Suspected Duplicate Processing

The Suspected Duplicate Processing feature in Open Cloud MDM provides a mechanism to identify and manage duplicate parties, ensuring the existence of a "golden" copy for each party in the system. This feature works by searching for existing parties that match the party being added or updated and associating these duplicates, or suspects, with the input party. If an exact match is found and there are no pending critical data changes for the existing party, the new party is used to update the data in the existing party instead of adding a new one.

Example Use Cases:

1. Duplicate Customer Identification:
• Description: In a customer database, it's common to have multiple entries for the same customer due to data entry errors or variations in input. Suspected Duplicate Processing can identify and link these duplicate customer records to maintain a single, accurate customer profile.
• Use Case: When a new customer record is added, the system checks for potential duplicates based on criteria like name, address, and contact information. If a matching customer exists and there are no pending critical data changes, the new data is merged into the existing customer record.
2. Patient Records in Healthcare:
• Description: Healthcare systems often encounter duplicate patient records, which can lead to medical errors and confusion. Suspected Duplicate Processing can help healthcare organizations identify and consolidate duplicate patient records.
• Use Case: When a new patient record is created, the system compares it to existing records using patient name, date of birth, and other identifying information. If a duplicate is found and there are no pending critical data changes, the new record is merged into the existing patient record.
3. Financial Institutions - Account Holders:
• Description: Banks and financial institutions may have multiple records for the same account holder. Suspected Duplicate Processing helps ensure accurate and consistent customer data.
• Use Case: When a new account holder is added, the system checks for potential duplicates based on account information, personal details, and contact information. If a matching account holder exists and there are no pending critical data changes, the new data is merged into the existing account holder's record.
4. Retail Loyalty Programs:
• Description: Retailers with loyalty programs may collect customer data through various channels. Suspected Duplicate Processing can identify and merge duplicate loyalty program members.
• Use Case: When a customer joins a loyalty program or updates their information, the system checks for duplicate members using loyalty card numbers, phone numbers, or email addresses. If a matching member exists and there are no pending critical data changes, the new data is merged into the existing member's profile.
5. Government Citizen Records:
• Description: Government agencies maintain citizen records, and duplicate records can lead to administrative challenges. Suspected Duplicate Processing helps consolidate citizen data.
• Use Case: When a new citizen record is created or updated, the system compares it to existing records using criteria like social security numbers or national identification numbers. If a matching citizen exists and there are no pending critical data changes, the new data is merged into the existing citizen record.
6. Insurance Policyholders:
• Description: Insurance companies may have duplicate records for policyholders. Suspected Duplicate Processing ensures accurate policyholder data.
• Use Case: When a new policyholder is added or updates their information, the system checks for potential duplicates based on policy numbers, names, and other policyholder details. If a matching policyholder exists and there are no pending critical data changes, the new data is merged into the existing policyholder record.

In each of these use cases, Suspected Duplicate Processing helps maintain data accuracy and consistency by identifying and handling duplicate records intelligently. It prevents the proliferation of duplicate data entries and ensures that a single, accurate "golden" copy of each party is retained in the system. The feature is highly configurable to accommodate specific matching criteria and business needs.