overview

This note considers what is variously characterised as the consumer data trading, list broking or data aggregation industry.

It covers -

• this overview
• demand - who uses information from data traders
• supply - where does data come from
• agents - questions about responsibility and use of intermediaries
• access - access by consumers to the data
• regulation - data protection and other law
• snapshots - concise profiles of leading enterprises
• studies - major works on law and practice
• landmarks - illustrating international expansion and consolidation

It complements discussion of privacy, consumer credit referencing and vetting services elsewhere on this site.

     introduction

The term 'data trading' is used by different people to characterise a range of practices and organisations, including -

• compilation and sale of large-scale direct marketing databases (eg comprehensive lists of contact details sorted by attributes such as age, income, location, disability, religious affiliation)
• creation of market research tools that provide end-users with aggregated rather than personally identified information
• maintenance and sale of databases that allow insurers, retailers, health service providers and lenders to assess and minimise risk
• commercial access to databases that integrate public and private sector records and thus can provide a basis for employment vetting or profiling of suspected terrorists and other criminals
• provision of information that is specific to an individual and has been gained through pretexting or other illicit mechanisms.

It reflects a blurring of traditional demarcations between credit reference services, business directories, market research, identity verification and private investigation services (including 'skiptracing'), and direct mail lists.

It has been hailed as a basis for the 'market of one', in which consumer needs are accurately identified and satisfied (even anticipated). It has been criticised as central to the contemporary 'security-industrial complex', as embodying pervasive categorisation and surveillance of consumers, as rife with legal or ethical problems, and as resulting in blizzards of print/electronic junkmail.

Data trading as an industry is little known and even less understood, with arguably inadequate regulation of the compilation, maintenance and sale of databases (some of which include information on over 200 million people) and problematical implementation of mechanisms aimed at restricting practices that are clearly illegal or that are situated on the fringes of legality.

Ultimately most data trading reflects the existence and ongoing generation of large amounts of information (albeit information that often only enables a fuzzy identification of individuals and is rapidly superseded) that can be readily accessed, sorted and communicated.

It also reflects the creation of value through amalgamation of discrete data sets to either verify particular attributes or to enable sorting by specified characteristics.

As discussed in the following pages of this note a direct marketer might thus buy electronic access to a database that is claimed to provide all postal addresses for a particular location (which might be a street, a suburb, a city or a whole nation). That information might be matched with a list of people who have recently retired and then with a list of people who are perceived as good credit risks. The 'risk' listing might have been developed through a process of exclusion, eg removing anyone who appears on lists of bankrupts, loan defaults, criminal convictions, suspected insurance fraud or long-term illness.

To achieve greater 'granularity' it might be matched with lists of people who are affiliated with particular organizations (eg a political party, an environmental advocacy group, a church), in a particular profession and who have recently engaged in particular transactions (eg bought a sports car, visited an overseas resort, bought wine to a certain value online from a specialist retailer). It might be further targeted through matching with lists of avocations or other attributes, for example people who have a gun licence, people who own several cars, people who own several cars and a yacht, people who are not married.

Manual identification and sorting of such information is difficult and expensive.

     precursors

Trade in personal and corporate information dates from at least the beginnings of the Industrial revolution, with compilation of commercial directories of institutions and enterprises that resemble contemporary 'colour pages' phone directories and restaurant guides. Those publications included works on the best places to buy gloves in pre-revolutionary Paris and ratings on the best brothels in Georgian London and 1850s New York, for example Harris's List of Covent Garden Ladies 1757 to 1795 described in The Covent Garden Ladies: Pimp General Jack and The Extraordinary Story of Harris’s List (Stroud: Tempus 2005) by Hallie Rubenhold and the 1856 Guide to the Harem, or Directory to the Ladies of Fashion in New York and Various Other Cities.

As discussed elsewhere on this site, the same period saw efforts to identify and minimise commercial risk through development of privately operated registers about the credit-worthiness of individuals and businesses (the precursors of contemporary consumer credit reference services and corporate rating services).

     next page  (demand)