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US Patent 11989740 Reducing false positives using customer feedback and machine learning

OverviewStructured DataIssuesContributorsActivity

Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
119897401
Patent Inventor Names
Miriam Valero1
Shanna L Phillips1
Russell Ruestman1
Timothy Kramme1
Puneit Dua1
Reena Batra1
Elizabeth A. Flowers1
Bradley A. Craig1
Date of Patent
May 21, 2024
1
Patent Application Number
179937581
Date Filed
November 23, 2022
1
Patent Citations
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US Patent 8073691 Method and system for screening using voice data and metadata
1
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US Patent 9858575 Fraud detection via mobile device location tracking
1
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US Patent 9883040 Fraud detection in interactive voice response systems
1
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US Patent 9916606 System and method for processing a transaction document including one or more financial transaction entries
1
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US Patent 9934498 Facilitating guaranty provisioning for an exchange
1
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US Patent 9947055 System and method for monitoring merchant transactions using aggregated financial data
1
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US Patent 9953326 Alert optimization system and method
1
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US Patent 10013646 Method and apparatus for transferring and processing transaction data
1
...
Patent Primary Examiner
‌
Scott C Anderson
1
CPC Code
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G06Q 20/3224
1
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G06Q 30/0185
1
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G06Q 30/0225
1
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G06Q 20/102
1
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G06Q 20/20
1
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G06N 20/00
1
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G06Q 20/24
1
Patent abstract

A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.

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