公开(公告)号：US20190108465A1

公开(公告)日：2019-04-11

申请号：US16154223

申请日：2018-10-08

申请人： MASTERCARD INTERNATIONAL INCORPORATED

发明人： Xianzhe Zhou ,  Xiaoying Zhang ,  Meghana Santhapur

IPC分类号： G06Q10/06 ,  G06F17/27 ,  G06F17/16

摘要： Systems and methods are provided for predicting a probability of a problem in a service at a service provider based on implementation of a change to the service. One exemplary method includes a risk engine accessing change records for historical changes in services associated with the service provider where each record includes a text description of the implemented change and a problem/no problem result for the change. For each record, the risk engine normalizes the text description of the implemented change and generates a word-count matrix based on the normalized text description. The risk engine then performs a regression analysis of the generated word-count matrices for the records and the corresponding problem/no problem results, thereby providing a regression model, and generates a predictive algorithm based on a score provided from the regression model and at least one change factor associated with the change records.

公开(公告)号：US20210304207A1

公开(公告)日：2021-09-30

申请号：US17345642

申请日：2021-06-11

申请人： MASTERCARD INTERNATIONAL INCORPORATED

发明人： Walter F. Lo Faro ,  MohammadMehdi Kafashan ,  Elieser J. Barrios ,  Xiaoying Zhang ,  Ravi Santosh Arvapally ,  Xianzhe Zhou

IPC分类号： G06Q20/40 ,  G06N20/00 ,  G06N5/04 ,  G06Q40/02

摘要： Systems and methods are provided for performing anomaly detection. One example method relates to transaction data including fraud scores output by a fraud score model generated by a machine learning system. The method includes determining, by a computing device, divergence values for multiple segments of payment accounts between baseline distributions of fraud scores and current distributions of fraud scores for the segments and detecting, by the computing device, at least one of the divergence values for at least one of the multiple segments as an anomaly. The method also includes categorizing, by the computing device, the detected anomaly into one of multiple categories, whereby the one of the multiple categories is indicative of a type of issue associated with the detected anomaly.

公开(公告)号：US11514533B2

公开(公告)日：2022-11-29

申请号：US16718737

申请日：2019-12-18

申请人： MASTERCARD INTERNATIONAL INCORPORATED

发明人： Melinda L. Rolfs ,  Jonathan Trivelas ,  Nicole Marie Katzman ,  Paul John Paolucci ,  Gary Adler ,  Luis F. Rodriguez-Lemus ,  Xianzhe Zhou

IPC分类号： G06Q40/00 ,  G06F16/953 ,  G06F16/23 ,  G06Q20/40

摘要： A computer system for identifying merchant category code misclassifications includes at least one processor in communication with a transaction database and a high-risk merchant database. The transaction database stores transaction records by a plurality of account holders. The high-risk merchant database stores high-risk merchant records each associated with high-risk merchants. The processor queries the transaction database for transaction records and calculates a high-risk cardholder metric for each of the account numbers. The at least one processor further queries the transaction database for transaction records including (i) the account number of high-risk cardholders, and (ii) a merchant identifier associated with other than the plurality of high-risk merchants, to retrieve a second set of transaction records. The at least one processor further calculates a high-risk merchant metric for each of the merchant identifiers, identifying a MCC misclassified merchant.

公开(公告)号：US12094011B2

公开(公告)日：2024-09-17

申请号：US18056152

申请日：2022-11-16

申请人： MASTERCARD INTERNATIONAL INCORPORATED

发明人： Melinda L. Rolfs ,  Jonathan Trivelas ,  Nicole Marie Katzman ,  Paul John Paolucci ,  Gary Adler ,  Luis F. Rodriguez-Lemus ,  Xianzhe Zhou

IPC分类号： G06Q40/00 ,  G06F16/23 ,  G06F16/953 ,  G06Q20/40 ,  G06Q40/12

CPC分类号： G06Q40/12 ,  G06F16/2379 ,  G06F16/953 ,  G06Q20/4016

摘要： A computer system for identifying merchant category code misclassifications includes at least one processor in communication with a transaction database and a merchant database. The transaction database stores transaction records by a plurality of account holders. The processor generates a first MCC profile including at least one transaction characteristic representative of merchants properly classified as the first MCC and comparing the first MCC profile to a second set of transaction records. If the comparison satisfies a comparison threshold for the first MCC the processor identifies the corresponding selected merchant as being MCC misclassified.

公开(公告)号：US20230079865A1

公开(公告)日：2023-03-16

申请号：US18056152

申请日：2022-11-16

申请人： MASTERCARD INTERNATIONAL INCORPORATED

发明人： Melinda L. Rolfs ,  Jonathan Trivelas ,  Nicole Marie Katzman ,  Paul John Paolucci ,  Gary Adler ,  Luis F. Rodriguez-Lemus ,  Xianzhe Zhou

IPC分类号： G06Q40/00 ,  G06F16/953 ,  G06F16/23 ,  G06Q20/40

摘要： A computer system for identifying merchant category code misclassifications includes at least one processor in communication with a transaction database and a merchant database. The transaction database stores transaction records by a plurality of account holders. The processor generates a first MCC profile including at least one transaction characteristic representative of merchants properly classified as the first MCC and comparing the first MCC profile to a second set of transaction records. If the comparison satisfies a comparison threshold for the first MCC the processor identifies the corresponding selected merchant as being MCC misclassified.

公开(公告)号：US20210192640A1

公开(公告)日：2021-06-24

申请号：US16718737

申请日：2019-12-18

申请人： MASTERCARD INTERNATIONAL INCORPORATED

发明人： Melinda L. Rolfs ,  Jonathan Trivelas ,  Nicole Marie Katzman ,  Paul John Paolucci ,  Gary Adler ,  Luis F. Rodriguez-Lemus ,  Xianzhe Zhou

IPC分类号： G06Q40/00 ,  G06Q20/40 ,  G06F16/23 ,  G06F16/953

摘要： A computer system for identifying merchant category code misclassifications includes at least one processor in communication with a transaction database and a high-risk merchant database. The transaction database stores transaction records by a plurality of account holders. The high-risk merchant database stores high-risk merchant records each associated with high-risk merchants. The processor queries the transaction database for transaction records and calculates a high-risk cardholder metric for each of the account numbers. The at least one processor further queries the transaction database for transaction records including (i) the account number of high-risk cardholders, and (ii) a merchant identifier associated with other than the plurality of high-risk merchants, to retrieve a second set of transaction records. The at least one processor further calculates a high-risk merchant metric for each of the merchant identifiers, identifying a MCC misclassified merchant.