公开(公告)号：US20240403369A1

公开(公告)日：2024-12-05

申请号：US18733518

申请日：2024-06-04

Applicant: MASTERCARD INTERNATIONAL INCORPORATED

Inventor： Akshay Sethi ,  Ayush Agarwal ,  Nancy Agrawal ,  Siddhartha Asthana ,  Sonia Gupta

IPC: G06F16/906 ,  G06F16/901

Abstract: Methods and systems for training artificial intelligence (AI)-based models using limited labeled data are disclosed. The method performed by a server system includes accessing a tabular dataset including tabular data that further labeled data and unlabeled data. Method includes generating labeled features including labeled numerical features and labeled categorical features based on the labeled data and generating unlabeled features including unlabeled numerical features and unlabeled categorical features based on the unlabeled data. Method includes determining, via a first transformer model, a contextual numerical embeddings based on the labeled numerical features and the unlabeled numerical features. Method includes determining, via a second transformer model, a contextual categorical embeddings based on the labeled categorical features and the unlabeled categorical features. Method includes generating a concatenated embeddings based on concatenating the contextual numerical embeddings and the contextual categorical embeddings. Method includes generating a third transformer model based on the concatenated embeddings.

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.