Difference between revisions of "Data brokers"

Revision as of 21:10, 14 March 2018

Data brokers refers to the industry where companies collect information on consumers and package the data for sale to businesses or government agencies. Most commonly, data is gathered by Data brokers when people carry out activities online: purchases, web searches, social media pages, etc. The data is aggregated to create profiles on individuals; and, oftentimes, this information is analyzed and people are grouped into useful lists or categories that make the information desirable for purchase. There are three main types of data broking companies: ones that create marketing, risk mitigation, or people search products. There are few laws that currently govern these companies, and ethical dilemmas have risen as a result of mass collection of personal information. Critics argue that consumers are often not aware that data brokers are acquiring data about them, and believe that companies violate the privacy of these individuals and could potentially jeopardize the safety of consumers. There are further concerns regarding the categorization of individuals, and the potential mistreatment and repercussions that can stem from sensitive grouping.

Origins

In 1965, Gordon Moore noticed the fast-paced improvement of transistors on a chip, and observed that they doubled every year from 1959-1965 ^[1]. This later became known as Moore's Law, which is the expectation that transistors will continue to double every two years. The cost of computing has decreased as well, allowing for the improvement of software and hardware.

The rapid advancement of more powerful computing, networking, and data storage has led to the field of Big data. Big data is the collection and analysis of large amounts of data by both government agencies and corporations ^[1]. The Big Data field has allowed for the formation of the Data Broking industry. Companies began to enter the market that specialized in various types of massive data collection and analysis. After data is collected data brokers use algorithms to predict an individual's health, financial status, interests, sexual orientation, religion, political beliefs, and habits. This data is then sold to government agencies and corporations who use the information for a variety of different purposes: verifying an individual's identity, marketing products, and detecting fraud.

Data Collection

Most often consumers are not aware of the existence of data broking companies, and do not know that data is being collected about them. In May 2014, the Federal Trade Commission (FTC) released a report that shed light on the Data broker industry, Data Brokers: A Call for Transparency and Accountability. Before this report, the interworking of the Data broker industry was a mystery. Within the document the FTC listed the main Data broker sources: the government, publicly available sources (social media, blogs, the internet), and commercial data sources.

Government Sources

Data brokers gather information from the federal, state, and local governments. The government agencies that are typically used are the U.S Census Bureau, Social Security Administration, U.S Postal Service, Federal Bureau of Investigation, U.S Secret Service, and the European Union. These sources provide information on these individuals: ethnicity, age, education level, household makeup, income, occupations, commute times, and addresses. The U.S Secret Service and European Union give access to most wanted lists or terrorists watch lists ^[2]. State and local governments provide information, including licenses, real property and assessor records, assessed value, liens, deeds, mortgages, mortgage releases, pre-foreclosures, identifying information about the owner, voter registration information, motor vehicle and driving records, and court records.

The information collected from government sources is not always directly accumulated from state and local governments. Data brokers will hire individuals to go to these local offices to gather the data. Another means of collecting data is through relationships with these offices that give them access to the data automatically ^[2]. There are some state laws that prohibit companies from gathering personal information from government sources. For example, the Federal Driver's Privacy Protection Act ("DPPA") which does not allow the release of motor vehicle and driving recorded information unless it is used for or requested by law enforcement, insurance, and identity verification or fraud detection ^[3]. Also twenty-two states do not allow the use of voter registration record for commercial or non-election related purposes ^[2].

Publicly Available Sources

Data Brokers get information from publicly available sources such as directories, press reports, and posts on the internet ^[2]. One technique these companies use to collect information is web crawling. Web crawlers are programs that search through the web in an automated way, and it reports the data back to a specified server ^[4]. When users do not set their privacy settings to restrict access to their information on various sites, Data brokers will pull all available information from these websites. For example, they will crawl individuals' social media profiles for information.

Aside from web crawling, Data brokers have other methods they use to collect information from publicly available sources. They will buy or acquire printed information, like records or directories. They also arrange for collection processing of information. For example, they acquire data from a daily news feed. The final way they gather data is through Application Programing Interface (API). They arrange for their sources to make available an API where they process the data ^[2].

