公开(公告)号：US12211106B2

公开(公告)日：2025-01-28

申请号：US17391101

申请日：2021-08-02

Applicant: Mastercard International Incorporated

Inventor： Smriti Gupta ,  Gaurav Dhama ,  Hardik Wadhwa ,  Puneet Vashisht ,  Yatin Katyal ,  Ankur Saraswat ,  Aakash Deep Singh

IPC: G06Q40/12 ,  G06F16/28 ,  G06N3/045

Abstract: A computing device for determining a new credit card number that is a continuation match with an old credit card number of a credit card account that has changed numbers comprises a processing element programmed to: receive transactional data for a plurality of credit card numbers, determine a plurality of old credit card numbers and a plurality of new credit card numbers, determine a plurality of clusters of new credit card numbers, convert the transactional data for each old credit card number and the associated cluster of new credit card numbers into snapshots with an image-like data format, train a modified siamese network with instances of snapshots of an old credit card number, a first new credit card number, and a second new credit card number, and use the modified siamese network to determine one new credit card number that is an upgrade of one old credit card number.

公开(公告)号：US20250139711A1

公开(公告)日：2025-05-01

申请号：US19008790

申请日：2025-01-03

Applicant: Mastercard International Incorporated

Inventor： Smriti Gupta ,  Gaurav Dhama ,  Hardik Wadhwa ,  Puneet Vashisht ,  Yatin Katyal ,  Ankur Saraswat ,  Aakash Deep Singh

IPC: G06Q40/12 ,  G06F16/28 ,  G06N3/045

Abstract: A computing device for determining a new credit card number that is a continuation match with an old credit card number of a credit card account that has changed numbers comprises a processing element programmed to: receive transactional data for a plurality of credit card numbers, determine a plurality of old credit card numbers and a plurality of new credit card numbers, determine a plurality of clusters of new credit card numbers, convert the transactional data for each old credit card number and the associated cluster of new credit card numbers into snapshots with an image-like data format, train a modified siamese network with instances of snapshots of an old credit card number, a first new credit card number, and a second new credit card number, and use the modified siamese network to determine one new credit card number that is an upgrade of one old credit card number.

公开(公告)号：US20230034850A1

公开(公告)日：2023-02-02

申请号：US17391101

申请日：2021-08-02

Applicant: Mastercard International Incorporated

Inventor： Smriti Gupta ,  Gaurav Dhama ,  Hardik Wadhwa ,  Puneet Vashisht ,  Yatin Katyal ,  Ankur Saraswat ,  Aakash Deep Singh

IPC: G06Q40/00 ,  G06F16/28 ,  G06N3/04

Abstract: A computing device for determining a new credit card number that is a continuation match with an old credit card number of a credit card account that has changed numbers comprises a processing element programmed to: receive transactional data for a plurality of credit card numbers, determine a plurality of old credit card numbers and a plurality of new credit card numbers, determine a plurality of clusters of new credit card numbers, convert the transactional data for each old credit card number and the associated cluster of new credit card numbers into snapshots with an image-like data format, train a modified siamese network with instances of snapshots of an old credit card number, a first new credit card number, and a second new credit card number, and use the modified siamese network to determine one new credit card number that is an upgrade of one old credit card number.

公开(公告)号：US20240119457A1

公开(公告)日：2024-04-11

申请号：US18482733

申请日：2023-10-06

Applicant: MASTERCARD INTERNATIONAL INCORPORATED

Inventor： Smriti Gupta ,  Adarsh Patankar ,  Akash Choudhary ,  Alekhya Bhatraju ,  Ammar Ahmad Khan ,  Amrita Kundu ,  Ankur Saraswat ,  Anubhav Gupta ,  Awanish Kumar ,  Ayush Agarwal ,  Brian M. McGuigan ,  Debasmita Das ,  Deepak Yadav ,  Diksha Shrivastava ,  Garima Arora ,  Gaurav Dhama ,  Gaurav Oberoi ,  Govind Vitthal Waghmare ,  Hardik Wadhwa ,  Jessica Peretta ,  Kanishk Goyal ,  Karthik Prasad ,  Lekhana Vusse ,  Maneet Singh ,  Niranjan Gulla ,  Nitish Kumar ,  Rajesh Kumar Ranjan ,  Ram Ganesh V ,  Rohit Bhattacharya ,  Rupesh Kumar Sankhala ,  Siddhartha Asthana ,  Soumyadeep Ghosh ,  Sourojit Bhaduri ,  Srijita Tiwari ,  Suhas Powar ,  Susan Skelsey

IPC: G06Q20/40

CPC classification number: G06Q20/4016

Abstract: Methods and server systems for computing fraud risk scores for various merchants associated with an acquirer described herein. The method performed by a server system includes accessing merchant-related transaction data including merchant-related transaction indicators associated with a merchant from a transaction database. Method includes generating a merchant-related transaction features based on the merchant-related indicators. Method includes generating via risk prediction models, for a payment transaction with the merchant, merchant health and compliance risk scores, merchant terminal risk scores, merchant chargeback risk scores, and merchant activity risk scores based on the merchant-related transaction features. Method includes facilitating transmission of a notification message to an acquirer server associated with the merchant. The notification message includes the merchant health and compliance risk scores, the merchant terminal risk scores, the merchant chargeback risk scores, and the merchant activity risk scores.

公开(公告)号：US20220366493A1

公开(公告)日：2022-11-17

申请号：US17739056

申请日：2022-05-06

Applicant: Mastercard International Incorporated

Inventor： Ankur Arora ,  Lalasa Dheekollu ,  Siddhartha Asthana ,  Amit Kumar ,  Smriti Gupta ,  Ankur Saraswat ,  Kandukuri Karthik ,  Kushagra Agarwal ,  Himanshi Charotia ,  Anket Prakash Hirulkar ,  Janu Verma ,  Kanishk Goyal ,  Gaurav Dhama

IPC: G06Q40/02

Abstract: Embodiments provide methods and systems for predicting overall account-level risks of cardholders. The method performed by server system includes accessing payment transaction data associated with a cardholder from a transaction database. Method includes generating a set of transaction features based on a set of transaction indicators. The method includes determining a plurality of network risk scores associated with the cardholder based on the set of transaction features and a set of trained machine learning models. The plurality of network risk scores includes a payment capacity risk score, a contactless payment risk score, and a set of account-level risk scores. The method includes aggregating the plurality of network risk scores to calculate an overall account risk score associated with the cardholder based on a statistical model. The method also includes transmitting a notification to the issuer server associated with the cardholder based on the overall account risk score.