Find Canadian Social Insurance Number

Canada’s social insurance number (SIN) was created in 1964 to serve as a client account number in the administration of the Canada Pension Plan and Canada's varied employment insurance programs. In 1967, Revenue Canada (now the Canada Revenue Agency) started using the SIN for tax reporting purposes. Today, SINs are issued by Human Resources and Social Development Canada. The SIN is formatted as three groups of three digits (e.g., 123-456-789).

Through functionality creep, the SIN has become a national identification number, in much the same way that the Social Security Number has in the United States. However, unlike in the US, in Canada there are specific legislated purposes for which a SIN can be requested. Examples of organizations that legitimately require a SIN include employers, banks and investment companies, and federal government agencies. As a result of these uses, SINs are considered sensitive and targeted by data thieves. To prevent data loss, Identity Finder finds and protects Canadian Social Insurance Numbers.

Identity Finder first starts with deep, deep data analysis. When Identity Finder comes across data that could potentially be a match, it applies proprietary validation techniques our data experts have developed after extensive data analysis to determine whether the data is likely to be a Canadian Social Insurance Number. For example, Canadian SINs must adhere to the Luhn Algorithm. Identity Finder’s techniques are updated every month with new information to increase accuracy.

Beyond deep data analysis, Identity Finder also performs contextual analysis to increase the accuracy of returning relevant information. By performing contextual analysis, Identity Finder can ascertain whether the data is being referred to in a way that would also indicate it is relevant to an end user. Finally, Identity Finder puts all of this power into the hands of the user. Although the software supports defaults that have been configured by our data analytic experts, users may tune the sensitivity of the search and cater it to the unique data set they are searching within their own internal environment.