Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: In a business where a database tracks customers and manages customer accounts, a method and system correctly link accounts with customers. The method entails reading customer information for a first customer and for a second customer, and then utilizing personal identification information obtained from other sources to determine if the first customer is the same as the second customer. If the first customer and the second customer are the same person, the first customer and the second customer are identified as being the same unique person. Accounts associated with the two customers are identified as belonging to the same unique person. Viewed another way, the method and system of the present invention takes an existing database of personal identification information, and cross-references that database against other sources of personal identification information to identify persons who appear to be separate persons, but who are actually one and the same individual.

Abstract: In a business where a database tracks customers and manages customer accounts, a method and system correctly link accounts with customers. The method entails reading customer information for a first customer and for a second customer, and then utilizing personal identification information obtained from other sources to determine if the first customer is the same as the second customer. If the first customer and the second customer are the same person, the first customer and the second customer are identified as being the same unique person. Accounts associated with the two customers are identified as belonging to the same unique person. Viewed another way, the method and system of the present invention takes an existing database of personal identification information, and cross-references that database against other sources of personal identification information to identify persons who appear to be separate persons, but who are actually one and the same individual.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: Systems and methods that identify and manage partner relationships are disclosed. A third-party trustee collects and processes confidential customer information from more than one interested parties. The third-party trustee acts as a neutral intermediary between the parties. The third-party trustee processes and analyzes the information received from the various parties to identify mutual and/or prospective customers between the interested parties. The processing results may then be used for further analysis to help at least one of the interested parties to improve their marketing efforts, risk management, and servicing of their customers.

Abstract: Systems and methods that identify and manage partner relationships are disclosed. A third-party trustee collects and processes confidential customer information from more than one interested parties. The third-party trustee acts as a neutral intermediary between the parties. The third-party trustee processes and analyzes the information received from the various parties to identify mutual and/or prospective customers between the interested parties. The processing results may then be used for further analysis to help at least one of the interested parties to improve their marketing efforts, risk management, and servicing of their customers.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: The disclosed methods, systems, and computer-program products allow a business to estimate linking errors in customer relationships in a database and to identify metrics that improve the linking accuracy. In an embodiment, a plurality of sample customer relationships are selected from a database to form a sample data set that is statistically representative of the database. Potential linking errors are then identified within the sample data set. The identified potential linking errors are then validated to identify actual linking errors in the sample data set. Once validated, the actual linking errors within the sample data set are used to estimate linking errors within the database. Further, the estimated linking errors in the database may be analyzed to identify one or more factors that contribute to the linking errors.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: The disclosed methods, systems, and computer-program products allow a business to generate data quality indicators for relationships in a database. In an embodiment, one or more relationships linked to a customer are retrieved from a database to form a set of relationships. A match confidence code is generated for each relationship based on a score generated by the comparison of customer data associated with the respective relationship and corresponding customer data obtained from an external industry database. A link confidence code is subsequently determined for the customer based on a score generated by the scores used to define the match confidence code for each relationship in the set of relationships and on internal data associated with each relationship in the set of relationships.

Abstract: The disclosed methods, systems, and computer-program products allow a business to estimate linking errors in customer relationships in a database and to identify metrics that improve the linking accuracy. In an embodiment, a plurality of sample customer relationships are selected from a database to form a sample data set that is statistically representative of the database. Potential linking errors are then identified within the sample data set. The identified potential linking errors are then validated to identify actual linking errors in the sample data set. Once validated, the actual linking errors within the sample data set are used to estimate linking errors within the database. Further, the estimated linking errors in the database may be analyzed to identify one or more factors that contribute to the linking errors.

Abstract: In an enterprise where a database maintains multiple accounts for one or more business customers, a method, system, and computer program product correctly links accounts which are associated with a single location of a common business. Further hierarchical linkages are established between accounts associated with multiple locations of the common business. The linkages are established via matching rules, the matching rules including provisions for optimizing the quality of the account data, integrating account-related data from external sources, and assigning quality-of-matching factors to different kinds of account data. Both internal and external account data are utilized to create an integrated view, or “business demographics”, of the business structure of the single common business shared by the linked, hierarchically-related accounts. Separate accounts of separate businesses which are nonetheless related accounts may be associated with each other.

Abstract: Systems and methods that identify and manage partner relationships. The systems and methods presented herein provide that a third-party trustee collect and process confidential customer information from a plurality of interested parties. The third-party trustee acts as a neutral intermediary between the parties. The third-party trustee processes and analyzes the information received from the various parties to identify mutual and/or prospective customers between the interested parties. The processing results may then be used for further analysis to help one or more of the interested parties to improve their marketing efforts, risk management, and servicing of their customers.

Abstract: Systems and methods that identify and manage partner relationships. The systems and methods presented herein provide that a third-party trustee collect and process confidential customer information from a plurality of interested parties. The third-party trustee acts as a neutral intermediary between the parties. The third-party trustee processes and analyzes the information received from the various parties to identify mutual and/or prospective customers between the interested parties. The processing results may then be used for further analysis to help one or more of the interested parties to improve their marketing efforts, risk management, and servicing of their customers.