Semantic processing of customer communications

1. An electronic computing device, comprising:

a processing unit; and

system memory, the system memory including instructions which, when executed by the processing unit, cause the electronic computing device to:

receive, at a text translator, a communication, the communication including voice data associated with a customer of an institution, the voice data being received from one or more other electronic computing devices;

transcribe, using the text translator, the voice data into text data;

parse, using a natural language processor of the processing unit, the text data;

derive relationships from the parsed text data;

use at least one of the derived relationships to identify the customer as an individual for which a remedial action is warranted;

use at least one of the derived relationships to identify another individual that belongs to a consumer household of the customer;

use a machine configured to crawl the web to capture semantically tagged information based on the transcribed text data, the semantically tagged information being related to the identified another individual, to provide contextual information for the communication, the contextual information not being available from the communication; and

display, based on the contextual information, a visual representation of the derived relationships, wherein the visual representation shows that the customer needs remedial action and the another individual belongs to the consumer household.

2. The electronic computing device of claim 1 , wherein the instructions, when executed by the processing unit, cause the processing unit to use at least one of the derived relationships to predict future behavior of the customer.

3. The electronic computing device of claim 1 , wherein the instructions, when executed by the processing unit, cause the processing unit to use the derived relationships to enhance marketing efforts for the customer.

4. The electronic computing device of claim 1 , wherein the instructions, when executed by the processing unit, cause the processing unit to provide a link for viewing the visual representation.

5. The electronic computing device of claim 1 , wherein the visual representation includes a two-dimensional graph.

6. The electronic computing device of claim 1 , wherein the instructions, when executed by the processing unit, cause the processing unit to apply logic and statistical models to generate one or more recommendations for the customer.

7. The electronic computing device of claim 6 , wherein the instructions, when executed by the processing unit, cause the processing unit to update the statistical models using supervised and unsupervised learning methods.

8. The electronic computing device of claim 1 , wherein the contextual information relates to an industry associated with the customer.

9. The electronic computing device of claim 1 , wherein to parse includes parsing the text data into a subject, a predicate, and an object.

10. The electronic computing device of claim 1 , wherein the instructions, when executed by the processing unit, cause the processing unit to infer that the consumer household has at least a predefined minimum bank account balance.

11. A computer-implemented method, comprising:

receiving, at a text translator, a communication, the communication including voice data associated with a customer of an institution, the voice data being received from one or more other electronic computing devices;

transcribing, using the text translator, the voice data into text data;

parsing, using a natural language processor, the text data;

deriving relationships from the parsed text data;

using at least one of the derived relationships to identify the customer as an individual for which a remedial action is warranted;

using at least one of the derived relationships to identify another individual that belongs to a consumer household of the customer;

using a machine configured to crawl the web to capture semantically tagged information based on the transcribed text data, the semantically tagged information being related to the identified another individual, to provide contextual information for the communication, the contextual information not being available from the communication; and

displaying, based on the contextual information, a visual representation of the derived relationships, wherein the visual representation shows that the customer needs remedial action and the another individual belongs to the consumer household.

12. The computer-implemented method of claim 11 , comprising using at least one of the derived relationships to predict future behavior of the customer.

13. The computer-implemented method of claim 11 , further comprising using the derived relationships to enhance marketing efforts for the customer.

14. The computer-implemented method of claim 11 , further comprising providing a link for viewing the visual representation.

15. The computer-implemented method of claim 11 , wherein the visual representation includes a two-dimensional graph.

16. The computer-implemented method of claim 11 , further comprising applying logic and statistical models to generate one or more recommendations for the customer.

17. The computer-implemented method of claim 16 , further comprising updating the statistical models using supervised and unsupervised learning methods.

18. The computer-implemented method of claim 11 , wherein the contextual information relates to an industry associated with the customer.

19. The computer-implemented method of claim 11 , wherein parsing includes parsing the text data into a subject, a predicate, and an object.

20. The computer-implemented method of claim 11 , further comprising inferring that the consumer household has at least a predefined minimum bank account balance.