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|title=The Little-Known Data Broker Industry Is Spending Big Bucks Lobbying Congress \|website=The Markup \|date=April 1, 2021 \|access-date=2025-05-07}}</ref>

	=== LexisNexis ===		===LexisNexis===
	LexisNexis is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>		[[LexisNexis]] is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>

	On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants (General Motors, OnStar LLC, and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>		On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants ([[General Motors]], [[OnStar\|OnStar LLC]], and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>

	==See also==		==See also==

TheRickestRick: /* Examples of major data brokers */ Added LexisNexis entry

2025-05-10T01:00:38Z

Examples of major data brokers: Added LexisNexis entry

← Older revision		Revision as of 01:00, 10 May 2025
Line 38:		Line 38:
	===Oracle Data Cloud===		===Oracle Data Cloud===
	Oracle Data Cloud (formerly BlueKai) provides data services that help marketers target consumers across digital channels. The platform processes trillions of data points monthly from various online and offline sources to create detailed audience profiles. In 2020, Oracle faced scrutiny after security researchers discovered billions of records from its BlueKai database had been left exposed on an unsecured server.<ref>{{cite web \|url=https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|title=The Little-Known Data Broker Industry Is Spending Big Bucks Lobbying Congress \|website=The Markup \|date=April 1, 2021 \|access-date=2025-05-07}}</ref>		Oracle Data Cloud (formerly BlueKai) provides data services that help marketers target consumers across digital channels. The platform processes trillions of data points monthly from various online and offline sources to create detailed audience profiles. In 2020, Oracle faced scrutiny after security researchers discovered billions of records from its BlueKai database had been left exposed on an unsecured server.<ref>{{cite web \|url=https://themarkup.org/privacy/2021/04/01/the-little-known-data-broker-industry-is-spending-big-bucks-lobbying-congress \|title=The Little-Known Data Broker Industry Is Spending Big Bucks Lobbying Congress \|website=The Markup \|date=April 1, 2021 \|access-date=2025-05-07}}</ref>

			=== LexisNexis ===
			LexisNexis is a data broker with over 75 billion records covering over 95% of the adult US population, according to their website. Their primary market includes various government agencies, banks, insurance, and legal firms.<ref>{{Cite web \|title=LexisNexis Risk Solutions \|url=https://risk.lexisnexis.com/ \|access-date=2025-05-09}}</ref> Since at least 2016 the Washington, DC Office of Tax Revenue has been using LexisNexis to identify taxpayers.<ref>{{Cite web \|last=DC Office of Tax and Revenue \|date=2016-02-29 \|title=LexisNexis Risk Solutions Quiz FAQs \|url=https://otr.cfo.dc.gov/release/lexisnexis-risk-solutions-quiz-faqs \|url-status=live \|access-date=2025-05-09}}</ref> DocuSign partnered with LexisNexis to confirm identity of document signers with what they call “out of wallet” questions, or questions that someone would not be able to answer if they found your wallet laying in the street.<ref>{{Cite web \|date= \|title=DocuSign Partners \|url=https://partners.docusign.com/s/partner-profile/aNQ1W0000004CEFWA2/lexisnexis-risk-solutions \|url-status=live \|access-date=2025-05-09}}</ref>

