公开(公告)号：US20250111011A1

公开(公告)日：2025-04-03

申请号：US18374799

申请日：2023-09-29

Applicant: Visa International Service Association

Inventor： Junpeng Wang ,  Minghua Xu ,  Shubham Jain ,  Yan Zheng ,  Michael Yeh ,  Liang Wang ,  Wei Zhang

IPC: G06F17/18

Abstract: Methods, systems, and computer program products are provided for coordinated analysis of output scores and input features of machine learning models in different environments. An example method includes receiving a plurality of first data records and a plurality of second data records. A first plot is generated based on a first score generated by a machine learning model for each first data record and a second score generated by the machine learning model for each second data record. The first plot is displayed. A plurality of second plots associated with at least a subset of the plurality of features are generated. Each respective second plot is generated based on a respective first field associated with a respective feature from the first data records and a respective second field associated with the respective feature from the second data records. The second plots are displayed.

公开(公告)号：US20240177071A1

公开(公告)日：2024-05-30

申请号：US18281663

申请日：2022-03-30

Applicant: Visa International Service Association

Inventor： Junpeng Wang ,  Liang Wang ,  Yan Zheng ,  Michael Yeh ,  Shubham Jain ,  Wei Zhang ,  Zhongfang Zhuang ,  Hao Yang

IPC: G06N20/20 ,  G06F18/2415

CPC classification number: G06N20/20 ,  G06F18/2415

Abstract: Systems, methods, and computer program products may compare machine learning models by identifying data instances with disagreed predictions and learning from the disagreement. Based on a model interpretation technique, differences between the compared machine learning models may be interpreted. Multiple metrics to prioritize meta-features from different perspectives may also be provided.

公开(公告)号：US20220414665A1

公开(公告)日：2022-12-29

申请号：US17781209

申请日：2021-11-05

Applicant: Visa International Service Association

Inventor： Dhruv Gelda ,  Shubham Jain ,  Andrew Malachy McGloin ,  Wei Zhang ,  Hao Yang ,  Liang Wang

IPC: G06Q20/40 ,  G06N3/08

Abstract: A method of determining fraud includes: receiving a transaction request associated with a first payment transaction between a merchant and a user from a merchant system; generating a first risk score based on the transaction request and a first set pot of transaction data received prior to the transaction request; processing a transaction request approval based on the first risk score not satisfying a first threshold; receiving a risk score request associated with the first payment transaction, where the risk score request is received after the transaction request has been approved; generating a second risk score based on a second set of transaction data received after the first risk score is determined; and automatically classifying the first payment transaction as potentially fraudulent in response to determining that the second risk score satisfies a second threshold.

公开(公告)号：US11922422B2

公开(公告)日：2024-03-05

申请号：US17781209

申请日：2021-11-05

Applicant: Visa International Service Association

Inventor： Dhruv Gelda ,  Shubham Jain ,  Andrew Malachy McGloin ,  Wei Zhang ,  Hao Yang ,  Liang Wang

IPC: G06Q20/40

CPC classification number: G06Q20/4016 ,  G06Q20/407

Abstract: A method of determining fraud includes: receiving a transaction request associated with a first payment transaction between a merchant and a user from a merchant system; generating a first risk score based on the transaction request and a first set pot of transaction data received prior to the transaction request; processing a transaction request approval based on the first risk score not satisfying a first threshold; receiving a risk score request associated with the first payment transaction, where the risk score request is received after the transaction request has been approved; generating a second risk score based on a second set of transaction data received after the first risk score is determined; and automatically classifying the first payment transaction as potentially fraudulent in response to determining that the second risk score satisfies a second threshold.

公开(公告)号：US12253991B2

公开(公告)日：2025-03-18

申请号：US18280828

申请日：2022-06-09

Applicant: Visa International Service Association

Inventor： Yan Zheng ,  Wei Zhang ,  Michael Yeh ,  Liang Wang ,  Junpeng Wang ,  Shubham Jain ,  Zhongfang Zhuang

IPC: G06F16/00 ,  G06F16/22

Abstract: Provided is a system for analyzing features associated with entities using an embedding tree, the system including at least one processor programmed or configured to receive a dataset associated with a plurality of entities, wherein the dataset comprises a plurality of data instances for a plurality of entities. The processor may be programmed or configured to generate at least two embeddings based on the dataset and determine split criteria for partitioning an embedding space of at least one embedding tree associated with the dataset based on feature data associated with an entity and embedding data associated with the at least two embeddings. The processor may be programmed or configured to generate at least one embedding tree having a plurality of nodes based on the split criteria. Methods and computer program products are also provided.

公开(公告)号：US20240403715A1

公开(公告)日：2024-12-05

申请号：US18694152

申请日：2021-09-22

Applicant: Visa International Service Association

Inventor： Liang Wang ,  Junpeng Wang ,  Yan Zheng ,  Shubham Jain ,  Michael Yeh ,  Zhongfang Zhuang ,  Wei Zhang ,  Hao Yang

IPC: G06N20/00 ,  G06N5/022

Abstract: Systems, methods, and computer program products that obtain a plurality of features associated with a plurality of samples and a plurality of labels for the plurality of samples; generate a plurality of first predictions for the plurality of samples with a first machine learning model; generate a plurality of second predictions for the plurality of samples with a second machine learning model; generate, based on the plurality of first predictions, the plurality of second predictions, the plurality of labels, and a plurality of groups of samples of the plurality of samples; determine, based on the plurality of groups of samples, a first success rate associated with the first machine learning model and a second success rate associated with the second machine learning model; and identify, based on the first success rate and the second success rate, a weak point in the machine learning first model or the second model.

公开(公告)号：US20240152499A1

公开(公告)日：2024-05-09

申请号：US18280828

申请日：2022-06-09

Applicant: Visa International Service Association

Inventor： Yan Zheng ,  Wei Zhang ,  Michael Yeh ,  Liang Wang ,  Junpeng Wang ,  Shubham Jain ,  Zhongfang Zhuang

IPC: G06F16/22

CPC classification number: G06F16/2246

Abstract: Provided is a system for analyzing features associated with entities using an embedding tree, the system including at least one processor programmed or configured to receive a dataset associated with a plurality of entities, wherein the dataset comprises a plurality of data instances for a plurality of entities. The processor may be programmed or configured to generate at least two embeddings based on the dataset and determine split criteria for partitioning an embedding space of at least one embedding tree associated with the dataset based on feature data associated with an entity and embedding data associated with the at least two embeddings. The processor may be programmed or configured to generate at least one embedding tree having a plurality of nodes based on the split criteria. Methods and computer program products are also provided.