9,954,879 | 04/24/2018 | Workflow platform that allows customer teams to build and update their fraud processes without needing to write code; enables set up of workflows that automate any type of fraud detection achievable on Sift's platform. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/9954879 |
10,284,582 | 05/07/2019 | Workflow platform that allows customer teams to build and update their fraud processes without needing to write code; enables set up of workflows that automate any type of fraud detection achievable on Sift's platform. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10284582 |
10,643,216 | 05/05/2020 | Workflow platform that allows customer teams to build and update their fraud processes without needing to write code; enables set up of workflows that automate any type of fraud detection achievable on Sift's platform. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10643216 |
9,978,067 | 05/22/2018 | Enables the classification of multiple types of fraud and abuse simultaneously on a single account via the use of global and custom models, and ensemble of models. A distinct fraud score can be computed for each listed type of fraud. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/9978067 |
10,108,962 | 10/23/2018 | Enables the classification of multiple types of fraud and abuse simultaneously on a single account via the use of global and custom models, and ensemble of models. A distinct fraud score can be computed for each listed type of fraud. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10108962 |
10,296,912 | 05/21/2019 | Enables the classification of multiple types of fraud and abuse simultaneously on a single account via the use of global and custom models, and ensemble of models. A distinct fraud score can be computed for each listed type of fraud. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10296912 |
10,402,828 | 09/03/2019 | Enables the classification of multiple types of fraud and abuse simultaneously on a single account via the use of global and custom models, and ensemble of models. A distinct fraud score can be computed for each listed type of fraud. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10402828 |
10,181,032 | 01/15/2019 | Enables the detection of account misappropriation and produces a risk score that indicates when an account may be being used by someone other than the original creator. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10181032 |
10,482,395 | 11/19/2019 | Enables the detection of account misappropriation and produces a risk score that indicates when an account may be being used by someone other than the original creator. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10482395 |
10,339,472 | 07/02/2019 | Enables migration from an old risk scoring model to a new risk scoring model for a given customer to address changes and trends in fraud patterns. The calibration keeps score distributions stable even when Sift migrates customers between model types. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10339472 |
10,572,832 | 02/25/2020 | Enables migration from an old risk scoring model to a new risk scoring model for a given customer to address changes and trends in fraud patterns. The calibration keeps score distributions stable even when Sift migrates customers between model types. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10572832 |
10,341,374 | 07/02/2019 | Provides an analytical framework for evaluating anomalous shifts in risk scores for a given customer, allowing Sift to validate a new scoring model for a given customer before deployment and blocks deployment until validated. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10341374 |
10,462,172 | 10/29/2019 | Provides an analytical framework for evaluating anomalous shifts in risk scores for a given customer, allowing Sift to validate a new scoring model for a given customer before deployment and blocks deployment until validated. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10462172 |
10,623,423 | 04/14/2020 | Prevents interferences between customer analysts reviewing a transaction within the Sift platform, providing real time updates to systems and client browsers interacting with the review queue. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10623423 |
10,491,617 | 11/26/2019 | Varies the weights on a per customer basis of the models that make up Sift’s global scoring model to generate more accurate and specific risk scores. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10491617 |
10,666,674 | 05/26/2020 | Varies the weights on a per customer basis of the models that make up Sift’s global scoring model to generate more accurate and specific risk scores. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10666674 |
11,070,585 | 07/20/2021 | Produces a prediction that includes a risk score for posted content, and may include multiple distinct models that operate together as a unified risk model to predict whether abuse or fraudulent content is likely to occur. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11070585 |
11,303,665 | 04/12/2022 | Produces a prediction that includes a risk score for posted content, and may include multiple distinct models that operate together as a unified risk model to predict whether abuse or fraudulent content is likely to occur. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11303665 |
10,929,756 | 02/23/2021 | Provides a proxy model for interpreting complex black box models by constructing a surrogate model that mimics outputs of a black box model. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10929756 |
10,897,479 | 01/19/2021 | Provides automatic multi-factor authentication to Sift's service, enabling both direct verification requests and verification requests triggered by an automated workflow. Verification data may be used as training data to improve customer-specific models. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10897479 |
