HEURISTIC IDENTITY AUTHENTICATION ENGINE
A heuristic engine includes capabilities to collect an unstructured data set and authenticate a user's identity. By providing a heuristic algorithm with unstructured data, such as question and answer sets related to a user's activities in the past, a correlation factor can be calculated with a current context. Authenticating users using heuristic algorithms ensures precision and predictability of authentication decisions. Such heuristic algorithms may learn from each interaction and improve the accuracy of authentication decisions in the future.
1 . A computer-implemented method, executed with a computer processor, to authenticate an identity in a transaction, comprising:
retrieving, with the computer processor, an un-structured transaction data set associated with a customer;
receiving, with the computer processor and via a human-machine interface, an encoded context indicating a natural language input received from the customer, wherein the natural language input is associated with past usage of at least one account;
accessing, with the computer processor, a heuristic algorithm;
generating, by executing the heuristic algorithm with the computer processor, and using the un-structured transaction data set and the natural language input as inputs to the heuristic algorithm:
a suggested set of identity authentication questions, and
a set of expected identity authentication answers corresponding to the suggested set of identity authentication questions;
receiving, with the computer processor, an indication of a customer response to at least one question of the suggested set of identity authentication questions; and
training, with the computer processor, the heuristic algorithm using machine learning, wherein the machine learning updates the heuristic algorithm based at least partly on a correlation factor between the set of expected identity authentication answers and the customer response to the at least one question.
2 . (canceled)
3 . (canceled)
4 . The computer-implemented method of claim 1 , wherein the un-structured transaction data set comprises information indicative of past transactions related to the at least one account.
5 . The computer-implemented method of claim 1 , wherein the un-structured transaction data set is retrieved by the computer processor from an external transaction server.
6 . The computer-implemented method of claim 1 , wherein the heuristic algorithm is accessed by the computer processor from an external heuristic server.
7 . (canceled)
8 . A computer system configured to authenticate an identity in a transaction, the computer system comprising at least one of a processor or a transceiver configured to:
retrieve an un-structured transaction data set associated with a customer;
receive an encoded context via a human-machine interface, the encoded context indicating a natural language input received from the customer, wherein the natural language input is associated with past usage of at least one account;
access a heuristic algorithm;
generate, by executing the heuristic algorithm using the un-structured transaction data set and the natural language input as inputs to the heuristic algorithm:
a suggested set of identity authentication questions, and
a set of expected identity authentication answers corresponding to the suggested set of identity authentication questions;
receiving an indication of a customer response to at least one question of the suggested set of identity authentication questions; and
train the heuristic algorithm using machine learning, wherein the machine learning updates the heuristic algorithm based at least partly on a correlation factor between the set of expected identity authentication answers and the customer response to the at least one question.
9 . (canceled)
10 . (canceled)
11 . The computer system of claim 8 , wherein the un-structured transaction data set comprises information indicative of past transactions related to the at least one account.
12 . The computer system of claim 8 , wherein the un-structured transaction data set is retrieved from an external transaction server.
13 . The computer system of claim 8 , wherein the heuristic algorithm is accessed from an external heuristic server.
14 . A non-transitory computer readable medium, comprising computer readable instructions that, when executed by a computer processor, cause the computer processor to:
retrieve an un-structured transaction data set associated with a customer;
receive an encoded context via a human-machine interface, the encoded context indicating a natural language input received from the customer, wherein the natural language input is associated with past usage of at least one account;
access a heuristic algorithm;
generate, by executing the heuristic algorithm using the un-structured transaction data set and the natural language input as inputs to the heuristic algorithm:
a suggested set of identity authentication questions, and
a set of expected identity authentication answers corresponding to the suggested set of identity authentication questions;
receive an indication of a customer response to at least one question of the suggested set of identity authentication questions; and
train the heuristic algorithm using machine learning, wherein the machine learning updates the heuristic algorithm based at least partly on a correlation factor between the set of expected identity authentication answers and the customer response to the at least question.
15 . (canceled)
16 . (canceled)
17 . The non-transitory computer readable medium of claim 14 , wherein the un-structured transaction data set comprises information indicative of past transactions related to the at least one account.
18 . The non-transitory computer readable medium of claim 14 , wherein the un=structured transaction data set is retrieved from an external transaction server.
19 . The non-transitory computer readable medium of claim 14 , wherein the heuristic algorithm is accessed from an external heuristic server.
20 . (canceled)
21 . The computer-implemented method of claim 1 , further comprising:
generating, by the computer processor and using the heuristic algorithm, an authentication score based upon the customer response; and
determining, with the computer processor, an identity authentication result by determining that the authentication score exceeds a threshold score.
22 . The computer-implemented method of claim 21 , wherein the transaction is initiated by the customer, and the threshold score indicates a level of authentication required to perform the transaction.
23 . The computer system of claim 8 , wherein the at least one of the processor or the transceiver is further configured to:
generate, using the heuristic algorithm, an authentication score based upon the customer response; and
determine an identity authentication result by determining that the authentication score exceeds a threshold score.
24 . The computer system of claim 23 , wherein the transaction is initiated by the customer, and the threshold score indicates a level of authentication required to perform the transaction.
25 . The non-transitory computer readable medium of claim 14 , wherein the computer readable instructions further cause the computer processor to:
generate, using the heuristic algorithm, an authentication score based upon the customer response; and
determine an identity authentication result by determining that the authentication score exceeds a threshold score.
26 . The non-transitory computer readable medium of claim 25 , wherein a transaction is initiated by the customer, and the threshold score indicates a level of authentication required to perform the transaction.
27 . The computer-implemented method of claim 1 , further comprising:
presenting the at least one question of the suggested set of identity authentication questions to the customer via a computer terminal,
wherein the customer response is received via the computer terminal.
28 . The computer-implemented method of claim 1 , wherein the transaction is initiated by the customer, and the retrieving, the receiving of the encoded context, the accessing, the generating, the receiving of the indication of the customer response, and the training are performed in response to initiation of the transaction.