			On March 13, 2024 a class action lawsuit was filed in the US District Court, Southern District of Florida alleging the defendants (General Motors, OnStar LLC, and LexisNexis Risk Solutions Inc.) violated The Fair Credit Reporting Act (15 U.S.C. § 1681), The Florida Deceptive and Unfair Trade Practices Act (FLA. STAT. § 501.201), and Florida Common-law Invasion of Privacy. Court documents allege OnStar was selling vehicle telematics data, collected through the Smart Driver program, to LexisNexis which was in turn sold to insurance providers leading to the plaintiff to be rejected on multiple car insurance applications and then having insurance rates doubled based on the information provided by LexisNexis.<ref>{{Cite web \|date=2024-03-13 \|title=Class Action Claims General Motors, OnStar Shared Driving Behavior Data Without Consent \|url=https://www.classaction.org/media/chicco-v-general-motors-llc-et-al.pdf \|access-date=2025-05-09}}</ref> According to a NY Times article, GM has stopped selling vehicle telematics data with LexisNexis and Verisk after the lawsuit was filed. A GM document referenced but not released by the NY Times allegedly showed that as of 2022 more than 8 million vehicles were enrolled in the program, and a company employee told the NY Times the revenue from the Smart Driver program was in the low millions of dollars.<ref>{{Cite news \|last=Hill \|first=Kashmir \|date=2024-03-22 \|title=General Motors Quits Sharing Driving Behavior With Data Brokers \|url=https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|url-status=live \|archive-url=https://web.archive.org/web/20250426081230/https://www.nytimes.com/2024/03/22/technology/gm-onstar-driver-data.html \|archive-date=2025-04-26 \|work=The New York Times}}</ref>

	==See also==		==See also==

Emanuele: Added category

2025-05-08T15:49:11Z

Added category

← Older revision		Revision as of 15:49, 8 May 2025
Line 1:		Line 1:
	'''Data brokers''' are companies that collect, aggregate, analyze, and sell personal information about consumers without having a direct relationship with those individuals.<ref>{{cite web \|url=https://www.ftc.gov/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014 \|title=Data Brokers: A Call for Transparency and Accountability: A Report of the Federal Trade Commission \|publisher=Federal Trade Commission \|date=May 2014 \|access-date=2025-05-07}}</ref> These companies operate largely behind the scenes of the digital economy, accumulating vast databases of consumer information from both public and private sources to create detailed profiles used primarily for marketing, risk assessment, and other business purposes.		'''[[wikipedia:Data_broker\|Data brokers]]''' are companies that collect, aggregate, analyze, and sell personal information about consumers without having a direct relationship with those individuals.<ref>{{cite web \|url=https://www.ftc.gov/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014 \|title=Data Brokers: A Call for Transparency and Accountability: A Report of the Federal Trade Commission \|publisher=Federal Trade Commission \|date=May 2014 \|access-date=2025-05-07}}</ref> These companies operate largely behind the scenes of the digital economy, accumulating vast databases of consumer information from both public and private sources to create detailed profiles used primarily for marketing, risk assessment, and other business purposes.

	==How they work==		==How they work==
Line 40:		Line 40:

	==See also==		==See also==
	* [[LiveRamp]]		*[[LiveRamp]]

	==References==		==References==
	<references />		<references />
			[[Category:Common terms]]

86.166.162.132: /* Security vulnerabilities */

2025-05-08T06:28:01Z

Security vulnerabilities

← Older revision		Revision as of 06:28, 8 May 2025
Line 26:		Line 26:
	===Security vulnerabilities===		===Security vulnerabilities===
	The consolidation of large volumes of personal data creates security risks. Data brokers become attractive targets for hackers, and breaches of these vast repositories can expose sensitive personal information of millions of consumers, leading to identity theft and other forms of fraud.<ref>{{cite web \|url=https://www.brennancenter.org/our-work/research-reports/closing-data-broker-loophole \|title=Closing the Data Broker Loophole \|publisher=Brennan Center for Justice \|access-date=2025-05-07}}</ref>		The consolidation of large volumes of personal data creates security risks. Data brokers become attractive targets for hackers, and breaches of these vast repositories can expose sensitive personal information of millions of consumers, leading to identity theft and other forms of fraud.<ref>{{cite web \|url=https://www.brennancenter.org/our-work/research-reports/closing-data-broker-loophole \|title=Closing the Data Broker Loophole \|publisher=Brennan Center for Justice \|access-date=2025-05-07}}</ref>
			And with the search for indemnification related to being held harmless for such breaches, it is becoming harder and harder to hold these companies accountable.

	==Examples of major data brokers==		==Examples of major data brokers==