As the use of computer systems has evolved, a growing mass of data about people and organizations has been, and is continually being, collected and processed. In most cases this data is associated with a formal identity such as an account number, national identity number etc., and it is true that the majority of accesses to this data will be made by that identification number.

In many countries, however, every important service that could be provided to a person, company, business or household, has been computerized, and this has led to a proliferation of identification numbers. Due to the size of our growing populations, this has also meant that such numbers and codes are increasing in diversity and complexity. The opportunities for an identity number to be incorrect are increasing every day, despite our attempts at reliability through the use of check-digits, bar-codes and codes built from actual identification data.

In addition, some systems must cope with finding and matching data when there is no stable or reliable identification number available, (for example, police persons of interest, directory inquiries, prospect and marketing lists, intra-organization data matching, check payments with no payment slip, fraud investigation systems, grouping of accounts in a bank or insurance company application, data warehouse creation, credit reference checking etc.).

Another factor affecting the availability of identity numbers is that many people do not have them readily available when making an inquiry or filling out a form, and often even if they do, do not provide them.

The need for retrieval or matching of databases on names and addresses has become quite common and well known and the number of applications where ’name searching and matching’ techniques are needed is growing rapidly.