US 12,411,921 B2
System and method for detecting login fraud based on a machine learning model
Kumar Rao Krishnagi, Powell, OH (US); Rupa Shah, Morristown, NJ (US); Gaurav Chawla, Hoboken, NJ (US); and Vaibhav Vaibhav, Bernardsville, NJ (US)
Assigned to JPMORGAN CHASE BANK, N.A., New York, NY (US)
Filed by JPMorgan Chase Bank, N.A., New York, NY (US)
Filed on Apr. 28, 2023, as Appl. No. 18/140,934.
Claims priority of provisional application 63/365,221, filed on May 24, 2022.
Prior Publication US 2023/0385390 A1, Nov. 30, 2023
Int. Cl. G06F 21/31 (2013.01); G06F 21/32 (2013.01)
CPC G06F 21/32 (2013.01) [G06F 21/316 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method for detecting login fraud based on a machine learning model by utilizing one or more processors along with allocated memory, the method comprising:
accessing a database that stores user biometrics data and a pattern of activity logs data of the user utilized for past authentication purposes for logging into a plurality of systems;
creating a machine learning model configured to be trained to generate a score based on the user biometrics data and the pattern of activity logs data;
training the machine learning model with the user biometrics data and the pattern of activity logs data in real-time;
receiving user credentials data from the user for login attempt into a system among the plurality of systems;
comparing the received user credentials data with the biometrics data and the pattern of activity logs data of the user stored on the database and the machine learning model;
generating the score, in response to comparing, by utilizing the trained machine learning model, wherein the score is a value that is compared with a predetermined threshold value to determine in real-time whether the login attempt is fraudulent or not fraudulent;
transmitting, in response to detecting that the user's login attempt is fraudulent, an electronic notification to a user's computing device associated with the user's previous successful login indicating that a location or a computing device the user is currently utilizing to attempt login does not match with the prestored pattern of actively logs data of the user;
receiving user's input data from the user's computing device associated with the user's previous successful login indicating that the location or the computing device the user is currently utilizing to attempt login is actually correct;
allowing the user to access the system based on receiving the user's input data; and
retraining the machine learning model with data associated with allowing the user to access the system.