Conversation print system and method

1. A computer-implemented method, executed on a computing device, comprising:

defining a conversation print for each of a plurality of known entities, thus defining a plurality of conversation prints, wherein the conversation print includes a text-based transcript of one or more prior voice-based content received from at least one known entity of the plurality of known entities, and wherein the conversation print defines speech-pattern indicia that includes frequency of only a single word chosen and used by the at least one known entity over a similar single word chosen and used by another person, and wherein the conversation print further defines speech-pattern indicia that includes one or more inflection patterns defined within the one or more prior voice-based content, wherein the one or more inflection patterns include a location of one or more inflections in one or more sentences, wherein the conversation print is further based upon, at least in part, one or more pause patterns, speech speed patterns, word character length patterns, and filler word patterns of the one or more pause patterns defined within the voice-based content;

receiving voice-based content from a third-party; and

comparing the voice-based content to at least one of the plurality of conversation prints, including the one or more inflection patterns, the location of one or more inflections in one or more sentences, the speech speed patterns, the one or more pause patterns, the word character length patterns, and the filler word patterns of the one or more pause patterns of the voice-based content, to identify the third-party;

determining if the third-party includes a known fraudster based upon comparing the voice-based content to the at least one of the plurality of conversation prints;

continuing a call with the third-party if the subsequent call does not include the known fraudster; and

taking remedial action if the call does include the known fraudster, wherein remedial action includes at least one of terminating the call and providing a notification that the call does include the known fraudster.

2. The computer-implemented method of claim 1 wherein the plurality of known entities includes at least one authorized user.

3. The computer-implemented method of claim 1 wherein each conversation print defines speech-pattern indicia that includes:

one or more accent patterns defined within the voice-based content.

4. The computer-implemented method of claim 1 wherein each conversation print defines speech-pattern indicia that includes:

one or more word choices patterns defined within the voice-based content.

5. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

defining a conversation print for each of a plurality of known entities, thus defining a plurality of conversation prints, wherein the conversation print includes a text-based transcript of one or more prior voice-based content received from at least one known entity of the plurality of known entities, and wherein the conversation print defines speech-pattern indicia that includes frequency of only a single word chosen and used by the at least one known entity over a similar single word chosen and used by another person, and wherein the conversation print further defines speech-pattern indicia that includes one or more inflection patterns defined within the one or more prior voice-based content, wherein the one or more inflection patterns include a location of one or more inflections in one or more sentences, wherein the conversation print is further based upon, at least in part, one or more pause patterns, speech speed patterns, word character length patterns, and filler word patterns of the one or more pause patterns defined within the voice-based content;

receiving voice-based content from a third-party; and

comparing the voice-based content to at least one of the plurality of conversation prints, including the one or more inflection patterns, the location of one or more inflections in one or more sentences, the speech speed patterns, the one or more pause patterns, the word character length patterns, and the filler word patterns of the one or more pause patterns of the voice-based content, to identify the third-party;

determining if the third-party includes a known fraudster based upon comparing the voice-based content to the at least one of the plurality of conversation prints;

continuing a call with the third-party if the subsequent call does not include the known fraudster; and

taking remedial action if the call does include the known fraudster, wherein remedial action includes at least one of terminating the call and providing a notification that the call does include the known fraudster.

6. The computer program product of claim 5 wherein the plurality of known entities includes at least one authorized user.

7. The computer program product of claim 5 wherein each conversation print defines speech-pattern indicia that includes:

one or more accent patterns defined within the voice-based content.

8. The computer program product of claim 5 wherein each conversation print defines speech-pattern indicia that includes:

one or more word choice patterns defined within the voice-based content.

9. A computing system including a processor and memory configured to perform operations comprising:

defining a conversation print for each of a plurality of known entities, thus defining a plurality of conversation prints, wherein the conversation print includes a text-based transcript of one or more prior voice-based content received from at least one known entity of the plurality of known entities, and wherein the conversation print defines speech-pattern indicia that includes frequency of only a single word chosen and used by the at least one known entity over a similar single word chosen and used by another person, and wherein the conversation print further defines speech-pattern indicia that includes one or more inflection patterns defined within the one or more prior voice-based content, wherein the one or more inflection patterns include a location of one or more inflections in one or more sentences, wherein the conversation print is further based upon, at least in part, one or more pause patterns, speech speed patterns, word character length patterns, and filler word patterns of the one or more pause patterns defined within the voice-based content;

receiving voice-based content from a third-party; and

comparing the voice-based content to at least one of the plurality of conversation prints, including the one or more inflection patterns, the location of one or more inflections in one or more sentences, the speech speed patterns, the one or more pause patterns, the word character length patterns, and the filler word patterns of the one or more pause patterns of the voice-based content, to identify the third-party;

determining if the third-party includes a known fraudster based upon comparing the voice-based content to the at least one of the plurality of conversation prints;

continuing a call with the third-party if the subsequent call does not include the known fraudster; and

taking remedial action if the call does include the known fraudster, wherein remedial action includes at least one of terminating the call and providing a notification that the call does include the known fraudster.

10. The computing system of claim 9 wherein the plurality of known entities includes at least one authorized user.

11. The computing system of claim 9 wherein each conversation print defines speech-pattern indicia that includes:

one or more accent patterns defined within the voice-based content.

12. The computing system of claim 9 wherein each conversation print defines speech-pattern indicia that includes:

one or more word choice patterns defined within the voice-based content.