10,958,673 | 03/23/2021 | Provides automatic multi-factor authentication to Sift's service, enabling both direct verification requests and verification requests triggered by an automated workflow. Verification data may be used as training data to improve customer-specific models. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10958673 |
10,997,608 | 05/04/2021 | Enables a customer to Sift's service to determine false positive rates in declines or adverse decisions output from automated workflows. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/10997608 |
11,068,910 | 07/20/2021 | Enables a customer to Sift's service to determine false positive rates in declines or adverse decisions output from automated workflows. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11068910 |
11,037,173 | 06/15/2021 | Allows for automated anomaly detection in decisions output from automated workflows. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11037173 |
11,049,116 | 06/29/2021 | Allows for automated anomaly detection in decisions output from automated workflows. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11049116 |
11,330,009 | 05/10/2022 | Implements text clustering models and techniques to surface fraudulent or abusive patterns in online content across users. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11330009 |
11,528,290 | 12/13/2022 | Implements text clustering models and techniques to surface fraudulent or abusive patterns in online content across users. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11528290 |
11,429,974 | 08/30/2022 | Selectively identifies salient signals for card testing and converts those signals into learnable features that may be added to an existing machine learning. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11429974 |
11,620,653 | 04/04/2023 | Selectively identifies salient signals for card testing and converts those signals into learnable features that may be added to an existing machine learning. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11620653 |
11,409,629 | 08/09/2022 | Enables robust testing of workflow routes for identifying optimal routes for improving automated proposals for digital handling. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11409629 |
11,573,883 | 02/07/2023 | Enables robust testing of workflow routes for identifying optimal routes for improving automated proposals for digital handling. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11573883 |
11,496,501 | 11/08/2022 | Enables bulk labeling of corpora of data samples using a variety of techniques for exploring and identifying groups or networks of fraudulent and legitimate data samples. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11496501 |
11,645,386 | 05/09/2023 | Enables bulk labeling of corpora of data samples using a variety of techniques for exploring and identifying groups or networks of fraudulent and legitimate data samples. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11645386 |
11,575,695 | 02/07/2023 | Enables the creation of a connected component graph or network for exposing potential large scale attacks, such as bot attacks. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11575695 |
11,496,501 | 01/08/2022 | Introduces an active learning-informed data sampling technique for creating a labeled corpus of samples for effectively training a model. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11496501 |
11,887,126 | 3/17/2023 | Provides several mechanisms for automatically creating workflows and workflow routes for new and existing Sift customers. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11887126 |
11,916,927 | 11/07/2022; Second patent pending | Creates and enables an automated agent for accelerating chargeback disputes by automatically scoring the success of a chargeback based on known transaction evidence and proposing transaction evidence that may improve the probability of success. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11916927 | Second Patent Pending |
11,720,668 | 08/08/2023 | Identifies anomalies in risk score distributions including shifts or drifts to generate an explanation for the anomalous behavior(s) together with corrective actions taken to mitigate the anomalies. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11720668 |
11,841,941 | 06/16/2023 | Identifies anomalies in risk score distributions including shifts or drifts to generate an explanation for the anomalous behavior(s) together with corrective actions taken to mitigate the anomalies. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11841941 |
11,777,962 | 10/03/2023; Second patent allowed | Identifies fraudulent automated bot activities and generates a unique bot signature for each distinct bot that is detected and which can be leveraged in real-time bot identification to accelerate detection and threat mitigation posed by malicious bots. | https://ppubs.uspto.gov/dirsearch-public/print/downloadPdf/11777962 | Second Patent Allowed |
Pending | Second patent pending | Identifies fraudulent automated bot activities and generates a unique bot signature for each distinct bot that is detected and which can be leveraged in real-time bot identification to accelerate detection and threat mitigation posed by malicious bots. | Pending |
Pending | Patent pending | Allows customers to evaluate and respond to events based on multiple scoring criteria by introducing a technique that assigns both an event score and one or more percentile scores to each evaluated event, and enables customers to design related workflows. This invention involves using a T-Digest algorithm for calibration. | Pending |