US 11,889,024 B2Granted

Caller verification via carrier metadata

AssigneePindrop Security, Inc.

InventorsJohn Cornwell, Terry Nelms, II

Life of this patent

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Abstract

Embodiments described herein provide for passive caller verification and/or passive fraud risk assessments for calls to customer call centers. Systems and methods may be used in real time as a call is coming into a call center. An analytics server of an analytics service looks at the purported Caller ID of the call, as well as the unaltered carrier metadata, which the analytics server then uses to generate or retrieve one or more probability scores using one or more lookup tables and/or a machine-learning model. A probability score indicates the likelihood that information derived using the Caller ID information has occurred or should occur given the carrier metadata received with the inbound call. The one or more probability scores be used to generate a risk score for the current call that indicates the probability of the call being valid (e.g., originated from a verified caller or calling device, non-fraudulent).

Claims20

Dependent claims

A computer-implemented method for caller verification, the method comprising:

obtaining, by the computer, a call-data pair of call data received for a current call, the call-data pair including a carrier metadata value of a type of carrier metadata value correlated to a derived metadata value of a type of derived metadata value;
obtaining, by the computer, probability data according to the call data of the current call, the probability data comprising a machine-learning architecture trained to determine a risk score for the call data and a probability value indicating a probability of occurrence of the call-data pair;
generating, by the computer, a feature vector for the current call based upon the probability value, the derived metadata value, and the carrier metadata value of the call-data pair;
generating, by the computer, the risk score for the current call by applying the machine-learning architecture on the feature vector of the current call;
and
identifying, by the computer, the current call as a fraudulent call in response to the computer determining that the risk score satisfies a fraud threshold score.

3 more elements

A system comprising:

a server comprising a processor configured to:
obtain a call-data pair of call data received for a current call, the call-data pair including a carrier metadata value of a type of carrier metadata value correlated to a derived metadata value of a type of derived metadata value;
obtain probability data according to the call data of the current call, the probability data comprising a machine-learning architecture trained to determine a risk score for the call data and a probability value indicating a probability of occurrence of the call-data pair;
generate a feature vector for the current call based upon the probability value, the derived metadata value, and the carrier metadata value of the call-data pair;
generate the risk score for the current call by applying the machine-learning architecture on the feature vector of the current call;
and
identify the current call as a fraudulent call in response to the server determining that the risk score satisfies a fraud threshold score.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/948,991Filed 20 Sep 2022 · continuation
Priority: 19 Aug 2019
Published: US 2023/0014180 A119 Jan 2023
Granted: 30 Jan 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification12 codes

H04M 3/5175
Centralised call answering arrangements requiring operator intervention , e.g. call or contact centers for telemarketing: call or contact centers…
G06F 18/214
Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation: generating training…
G06F 18/241
Classification techniques: relating to the classification model, e.g. parametric or non-parametric approaches
H04M 3/2218
Arrangements for supervision, monitoring or testing: call detail recording

Family

Application62/888,978Us provisional application · filed 19 Aug 2019
Application16/992,789Parent of this continuation · filed 13 Aug 2020
US 2023/0014180 A1Pre-grant publication · published 19 Jan 2023
US 11,470,194 B2Parent of this continuation
US 2021/0058507 A1Published application
US 11,889,024 B2This patent

From the US filing history. Foreign family members aren’t listed.