IP Library Granted Patent US 11,363,138
Granted Patent B2
US 11,363,138 · App. 17/078,652 · Granted Jun 14, 2022

Fraud detection system and method

Inventor: Haydar Talib (Montreal, CA)
Assignee: NUANCE COMMUNICATIONS, INC.
H04M3/42221H04M3/2281H04M3/42042H04M3/42059H04M3/436H04M2203/6027
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,363,138
App. No.
17/078,652
Granted
Jun 14, 2022
Kind
B2
Abstract

A method, computer program product, and computing system for receiving input information concerning a conversation between a caller and a recipient; processing the input information to assess a fraud-threat-level; defining a targeted response based, at least in part, upon the fraud-threat-level assessed, wherein the targeted response is intended to refine the assessed fraud-threat-level; and effectuating the targeted response.

Claims (48)

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

receiving input information concerning a conversation between a caller and a recipient, wherein the conversation includes one or more of a voice-based conversation between the caller and the recipient that is transcribed into text and a text-based conversation between the caller and the recipient;

processing the input information to assess a fraud-threat-level of a plurality of fraud-threat-levels, wherein processing the input information to determine a fraud-threat-level includes determining if the input information is indicative of fraudulent behavior by comparing biometric information of one of a word and a phrase of the input information to a plurality of fraudulent behaviors and a plurality of legitimate non-fraudulent behaviors;

defining a targeted response from the recipient to be effectuated against the caller based, at least in part, upon the fraud-threat-level assessed, wherein each fraud-threat-level of the plurality of fraud-threat-levels is associated with a different targeted response from the recipient to be effectuated against the caller, wherein the targeted response is intended to refine the assessed fraud-threat-level; and

effectuating the targeted response.

2. The computer-implemented method of claim 1 wherein the input information further includes one or more of:

a caller conversation portion transcribed into the text; and

a recipient conversation portion transcribed into the text.

3. The computer-implemented method of claim 1 wherein effectuating the targeted response includes one or more of:

allowing the conversation to continue;

asking a question of the caller;

prompting the recipient to ask a question of the caller;

effecting a transfer from the recipient to a third-party; and

ending the conversation between the caller and the recipient.

4. The computer-implemented method of claim 1 wherein the plurality of fraudulent behaviors includes a plurality of empirically-defined fraudulent behaviors.

5. The computer-implemented method of claim 4 wherein the plurality of empirically-defined fraudulent behaviors are defined via AI/ML processing of information concerning a plurality of earlier conversations.

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

receiving input information concerning a conversation between a caller and a recipient, wherein the conversation includes one or more of a voice-based conversation between the caller and the recipient that is transcribed into text and a text-based conversation between the caller and the recipient;

processing the input information to assess a fraud-threat-level of a plurality of fraud-threat-levels, wherein processing the input information to determine a fraud-threat-level includes determining if the input information is indicative of fraudulent behavior by comparing biometric information of one of a word and a phrase of the input information to a plurality of fraudulent behaviors and a plurality of legitimate non-fraudulent behaviors;

defining a targeted response from the recipient to be effectuated against the caller based, at least in part, upon the fraud-threat-level assessed, wherein each fraud-threat-level of the plurality of fraud-threat-levels is associated with a different targeted response from the recipient to be effectuated against the caller, wherein the targeted response is intended to refine the assessed fraud-threat-level; and

effectuating the targeted response.

7. The computer program product of claim 6 wherein the input information further includes one or more of:

a caller conversation portion transcribed into the text; and

a recipient conversation portion transcribed into the text.

8. The computer program product of claim 6 wherein effectuating the targeted response includes one or more of:

allowing the conversation to continue;

asking a question of the caller;

prompting the recipient to ask a question of the caller;

effecting a transfer from the recipient to a third-party; and

ending the conversation between the caller and the recipient.

9. The computer program product of claim 6 wherein the plurality of fraudulent behaviors includes a plurality of empirically-defined fraudulent behaviors.

10. The computer program product of claim 9 wherein the plurality of empirically-defined fraudulent behaviors are defined via AI/ML processing of information concerning a plurality of earlier conversations.

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

receiving input information concerning a conversation between a caller and a recipient, wherein the conversation includes one or more of a voice-based conversation between the caller and the recipient that is transcribed into text and a text-based conversation between the caller and the recipient;

processing the input information to assess a fraud-threat-level of a plurality of fraud-threat-levels, wherein processing the input information to determine a fraud-threat-level includes determining if the input information is indicative of fraudulent behavior by comparing biometric information of one of a word and a phrase of the input information to a plurality of fraudulent behaviors and a plurality of legitimate non-fraudulent behaviors;

defining a targeted response from the recipient to be effectuated against the caller based, at least in part, upon the fraud-threat-level assessed, wherein each fraud-threat-level of the plurality of fraud-threat-levels is associated with a different targeted response from the recipient to be effectuated against the caller, wherein the targeted response is intended to refine the assessed fraud-threat-level; and

effectuating the targeted response.

12. The computing system of claim 11 wherein the input information further includes one or more of:

a caller conversation portion transcribed into the text; and

a recipient conversation portion transcribed into the text.

13. The computing system of claim 11 wherein effectuating the targeted response includes one or more of:

allowing the conversation to continue;

asking a question of the caller;

prompting the recipient to ask a question of the caller;

effecting a transfer from the recipient to a third-party; and

ending the conversation between the caller and the recipient.

14. The computing system of claim 11 wherein the plurality of fraudulent behaviors includes a plurality of empirically-defined fraudulent behaviors.

15. The computing system of claim 14 wherein the plurality of empirically-defined fraudulent behaviors are defined via AI/ML processing of information concerning a plurality of earlier conversations.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 14, 2023
From: NUANCE COMMUNICATIONS, INC.
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 065578/0676 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 23, 2020
From: TALIB, HAYDAR
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 054151/0656 →