Privacy Policy

Procedure for Protecting Personal Data

Seiko Instruments Inc. and its affiliated companies (collectively “SII Group”) recognize that protecting personal data (“Personal Data”), which is information relating to an identified or identifiable individual (“Individual”) and which you provide with on the SII Group’s web sites, is of utmost importance. SII Group is adopting the following procedure to protect Personal Data.

  1. SII Group collects Personal Data, specifying the purpose for which Personal Data is collected, by lawful and fair means.
  2. SII Group uses the Personal Data only to the extent necessary to complete the explicit purpose of its collection.
  3. SII Group keeps Personal Data accurate and up-to-date, and makes every effort to protect them by reasonable security safeguards against unauthorized access, loss, destruction, falsification or leakage. Also, when submitting such Personal Data to a third party for the completion of a specific service to that individual, SII Group will supervise the handling of that data by the third party to ensure the data is protected.
  4. SII Group accepts, in principle and within a reasonable period of time, requests for access to, correction or deletion of, or refusals of use (“opt out”) or disclosure of Personal Data by the Individual.
  5. SII Group establishes or appoints a special organization or a responsible person for the handling of complaints and consultation from the Individual with respect to Personal Data.
  6. SII Group complies with applicable laws and regulations relating to protection of Personal Data.
  7. SII Group conducts periodic reviews of the management system, including the SII Group’s Privacy Policy, in order to maintain the appropriate protection of Personal Data.

* “Personal Data” means data relating to an individual such as name, date of birth, address, office, credit card number, bank account number, personal preferences or other descriptions or from numbers, symbols, other marks, images or sounds assigned to the individual (including data in which an individual cannot be directly identified, but can be identified by collating with other data).