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EVIDENCE LAKE

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EVIDENCE LAKE
REGISTERED

on 11 Jun 2021

Last Applicant/ Owned by

GUARDIAN ANALYTICS INC.

2465 Latham St., Suite 200Mountain View, CA 94040

US

Serial Number

1876179 filed on 05th Jan 2018

Registration Number

TMA1101906 registered on 11th Jun 2021

Registration expiry Date

11th Jun 2031

Correspondent Address

1155 René-Lévesque Blvd. WestSuite 2500Montreal

QUEBEC

CA

H3B2K4

EVIDENCE LAKE

Trademark usage description

information, advice and consultancy relating to the monitoring of financial transactions; detecting and preventing suspicious financial behaviour and Read More

Classification Information

Class [036]
Information, advice and consultancy relating to the monitoring of financial transactions; detecting and preventing suspicious financial behaviour and reducing monetary losses; information, advice and consultancy relating to financial risk management

Classification kind code

11

Class [042]
Network based elastic computing providing a single source of truth in particular a Cloud-Based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake; electronic data storage and software-as-a-service for advanced risk scoring and model validation, monitoring, correlation and analytics of events, analysis of customer identity and relationships, monitoring and analysis of suspicious transactions, baselining of normal activity, detecting anomalous or suspicious activity, investigating linked relationships and activities, and generating or transmitting reports or electronic filings to regulatory authorities, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of ingesting and analyzing structured and unstructured data to detect financial crimes risk such as fraud and money laundering, analysis of customer identity and relationships to suspicious transactions, machine learning of normal activities, detection and alert of anomalous activities, investigation of linked relations and activities with ability to create case reports and e-filing suspicious activity reports to regulatory authorities; software-as-a-service for enabling tuning or setting of thresholds for risk scoring machine learning (ML) models, implementing customer segmentation to determine appropriate thresholds for risk scoring of ML models based on behaviour learned from respective customer segments, setting of initial thresholds for risk scoring ML models, implementing advanced machine learning algorithms to determine effective threshold values for application to a given scenario for successful detection of high risk events, tuning of risk scoring ML thresholds prior to going live with a dry run of an alertgeneration cycle in a test environment, and on-going tuning and enhancement of thresholds for risk scoring for ML models on a periodic basis to generate and investigate alerts below the risk scoring thresholds, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake, machine learning of normal activities, detection and alert of anomalous activities with risk scoring models, implementing customer segmentation to determine appropriate thresholds for the risk scoring models based on behaviors learning from respective segments setting of initial thresholds for risk scoring ML models, implementing advanced machine learning algorithms to determine effective threshold values for application to a given scenario for successful detection of high risk events, tuning of risk scoring ML thresholds prior to going live with a user acceptance testing of an alert-generation cycle in a test environment, and on-going tuning; software-as-a-service for providing a single source of truth assessment or risk assessment for any event-of-interest including detection and scoring by advanced cloud services driven artificial intelligence, machine learning and behavioural analytics, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake, machine learning of normal activities, detection and alert of anomalous activities with risk scoring models, implementing customer segmentation to determine appropriate thresholds for the risk scoring models based on behavioral analytics; software-as-aservice for multi-channel payment fraud detection and risk scoring services including automated clearing house services, wire services, online services, mobile services, supplier portal fraud detection services and analytics services, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake, machine learning of normal activities, detection and alert of anomalous activities with risk scoring models, implementing customer segmentation to determine appropriate thresholds for the risk scoring models based on behavioral analytics for the following digital banking and payments channels: automated clearing house services, wire services, online services, mobile services, supplier portal fraud detection services and analytics services; software-as-a-service for money laundering detection services, customer risk rating, transaction risk scoring, sanctions, watchlists and negative news screening, currency transaction report filings, suspicious activity report filings, link analysis, alerts/cases management, retaining evidence related to alerts/cases including documents, media, image files, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake., machine learning of normal activities, detection and alert of anomalous activities with risk scoring models, implementing customer segmentation to determine appropriate thresholds for the risk scoring models based on behavioral analytic, in particular for customer risk rating, transaction risk scoring, sanctions, watchlists and negative news screening, currency transaction report filings, suspicious activity report filings, link analysis, alerts/cases management, retaining evidence related to alerts/cases including documents, media, image files; software-as-a-service for publish-subscribe based real-time risk scoring and anomaly assessment of subscriber registered events-of-interest, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake, machine learning of normal activities, detection and alert of anomalous activities with risk scoring models for publish-subscribe based real-time risk scoring and anomaly assessment of subscriber registered events-of-interest; flexible public, managed on-premise, or managed hybrid cloud services options enabling the collection, analysis, processing, preservation, and reporting of events-of-interest in the form of electronic evidence, in particular a Cloud-based SaaS Financial crimes investigation platform, namely, cloud computing providing software for database management and cloud computing webhosting services in the field of generating risk alerts and enabling structured and unstructured aggregation and retention of risky events considered as evidence of illicit activities and stored in a cloud big data lake

Classification kind code

11

Mark Details

Serial Number

1876179

Mark Type

Trademark

Legal History

Show more

Action TakenStatus
Submitted for opposition 27
on 22nd Feb 2021		Approval Notice Sent
Submitted for opposition 48
on 29th Sep 2020		Agent Changed
Submitted for opposition 15
on 11th Aug 2020		Correspondence Created
Submitted for opposition 15
on 22nd Oct 2019		Correspondence Created
Submitted for opposition 67
on 11th Sep 2019		Agent Name Changed
Submitted for opposition 20
on 28th Feb 2019		Examiner's First Report
Submitted for opposition 22
on 27th Feb 2019		Search Recorded
Submitted for opposition 31
on 09th Jan 2018		Formalized
Submitted for opposition 1
on 08th Jan 2018		Created
Submitted for opposition 30
on 05th Jan 2018		Filed