Risk assessment using social networking data
First Claim
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1. A computer-implemented method for calculating a risk score for an entity account, the method comprising:
- a) receiving, by an electronic processor of a computer system, an indication that a user has requested evaluation of risk for a particular entity account by activating a link in an electronic communication, activating an element of a web or mobile application, or initiating a transaction that calls an API;
b) calculating, by the processor, an entity score in response to at least a portion of profile data associated with at least one online or mobile network of a first entity account, wherein the calculation comprises comparing at least a portion of the profile data of the first entity account to at least one reference profile model associated with at least one online or mobile network, wherein the at least one reference profile model comprises a fake profile;
c) calculating, by the processor, a connections score in response to at least one connection formed between the first entity account and at least a second entity account through the online or mobile network;
d) calculating, by the processor, an affinity score in response to an overlap between at least a portion of the profile data of the first entity account and at least a portion of profile data associated with at least a second entity account;
e) combining, by the processor, the calculated entity score, the calculated connections score, and the calculated affinity score to yield a risk score for at least the first entity account; and
f) determining, by the processor, accuracy of the risk score for the first entity by comparing the calculated risk score against an average score range for at least one cluster of other entities with similar affinity scores, wherein the accuracy is used to improve the at least one reference profile model.
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Abstract
Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect individual consumers, business enterprises, and other organizations from identity theft and fraud. Risks associated with various entities can be analyzed and assessed based on analysis of social network data, professional network data, or other networking connections, among other data sources. In various embodiments, the risk assessment may include calculating an authenticity score based on the collected network data.
59 Citations
21 Claims
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1. A computer-implemented method for calculating a risk score for an entity account, the method comprising:
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a) receiving, by an electronic processor of a computer system, an indication that a user has requested evaluation of risk for a particular entity account by activating a link in an electronic communication, activating an element of a web or mobile application, or initiating a transaction that calls an API; b) calculating, by the processor, an entity score in response to at least a portion of profile data associated with at least one online or mobile network of a first entity account, wherein the calculation comprises comparing at least a portion of the profile data of the first entity account to at least one reference profile model associated with at least one online or mobile network, wherein the at least one reference profile model comprises a fake profile; c) calculating, by the processor, a connections score in response to at least one connection formed between the first entity account and at least a second entity account through the online or mobile network; d) calculating, by the processor, an affinity score in response to an overlap between at least a portion of the profile data of the first entity account and at least a portion of profile data associated with at least a second entity account; e) combining, by the processor, the calculated entity score, the calculated connections score, and the calculated affinity score to yield a risk score for at least the first entity account; and f) determining, by the processor, accuracy of the risk score for the first entity by comparing the calculated risk score against an average score range for at least one cluster of other entities with similar affinity scores, wherein the accuracy is used to improve the at least one reference profile model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A computer-implemented system for calculating a risk score for an entity account, the system comprising:
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a) at least one processor, an operating system configured to perform executable instructions, and a memory; b) a computer program including instructions executable by the at least one processor to create an application comprising; i) a software module receiving an indication that a user has requested evaluation of risk for a particular entity account by activating a link in an electronic communication, activating an element of a web or mobile application, or initiating a transaction that calls an API; ii) a software module calculating an entity score in response to at least a portion of profile data associated with at least one online or mobile network of a first entity account, wherein the calculation comprises comparing at least a portion of the profile data of the first entity account to at least one reference profile model associated with at least one online or mobile network, wherein the at least one reference profile model comprises a fake profile; iii) a software module calculating a connections score in response to at least one connection formed between the first entity account and at least a second entity account through the online or mobile network; iv) a software module calculating an affinity score in response to an overlap between at least a portion of the profile data of the first entity account and at least a portion of profile data associated with at least a second entity account; v) a software module combining the calculated entity score, the calculated connections score, and the calculated affinity score to yield a risk score for at least the first entity account; and vi) a software module determining accuracy of the risk score for the first entity by comparing the calculated risk score against an average score range for at least one cluster of other entities with similar affinity scores, wherein the accuracy is used to improve the at least one reference profile model.
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Specification