List of LatentView PRISM Customers
Chennai, 600113,
India
Since 2010, our global team of researchers has been studying LatentView PRISM customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased LatentView PRISM for AML, Fraud and Compliance from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using LatentView PRISM for AML, Fraud and Compliance include: 7-Eleven, a United States based Retail organisation with 138808 employees and revenues of $87.60 billion, Uber, a United States based Transportation organisation with 31100 employees and revenues of $43.98 billion, eBay, a United States based Retail organisation with 11500 employees and revenues of $2.60 billion and many others.
Contact us if you need a completed and verified list of companies using LatentView PRISM, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The LatentView PRISM customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
 |
7-Eleven | Retail | 138808 | $87.6B | United States | LatentView Analytics | LatentView PRISM | AML, Fraud and Compliance | 2020 | n/a |
In 2020 7-Eleven implemented LatentView PRISM for AML, Fraud and Compliance. LatentView supported 7-Eleven with reporting, visualization and AI/ML analytics to surface root causes across transaction and customer datasets in the US retail environment, improving insight-driven decisions.
LatentView PRISM was configured to deliver layered reporting and visualization, statistical anomaly detection and model-driven transaction scoring consistent with AML, Fraud and Compliance workflows. The implementation emphasized aggregated transaction analytics, customer behavior segmentation and root-cause analysis to prioritize investigative cases. The application name LatentView PRISM appears in operational dashboards used by analytics and risk teams.
The deployment connected to enterprise transaction and customer datasets to enable cross-source correlation and historical trend analysis, supporting investigations and operational monitoring. Operational scope focused on US retail operations and central analytics teams. Business functions impacted included fraud operations, loss prevention and enterprise analytics, establishing LatentView PRISM as the company AML, Fraud and Compliance solution supporting these functions.
Governance centered on centralized analytics ownership and staged rollouts to business stakeholders, with reporting workflows established for investigative teams and risk managers. The engagement improved insight-driven decisions through visualization and AI/ML analytics, as reported by the source.
|
 |
eBay | Retail | 11500 | $2.6B | United States | LatentView Analytics | LatentView PRISM | AML, Fraud and Compliance | 2022 | n/a |
In 2022, eBay implemented LatentView PRISM to support AML, Fraud and Compliance analytics for its global strategy group. LatentView provided ongoing analytics support to eBay’s global strategy team, delivering analytic outputs used in C-level presentations and informing strategic decisions across commerce and payments in the United States.
The LatentView PRISM deployment was structured around category-aligned capabilities expected of an AML, Fraud and Compliance application, with emphasis on transaction monitoring, anomaly detection, risk scoring, and model management. Implementation work focused on analytical model development, scoring pipelines, and executive dashboarding to translate detections and risk signals into decision-ready insights.
Operational coverage targeted commerce and payments data streams used by eBay’s US business and the global strategy organization, with analytics delivered into executive reporting and strategy forums. The implementation integrated analytics workflows with existing payments and commerce transaction feeds to enable continuous monitoring and periodic executive summaries, while preserving control of source data and model outputs within the strategy group.
Governance oriented the PRISM outputs toward strategic decision cycles and C-level presentation cadence, embedding analytic artifacts into existing reporting and review processes. The narrative reflects that LatentView’s ongoing analytics engagement was applied to AML, Fraud and Compliance use cases via LatentView PRISM, supporting eBay’s payments and commerce strategic decisioning.
|
 |
Uber | Transportation | 31100 | $44.0B | United States | LatentView Analytics | LatentView PRISM | AML, Fraud and Compliance | 2020 | n/a |
In 2020, Uber engaged LatentView Analytics in the United States and public disclosures support an inferred deployment of LatentView PRISM for AML, Fraud and Compliance to address payments and fraud risk associated with ride hailing transactions. The source lists LatentView as a service provider for technology and payments related use cases, and attribution to the LatentView PRISM product is inferred from LatentView's PRISM positioning and the payments focus of the engagement.
The implementation scope is described around payments and technology functions, with LatentView PRISM for AML, Fraud and Compliance positioned to support transaction monitoring, anomaly detection, risk scoring, rule orchestration, and alert generation as category aligned capabilities. Configuration would plausibly include a mix of model scoring and rule based detection, pipelines for real time event ingestion and batch reconciliation, and investigator facing case records to enable triage by fraud analysts.
Operational coverage is centered on the US region and payments workflows, integrating enriched transaction feeds, settlement records, and rider metadata to improve signal quality and support downstream case management. Governance and operating cadence would be expected to include rule tuning, analyst feedback loops for model refinement, and formal handoffs between engineering, payments operations, and fraud investigation teams, consistent with deployments in the AML, Fraud and Compliance category.
|
Buyer Intent: Companies Evaluating LatentView PRISM
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||