Commercial Data Sources

Data brokers gather data from commercial sources: retailers, catalog companies, magazine publishers, registration websites, merchants and financial service clients. This information can include types of purchases or subscriptions sold, how much they paid, dates of purchase, and method of payment. Registration websites refers to sites where consumers receive services, such as retail, news, finances, and travel. In the FTC report, they found that data brokers get personal information from financial service companies, like data regarding health related purchases ^[2].

Data brokers get over 50 percent of their data from other data brokers ^[2]. Information gets repeatedly cycled back and forth from one data broking company to another. Oftentimes, information does not come from the original source, which makes finding a data element's origin nearly impossible.

Examples of Data Brokers

There are three main types of products that data broking companies provide: marketing products, people search and risk mitigation.

Marketing Products

Acxiom

Acxiom is public data broker company founded in 1969 ^[5]. In 2017 the company had a revenue of 880.2 million which is a 3.2 percent increase from 2016 ^[6]. Today, the company mainly uses the data it collects on individuals to provide marketing products for a wide range of companies; but, they do offer two more data products which are aimed at helping to reduce fraud and identity theft, as well as people search products for helping to find certain businesses or people.

Their marketing product allows companies to carry-out people-based marketing, and receive a higher return on their marketing investments ^[6]. People-based marketing refers to creating relevant advertisements, better service, improved offerings, and special promotions for consumers. ^[7]. According to an Acxiom brochure, Understanding Acxiom's Marketing Products, the company groups people together and forms lists based on similar characteristics. These lists help assist marketing strategies by providing the target customers for a product or service, and ways to reach the market of interest. For example, Acxiom has a Personicx cluster, which categorizes people into one of 70 segments based on demographics. The 70 clusters are based on 21 life stages: having a baby, retirement, marriage, income, etc ^[8] “Consumer Data Information.” Acxiom, 2018, www.acxiom.com/about-us/privacy/consumer-data-information/. </ref>.

Risk Mitigation

ID Analytics

ID Analytics offers products that deal with identity authentication, fraud, identity risk, and creditworthiness. They try and help companies prevent fraud and decrease credit risk. According to ID Analytics website, they study the connections and relationships of identity elements. From this data they are able to assess the risk by a range of individuals behaviors ^[9].

The company rates consumers on a scale based on personal information and connections made by the software, called an ID score. The personal information they use when calculating an ID score is data like social security numbers, name, address, and emails. ID Score First-Party Fraud algorithm looks for attributes that typically categorize thieves, and their is a particular score that is used to recognize them Cite error: Closing </ref> missing for <ref> tag Specifically going to talk about the ethical concerns of “data brokers” in regards to privacy. The data that we don't know is being collected and shared about us.

1. ↑ ^{1.0 1.1} Richards, Neil M.; King, Jonathan H. "Big Data Ethics," Wake Forest Law Review vol. 49, no. 2 (2014): p. 393-432, http://heinonline.org/HOL/Page?handle=hein.journals/wflr49&div=16&g_sent=1&casa_token=&collection=journals.
2. ↑ ^{2.0 2.1 2.2 2.3 2.4 2.5 2.6} Ramirez, Edith , et al. "Data Brokers: A Call For Transparency and Accountability." Federal Trade Commission, 27 May 2014, www.ftc.gov/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014.
3. ↑ "18 U.S. Code § 2721 - Prohibition on release and use of certain personal information from State motor vehicle records." LII / Legal Information Institute, www.law.cornell.edu/uscode/text/18/2721.
4. ↑ "Web crawler." ScienceDaily, ScienceDaily, www.sciencedaily.com/terms/web_crawler.htm.
5. ↑ “Company-Histories.com.” Acxiom Corporation -- Company History, www.company-histories.com/Acxiom-Corporation-Company-History.html.
6. ↑ ^{6.0 6.1} "PDF." Acxiom Corporation, 2017, https://s21.q4cdn.com/580938034/files/doc_financials/annual_reports/Annual-Report-2017-(Web-ready).pdf.
7. ↑ "PDF." Acxiom Corporations, 2012, https://www.acxiom.com/wp-content/uploads/2013/09/Acxiom-Marketing-Products.pdf.
8. ↑ Cite error: Invalid <ref> tag; no text was provided for refs named Acxiom_Website
9. ↑ “Personal Topology – ID Analytics.” ID Analytics, ID Analytics, 2018, www.idanalytics.com/our-business-model/personal-topology/.
10. ↑ Cite error: Invalid <ref> tag; no text was provided for refs named Citation