Computer-based systems configured for accessing electronic data sources with invisible authentication and launching, and computer-based methods of use thereof
The present disclosure describes a server computing device configured for receiving from a remote computing device via an application, in response to a low-risk access request to a data resource, a programming call with a URL comprising an second identification data item encrypted from a first identification data item acquired by the remote computing device, obtaining a first context information item associated with the programming call, inputting the first context information item into a machine learning model to generate a second context information item, extracting the second identification data item from the URL, generating a third identification data item by decrypting the second identification data item, retrieving a prestored property data item associated with the third identification data item, and transmitting requested data to the remote computing device if comparing the second context information with the prestored property data item produces a match.
1 . A method, comprising:
receiving, by a server computing device, from a remote computing device associated with a user via an application, in response to one of a plurality of low-risk access requests to at least one data resource, a programming call with a uniform resource locator (URL), wherein the URL comprises an encrypted portion of a second identification data item and the programming call is a HTTP request, the encrypted portion being generated by the remote computing device in response to acquiring and based at least in part on a first identification data item, wherein a low-risk access request includes the user selecting one or more of checking an account balance, a transaction status or account activities on the remote computing device and the user selecting to log into their account for high-risk access includes the user performing one or more of transferring funds or initiating a transaction;
decrypting, by the server computing device, the encrypted portion of the second identification data item wherein the second identification data item is account identification information;
obtaining, by the server computing device, a first context information item associated with the programming call, wherein the first context information item includes an Internet Protocol (IP) address to determine location;
inputting, by the server computing device, the first context information item into a machine learning model to generate a second context information item to derive a likelihood that the user is in a customary area of operation based on past fully authenticated operations;
extracting, by the server computing device, the second identification data item from the URL;
generating, by the server computing device, a third identification data item by decrypting the second identification data item;
retrieving, by the server computing device, a prestored property data item associated with the third identification data item;
comparing, by the server computing device, the second context information item with the prestored property data item; and
transmitting, by the server computing device, requested data to the remote computing device to be displayed by the application when comparing the second context information with the prestored property data item produces a match, wherein the first, second and third identification data item are encrypted by the same key.
2 . The method according to claim 1 , further comprising designating, by a server computing device, the plurality of low-risk access requests and at least one high-risk access request.
3 . The method according to claim 1 , wherein the at least one data resource comprises an account in an electronic repository.
4 . The method according to claim 3 , wherein the first identification data item comprises an account number of the account in the electronic repository.
5 . The method according to claim 1 , wherein remote computing device is a smartphone, tablet or a personal computer.
6 . The method according to claim 1 , wherein acquiring, by the remote computing device, the first identification data item comprises scanning a quick response (QR) code or reading a near-field communication (NFC) tag.
7 . The method according to claim 1 , wherein the first context information comprises a phone number.
8 . The method according to claim 1 , wherein the machine learning model is trained using past authenticated user data.
9 . The method according to claim 1 , wherein the prestored property data item comprises a user registered location or a phone number.
10 . A system, comprising:
a plurality of processors of a server computing device; and
at least one memory storing a plurality of computing instructions configured to instruct at least one of the plurality of processors to:
receive from a remote computing device associated with a user via an application, in response to one of a plurality of low-risk access requests to at least one data resource, a programming call with a uniform resource locator (URL), wherein the URL comprises an encrypted portion of a second identification data item and the programming call is a HTTP request, the encrypted portion being generated by the remote computing device in response to acquiring and based at least in part on a first identification data item, wherein a low-risk access request includes the user selecting one or more of checking an account balance, a transaction status or account activities on the remote computing device and the user selecting to log into their account for high-risk access includes the user performing one or more of transferring funds or initiating a transaction;
decrypting, by the server computing device, the encrypted portion of the second identification data item wherein the second identification data item is account identification information;
obtain a first context information item associated with the programming call, wherein the first context information item includes an Internet Protocol (IP) address to determine location;
input the first context information item into a machine learning model to generate a second context information item to derive a likelihood that the user is in a customary area of operation based on past fully authenticated operations;
extract the second identification data item from the URL;
generate a third identification data item by decrypting the second identification data item;
retrieve a prestored property data item associated with the third identification data item;
compare the second context information item with the prestored property data item; and
transmit requested data to the remote computing device to be displayed by the application if when comparing the second context information with the prestored property data item produces a match, wherein the first, second and third identification data item are encrypted by the same key.
11 . The system according to claim 10 , wherein the plurality of computing instructions is further configured to instruct at least one of the plurality of processors to designate the plurality of low-risk access requests and at least one high-risk access request.
12 . The system according to claim 10 , wherein the at least one data resource comprises an account in an electronic repository.
13 . The system according to claim 12 , wherein the first identification data item comprises an account number of the account in the electronic repository.
14 . The system according to claim 10 , wherein acquiring the first identification data item comprises scanning a quick response (QR) code or reading a near-field communication (NFC) tag.
15 . The system according to claim 10 , wherein the first context information comprises a phone number.
16 . The system according to claim 10 , wherein the machine learning model is trained using past authenticated user data.
17 . The system according to claim 10 , wherein the prestored property data item comprises a user registered location or a phone number.